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About SWMM
An open-source, comprehensive model for continuous and
single-event simulation of runoff quantity and quality for
stormwater, sanitary and combined sewer systems, SWMM
can model: dynamic storms; pollutant build-up, washoff and
transport; infiltration and inflow; dynamic routing; surcharging,
surface flooding; storage ponds; storage treatment; diversions;
pumping stations; various BMPs and LIDs; and much more.
PCSWMM incorporates SWMM5.
water systems
models
water systems models
user’s
guide
to swmm5
user’s guide
to swmm5
13th edition
13th edition
About PCSWMM
PCSWMM is CHI’s comprehensive, GIS-based, graphical
decision support system for SWMM urban drainage modeling
(sanitary, storm and/or combined systems). It is a fully-featured
urban drainage system modeling package, with no limitations
on model size or complexity, includes a complete, smart GIS
engine and provides native support for a large number of
GIS formats, as well as powerful topological operators and
querying. PCSWMM has been the trusted spatial decision
support system for US EPA SWMM for over 25 years.
William James
Lewis E. Rossman
W. Robert C. James
William James
Lewis E. Rossman
W. Robert C. James
Based on original USEPA
SWMM documentation
Based on original USEPA
SWMM documentation
About CHI
Since 1978, Computational Hydraulics International (CHI) has
developed, marketed and supported technically advanced,
professional software systems for stormwater management,
wastewater and watershed modeling. Licensed under the
Professional Engineers of Ontario, our technology is used by
more than 3,000 clients, has been successfully applied in over
10,000 projects in more than 50 countries.
CHI R242 · ISBN # 978-0-9808853-5-4
press
press
press
User’s guide to SWMM 5 Available books of the SWMM User Group
Cognitive Modeling of Urban Water Systems Monograph 19, 2010, ISBN 978-0-9808853-X-X. R241
Dynamic Modeling of Urban Water Systems Monograph 18, 2009 ISBN 978-0-9808853-3-0. (R236)
Conceptual Modeling of Urban Water Systems Monograph 17, 2008 ISBN 978-0-9808853-2-3. R229
Reliable Modeling of Urban Water Systems Monograph 16, 2007 ISBN 0-9736716-0-9 (R228)
Contemporary Modeling of Urban Water Systems Monograph 15, 2006 ISBN 0-9736716-3-7 (R227)
Intelligent Modeling of Urban Water Systems Monograph 14, 2005 ISBN 0-9736716-2-9 (R225)
Effective Modeling of Urban Water Systems Monograph 13, 2004 ISBN 0-9736716-0-2 (R223)
Innovative Modeling of Urban Water Systems Monograph 12, 2003 ISBN 0-9683681-9-0 (R220)
Practical Modeling of Urban Water Systems Monograph 11, 2002 ISBN 0-9683681-7-4
Best Modeling Practices for Urban Water Systems Monograph 10, 2001 ISBN:0-9683681-6-6
Models and Applications to Urban Water Systems Monograph 9, 2000 ISBN:0-9683681-4-X
Applied Modeling of Urban Water Systems Monograph 8, 1999 ISBN:0-9683681-3-1
New Applications in Modeling Urban Water Systems Monograph 7, 1998 ISBN:0-9697422-9-0
Advances in Modeling the Management of Stormwater Impacts Vol 6, 1997 ISBN:0-9697422-8-2
Advances in Modeling the Management of Stormwater Impacts Vol 5, 1996 ISBN:0-9697422-7-4
Advances in Modeling the Management of Stormwater Impacts, 1995 ISBN:0-9697422-5-8
Modern Methods for Modeling the Management of Stormwater Impacts, 1994 ISBN: 0-9697422-X-X
Current Practices in Modelling the Management of Stormwater Impacts 1993 ISBN: 1-56670-052-3
New Techniques for Modelling the Management of Stormwater Impacts, 1992 ISBN: 0-87371-898-4
Also available:
Rules for Responsible Modeling. William James, 2003, 300pp. ISBN: 0-9683681-5-8
Order from CHI at www.chiwater.com
or by fax: 519-489-0695; or email: [email protected]
ii
User’s guide to SWMM 5 by William James, Lewis A. Rossman and W. Robert C. James Including material from: SWMM User’s manual Version 5 (Lewis A. Rossman, 2010) [EPA/600/R-­‐05/040] SWMM 5 Manual (Lewis A. Rossman, 2008) [EPA/600/R-­‐05/040] Storm Water Management Model Quality Assurance Report: Dynamic Wave Flow Routing (Lewis A. Rossman, 2006) [EPA/600/R-­‐06/097] Storm Water Management Model Version 4: User's Manual (Wayne C. Huber and Robert E. Dickinson, 1988) [EPA/600/3-­‐88/001a(?)] Extran Addendum (Larry A. Roesner, John A. Aldrich and Robert E. Dickinson, 1989) [EPA/600/3-­‐88/001b] This is the 13th edition of the SWMM guides produced by CHI, and the second SWMM 5 edition, dated November 2010. CHI Press Publication R242 iii
International Standard Book Number
(ISBN) 978-0-9808853-5-4
CHI Catalog Number R242
Reference Data:
User’s guide to SWMM 5
xl + 905 pp.
James, William, 1937–, Rossman, Lewis A. and James, W. R. C.
Published by CHI, Guelph, Ontario, Canada.
Cover design by LIND design, Guelph.
© COPYRIGHT 2010
by COMPUTATIONAL HYDRAULICS INTERNATIONAL
ALL RIGHTS RESERVED
This book represents information quoted from authentic and highly regarded
sources. Reprinted material is quoted with permission, and sources are indicated.
A wide variety of references is listed. Every reasonable effort has been made to
give reliable data and information, but the authors, the editors and the publisher
cannot assume responsibility for the validity of all the materials or for the consequences of their use.
Replaces the 2008 User’s guide to SWMM 5, 12th edition
(ISBN 978-0-9808853-1-6)
PRINTED IN USA
iv
Preface to the 13th edition of the User’s guide
Consequences of water mismanagement are so dire that computer models used
for water systems planning, design, construction, operation, maintenance and
litigation have to be robustly reliable. Models used to evaluate, analyze and
manage flow and pollutant problems of storm water runoff, sanitary flows and
combined sewer overflows are based on the latest knowledge of their physics,
chemistry and environmental impacts. One of the first of such models and the de
facto standard is the USEPA Storm Water Management Model (SWMM).
This User’s guide to SWMM 5 has been compiled from earlier sources as an
interim measure, to bridge the gap until a complete SWMM 5 manual, with theoretical background, is released (now way overdue). The present guide includes:
・ a more narrowly-focused version (than appeared in the last edition,
12, of the User’s guide to SWMM 5) of the portions of the two
1988/9 user's manuals for SWMM 4, originally written by Wayne
Huber, Bob Dickinson, Larry Roesner and John Aldrich, which—in
the absence of a comprehensive theory component in the current
SWMM 5 manual—are a guide to understanding the theory behind
SWMM;
・ the current SWMM 5 Manual (updated to August 2010) —a practical
user's guide—by Lew Rossman;
・ the Stormwater Management Model Quality Assurance Report: Dynamic Wave Flow Routing by Lew Rossman;
・ the SWMM Applications Manual by Jorge Gironas, Larry Roesner
and Jennifer Davis, (downloaded September 2010); and
・ material derived from elsewhere, such as the SWMM Q&A archive
(from the SWMM Users List).
The text from all these sources, and indeed from the previous edition of the
SWMM 5 User’s guide, has been rearranged and changed. Instructions on the
use of the model and cautions known to the writer(s) are included. Much material in the original documentation deemed to be outdated, or irrelevant has been
deleted.
For those who may be unfamiliar with some of the terminology used in these
manuals, a Glossary is provided at the end of the volume.
William James
University Professor Emeritus, School of Engineering, University of
Guelph, and President, CHI, Guelph, Canada
v
Disclaimer The programs and this manual must be used at the user's own risk. The U.S. Environmental
Protection Agency, and the program and the authors are not responsible and assume no liability whatsoever for any results or any use made of the results obtained from these programs,
nor for any damages or litigation that result from the use of these programs for any purpose.
Mention of trade names or commercial products does not constitute endorsement or recommendation for use.
Original disclaimer for the SWMM 5 Manual The information in this document has been funded wholly or in part by the U.S. Environmental Protection Agency (USEPA). It has been subjected to the Agency’s peer and
administrative review, and has been approved for publication as an EPA document. Mention
of trade names or commercial products does not constitute endorsement or recommendation
for use.
Although a reasonable effort has been made to assure that the results obtained are correct,
the computer programs described in this manual are experimental. Therefore the author and
the U.S. Environmental Protection Agency are not responsible and assume no liability whatsoever for any results or any use made of the results obtained from these programs, nor for
any damages or litigation that result from the use of these programs for any purpose.
Original acknowledgments in the SWMM 5 manual The development of SWMM 5 was pursued under a Cooperative Research and Development
Agreement between the Water Supply and Water Resources Division of the U.S. Environmental Protection Agency and the consulting engineering firm of Camp Dresser & McKee
Inc. The project team consisted of the following individuals:
USEPA
CDM
Lewis Rossman
Robert Dickinson
Trent Schade
Carl Chan
Daniel Sullivan (retired)
Edward Burgess
The team would like to acknowledge the assistance provided by Wayne Huber (Oregon
State University), Dennis Lai (USEPA), and Michael Gregory (CDM). We also want to
acknowledge the contributions made by the following individuals to previous versions of
SWMM that we drew heavily upon in this new version: John Aldrich, Douglas Ammon, Carl
W. Chen, Brett Cunningham, Robert Dickinson, James Heaney, Wayne Huber, Miguel Medina, Russell Mein, Charles Moore, Stephan Nix, Alan Peltz, Don Polmann, Larry Roesner,
Charles Rowney, and Robert Shubinsky. Finally, we wish to thank Wayne Huber, Thomas
Barnwell (USEPA), Richard Field (USEPA), Harry Torno (USEPA retired) and William
James (University of Guelph) for their continuing efforts to support and maintain the program
over the past several decades.
Original disclaimer for the Quality Assurance Report: Dynamic Wave Flow Routing. EPA/600/R-­‐06/097 The information in this document has been funded wholly or in part by the U.S. Environmental Protection Agency (USEPA). It has been subjected to the Agency’s peer and
administrative review, and has been approved for publication as an EPA document. Mention
of trade names or commercial products does not constitute endorsement or recommendation
for use.
vi
Original foreword to Quality Assurance Report: Dynamic Wave Flow Routing The U.S. Environmental Protection Agency is charged by Congress with protecting the Nation’s land, air, and water resources. Under a mandate of national environmental laws, the
Agency strives to formulate and implement actions leading to a compatible balance between
human activities and the ability of natural systems to support and nurture life. To meet this
mandate, EPA’s research program is providing data and technical support for solving environmental problems today and building a science knowledge base necessary to manage our
ecological resources wisely, understand how pollutants affect our health, and prevent or reduce environmental risks in the future.
The National Risk Management Research Laboratory is the Agency’s center for investigation of technological and management approaches for reducing risks from threats to human
health and the environment. The focus of the Laboratory’s research program is on methods for
the prevention and control of pollution to the air, land, water, and subsurface resources; protection of water quality in public water systems; remediation of contaminated sites and ground
water; and prevention and control of indoor air pollution. The goal of this research effort is to
catalyze development and implementation of innovative, cost-effective environmental technologies; develop scientific and engineering information needed by EPA to support regulatory
and policy decisions; and provide technical support and information transfer to ensure effective implementation of environmental regulations and strategies.
Water quality impairment due to runoff from urban and developing areas continues
to be a major threat to the ecological health of our nation’s waterways. The EPA Storm Water
Management Model is a computer program that can assess the impacts of such runoff and
evaluate the effectiveness of mitigation strategies. This report documents the Quality Assurance testing that was performed on the dynamic wave flow routing portion of the recently
modernized and updated version 5.0 of the model. As a result of this testing, users can have
confidence that the updated model is performing correctly.
Sally C. Gutierrez, Director
National Risk Management Research Laboratory
vii
viii
Table of Contents
Table of Contents
Chapter 1 Introduction
1
1.1 What Is SWMM? ...................................................................................... 1
1.2 Modeling Capabilities ............................................................................... 2
1.3 Typical Applications Of SWMM .............................................................. 3
1.4 Installing EPA SWMM ............................................................................. 3
1.5 Steps In Using SWMM ............................................................................. 4
1.6 TIPS For Getting Started ........................................................................... 5
1.6.1 Use The Latest SWMM Engine .................................................. 5
1.7 Sources Of Help ........................................................................................ 5
1.7.1 Users’ Group Meetings ............................................................... 5
1.7.2 List Server ................................................................................... 5
1.7.3 SWMM Q&A ............................................................................. 7
1.7.4 On-Line Help .............................................................................. 7
1.7.5 Useful Practice SWMM Runs That You Can Execute ............... 8
1.8 Continuous Modeling Philosophy ............................................................. 8
1.9 Error Analysis ......................................................................................... 15
1.10 Some Useful Websites .......................................................................... 16
References ...................................................................................................... 16
Chapter 2 Background
19
2.1 Introduction ............................................................................................. 19
2.1.1 Capsule History......................................................................... 19
2.2 SWMM History ....................................................................................... 19
2.2.1 Derivatives Of SWMM ............................................................. 23
2.2.2 Serial Literature ........................................................................ 23
References ...................................................................................................... 26
Chapter 3 SWMM 5 Quick Start Tutorial (External To PCSWMM)
27
3.1 Example Study Area ............................................................................... 27
3.2 Project Setup ........................................................................................... 28
3.3 Drawing Objects...................................................................................... 30
3.4 Setting Object Properties......................................................................... 32
3.5 Running A Simulation............................................................................. 36
Setting Simulation Options ................................................................. 36
Running A Simulation ........................................................................ 37
Viewing The Status Report ................................................................. 37
Viewing Results On The Map ............................................................ 39
Viewing A Time Series Plot ............................................................... 40
Viewing A Profile Plot ....................................................................... 41
Running A Full Dynamic Wave Analysis .......................................... 42
3.6 Simulating Water Quality ....................................................................... 43
3.7 Running A Continuous Simulation ......................................................... 48
ix
Table of Contents
Chapter 4 PCSWMM Quick Start Tutorial
51
Chapter 5 Conceptual Model
53
5.1 Introduction ............................................................................................. 53
5.2 Visual Objects ......................................................................................... 54
5.2.1 Rain Gages ................................................................................ 54
5.2.2 Subcatchments .......................................................................... 54
5.2.3 Junction Noder .......................................................................... 55
5.2.4 Outfall Nodes ............................................................................ 56
5.2.5 Flow Divider Nodes .................................................................. 56
5.2.6 Storage Units............................................................................. 57
5.2.7 Conduits .................................................................................... 57
5.2.8 Pumps........................................................................................ 59
5.2.9 Flow Regulators ........................................................................ 60
5.2.10 Map Labels ............................................................................. 62
5.3 Non-Visual Objects ................................................................................. 63
5.3.1 Climatology .............................................................................. 63
5.3.2 Snow Packs ............................................................................... 64
5.3.3 Aquifers .................................................................................... 65
5.3.4 Unit Hydrographs ..................................................................... 65
5.3.5 Transects ................................................................................... 66
5.3.6 External Inflows ........................................................................ 67
5.3.7 Control Rules ............................................................................ 68
5.3.8 Pollutants .................................................................................. 69
5.3.9 Land Uses ................................................................................. 69
5.3.10 Treatment ................................................................................ 71
5.3.11 Curves ..................................................................................... 72
5.3.12 Time Series ............................................................................. 72
5.3.13 Time Patterns .......................................................................... 73
5.3.14 LID Controls ........................................................................... 73
5.4 Computational Methods .......................................................................... 75
5.4.1 Surface Runoff .......................................................................... 75
5.4.2 Infiltration ................................................................................. 76
5.4.3 Groundwater ............................................................................. 77
5.4.4 Snowmelt .................................................................................. 78
5.4.5 Flow Routing ............................................................................ 78
5.4.6 Surface Ponding ........................................................................ 87
5.4.7 Water Quality Routing .............................................................. 88
5.4.8 LID Representation ................................................................... 88
Chapter 6 Main Window
91
6.1 Overview ................................................................................................. 91
6.2Main Menu ................................................................................................ 92
File Menu ............................................................................................ 92
Edit Menu ........................................................................................... 93
View Menu ......................................................................................... 93
Project Menu ....................................................................................... 94
x
Table of Contents
6.3
6.4
6.5
6.6
6.7
6.8
6.9
Report Menu ....................................................................................... 94
Tools Menu ......................................................................................... 94
Window Menu .................................................................................... 95
Help Menu .......................................................................................... 95
Toolbars................................................................................................... 95
Standard Toolbar................................................................................. 96
Map Toolbar ....................................................................................... 97
Object Toolbar .................................................................................... 97
Status Bar ................................................................................................ 98
Auto-Length ........................................................................................ 98
Offsets ................................................................................................. 98
Flow Units........................................................................................... 98
Run Status ........................................................................................... 98
Zoom Level ......................................................................................... 98
XY Location ....................................................................................... 98
Study Area Map ...................................................................................... 99
Data Browser ......................................................................................... 100
Map Browser ......................................................................................... 100
Property Editor ...................................................................................... 103
Setting Program Preferences ................................................................. 104
General Preferences .......................................................................... 105
Number Format Preferences ............................................................. 105
Chapter 7 Property Editors
107
7.1 Aquifer Editor ....................................................................................... 107
7.2 Climatology Editor ................................................................................ 108
Temperature Page ............................................................................. 109
Evaporation Page .............................................................................. 110
Wind Speed Page .............................................................................. 111
Snowmelt Page ................................................................................. 112
Areal Depletion Page ........................................................................ 113
7.3 Control Rules Editor ............................................................................. 114
Control Rule Format ......................................................................... 114
Condition Clauses ............................................................................. 115
Action Clauses .................................................................................. 116
Modulated Controls .......................................................................... 116
PID Controllers ................................................................................. 117
7.4 Cross-Section Editor ............................................................................. 118
7.5 Curve Editor .......................................................................................... 119
7.6 Groundwater Flow Editor ..................................................................... 120
7.7 Infiltration Editor .................................................................................. 122
Horton Infiltration Parameters .......................................................... 123
Green-Ampt Infiltration Parameters ................................................. 123
Curve Number Infiltration Parameters ............................................. 124
7.8 Inflows Editor........................................................................................ 124
Direct Inflows Page .......................................................................... 125
xi
Table of Contents
Dry Weather Inflows Page ................................................................ 126
RDII Inflow Page .............................................................................. 127
7.9 Initial Buildup Editor ............................................................................ 128
7.10 Land Use Editor .................................................................................. 129
General Page ..................................................................................... 129
Buildup Page ..................................................................................... 130
Washoff Page .................................................................................... 131
7.11 Land Use Assignment Editor .............................................................. 133
7.12 LID Control Editor .............................................................................. 133
Surface Layer Page ........................................................................... 134
Soil Layer Page ................................................................................. 136
Storage Layer Page ........................................................................... 137
Underdrain Page ............................................................................... 138
7.13 LID Group Editor ................................................................................ 138
7.14 LID Usage Editor ................................................................................ 139
7.15 Pollutant Editor ................................................................................... 141
7.16 Snow Pack Editor ................................................................................ 142
Snow Pack Parameters Page ............................................................. 143
Snow Removal Parameters Page ...................................................... 144
7.17 Time Pattern Editor ............................................................................. 145
7.18 Time Series Editor............................................................................... 146
7.19 Title/Notes Editor ................................................................................ 147
7.20 Transect Editor .................................................................................... 148
7.21 Treatment Editor ................................................................................. 149
7.22 Unit Hydrograph Editor ...................................................................... 150
Chapter 8 Working with Projects
153
8.1 Creating a New Project ......................................................................... 153
8.2 Opening an Existing Project.................................................................. 153
8.3 Saving a Project..................................................................................... 154
8.4 Setting Project Defaults......................................................................... 154
Default ID Labels.............................................................................. 154
Default Subcatchment Properties ...................................................... 155
Default Node/Link Properties ........................................................... 155
8.5 Measurement Units ............................................................................... 156
8.6 Link Offset Conventions ....................................................................... 156
8.7 Calibration Data .................................................................................... 157
Calibration Files ................................................................................ 157
Registering Calibration Data ............................................................ 157
8.8 Viewing all Project Data ....................................................................... 158
Chapter 9 Working with Objects
159
9.1 Types of Objects ................................................................................... 159
9.2 Adding Objects...................................................................................... 159
Adding a Rain Gage .......................................................................... 160
Adding a Node .................................................................................. 160
Adding a Link ................................................................................... 161
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Table of Contents
Adding a Map Label ......................................................................... 161
Adding a Non-visual Object ............................................................. 161
9.3 Selecting and Moving Objects .............................................................. 162
9.4 Editing Objects ...................................................................................... 162
9.5 Converting an Object ............................................................................ 163
9.6 Copying and Pasting Objects ................................................................ 164
9.7 Shaping and Reversing Links................................................................ 164
9.8 Shaping a Subcatchment ....................................................................... 165
9.9 Deleting an Object................................................................................. 165
9.10 Editing or Deleting a Group of Objects .............................................. 165
Chapter 10 Working with the Map
167
10.1 Selecting a Map Theme ....................................................................... 167
10.2 Setting the Map’s Dimensions ............................................................ 167
10.3 Utilizing a Backdrop Image ................................................................ 168
Backdrop Image File ......................................................................... 169
World Coordinates File ..................................................................... 170
Scale Map to Backdrop Image .......................................................... 170
10.4 Measuring Distances ........................................................................... 172
10.5 Zooming the Map ................................................................................ 172
10.6 Panning the Map ................................................................................. 172
10.7 Viewing at Full Extent ........................................................................ 173
10.8 Finding an Object ................................................................................ 173
10.9 Submitting a Map Query ..................................................................... 174
10.10 Using the Map Legends .................................................................... 175
10.11 Using the Overview Map .................................................................. 176
10.12 Setting Map Display Options ............................................................ 176
Subcatchment Options ...................................................................... 177
Node Options .................................................................................... 178
Link Options ..................................................................................... 178
Label Options .................................................................................... 178
Annotation Options ........................................................................... 178
Symbol Options ................................................................................ 179
Flow Arrow Options ......................................................................... 179
Background Options ......................................................................... 179
10.13 Exporting the Map ............................................................................. 180
Chapter 11 Running a Simulation
181
11.1 Setting Simulation Options ................................................................. 181
General Options ................................................................................ 182
Date Options ..................................................................................... 183
Time Step Options ............................................................................ 184
Dynamic Wave Options .................................................................... 184
File Options....................................................................................... 186
11.2 Setting Reporting Options ................................................................... 187
11.3 Starting a Simulation ........................................................................... 188
11.4 Troubleshooting Results...................................................................... 189
xiii
Table of Contents
Unknown ID Error Message ............................................................. 189
File Errors ......................................................................................... 189
Drainage System Layout Errors ........................................................ 189
Excessive Continuity Errors ............................................................. 190
Unstable Flow Routing Results ........................................................ 190
Chapter 12 Viewing Results
193
12.1 Viewing a Status Report...................................................................... 193
12.2 Variables that can be Viewed .............................................................. 196
12.3 Viewing Results on the Map ............................................................... 196
12.4 Viewing Results with a Graph ............................................................ 197
Time Series Plots .............................................................................. 198
Profile Plots....................................................................................... 200
Scatter Plots ...................................................................................... 201
12.5 Customizing a Graph’s Appearance .................................................... 202
Graph Options Dialog ....................................................................... 202
Graph Options - General ................................................................... 203
Graph Options - Axes ....................................................................... 203
Graph Options - Legend ................................................................... 203
Graph Options - Series ...................................................................... 204
Profile Plot Options Dialog............................................................... 204
12.6 Viewing Results with a Table ............................................................. 205
12.7 Viewing a Statistics Report ................................................................. 207
Object Category ................................................................................ 208
Object Name ..................................................................................... 208
Variable Analyzed ............................................................................ 209
Event Time Period ............................................................................ 209
Statistic.............................................................................................. 209
Event Thresholds .............................................................................. 209
Chapter 13 Printing and Copying
211
13.1 Selecting a Printer ............................................................................... 211
13.2 Setting the Page Format ...................................................................... 212
13.3 Print Preview ....................................................................................... 212
13.4 Printing the Current View ................................................................... 213
13.5 Copying to the Clipboard or to a File.................................................. 213
Chapter 14 Files used by SWMM
215
14.1 Project Files ......................................................................................... 215
14.2 Report and Output Files ...................................................................... 215
14.3 Rainfall Files ....................................................................................... 216
14.4 Climate Files ....................................................................................... 217
14.5 Calibration Files .................................................................................. 217
14.6 Time Series Files ................................................................................. 218
14.7 Interface Files ...................................................................................... 219
Rainfall and Runoff Files .................................................................. 220
Hot Start Files ................................................................................... 220
xiv
Table of Contents
RDII Files ......................................................................................... 221
Routing Files ..................................................................................... 221
RDII / Routing File Format .............................................................. 222
Chapter 15 Using Add-In Tools
225
15.1 What are Add-In Tools? ...................................................................... 225
15.2 Configuring Add-In Tools................................................................... 226
Chapter 16 Visual Object Properties
229
16.1 Rain Gage Properties........................................................................... 229
16.2 Subcatchment Properties ..................................................................... 230
16.3 Junction Properties .............................................................................. 231
16.4 Outfall Properties ................................................................................ 231
16.5 Flow Divider Properties ...................................................................... 232
16.6 Storage Unit Properties ....................................................................... 233
16.7 Conduit Properties ............................................................................... 234
16.8 Pump Properties .................................................................................. 235
16.9 Orifice Properties ................................................................................ 235
16.10 Weir Properties.................................................................................. 235
16.11 Outlet Properties................................................................................ 236
16.12 Map Label Properties ........................................................................ 237
Chapter 17 Command Line SWMM
239
17.1 General Instructions ............................................................................ 239
17.2 Input File Format................................................................................. 239
17.3 Map Data Section ................................................................................ 273
Chapter 18 Error Messages
277
Chapter 19 Dynamic Wave Routing Quality Assurance
287
19.1 Introduction ......................................................................................... 287
19.2 Testing Procedure................................................................................ 288
19.3 SWMM 4 Routing Models .................................................................. 290
19.4 Extran Manual Test Cases ................................................................... 293
Example EXTRAN1 ......................................................................... 293
Example EXTRAN2 ......................................................................... 297
Example EXTRAN3 ......................................................................... 299
Example EXTRAN4 ......................................................................... 303
Example EXTRAN5 ......................................................................... 306
Example EXTRAN6 ......................................................................... 310
ExampleEXTRAN7 .......................................................................... 313
Example EXTRAN8 ......................................................................... 317
Example EXTRAN9 ......................................................................... 322
Example EXTRAN10 ....................................................................... 324
19.5 Challenge Test Cases .......................................................................... 329
Example TEST1 ................................................................................ 329
Example TEST2 ................................................................................ 334
Example TEST3 ................................................................................ 338
xv
Table of Contents
Example TEST4 ................................................................................ 343
Example TEST5 ................................................................................ 349
19.6 User-Supplied Test Cases ................................................................... 355
Example USER1 ............................................................................... 355
Example USER2 ............................................................................... 362
Example USER3 ............................................................................... 370
Example USER4 ............................................................................... 381
Example USER5 ............................................................................... 388
19.7 Summary and Conclusions .................................................................. 403
References .................................................................................................... 404
Chapter 20 Land surface phase: theoretical basis from earlier
documentation for SWMM 4 RUNOFF
405
20.1 Introduction ......................................................................................... 405
20.1.1 Basic Sources of Data ........................................................... 406
20.1.2 General Control Data ............................................................ 407
20.2 Rainfall ................................................................................................ 408
20.2.1 Choice of Rainfall Data ........................................................ 408
20.2.2 Modeling Objectives ............................................................. 409
20.2.3 Design Events ....................................................................... 409
20.2.4 Design Event Alternatives .................................................... 411
20.2.5 Precipitation Data ................................................................. 412
20.2.6 Atmospheric Environment Service Data .............................. 412
20.2.7 Temporal Rainfall Variations ............................................... 412
20.2.8 Spatial Rainfall Variations .................................................... 412
20.3 Snowmelt............................................................................................. 413
20.3.1 Introduction ........................................................................... 413
20.3.2 Snow and Temperature Generation ...................................... 415
20.3.3 Subcatchment Schematization .............................................. 420
20.3.4 Melt Calculations .................................................................. 424
20.3.5 Areal Extent of Snow Cover ................................................. 435
20.3.6 Snowmelt Quality ................................................................. 441
20.3.7 Data Requirements ................................................................ 443
20.4 Evaporation ......................................................................................... 450
20.4.1 Evaporation Data .................................................................. 450
20.5 Infiltration ........................................................................................... 451
20.5.1 Introduction ........................................................................... 451
20.5.2 Integrated Horton's Equation ................................................ 451
20.5.3 Green-Ampt Equation ........................................................... 460
20.5.4 Green-Ampt Infiltration Input Data ...................................... 464
20.5.5 Rainfall Dependent Infiltration-Inflow (RDII or I/I) ............ 466
20.6 Routing ................................................................................................ 470
20.6.1 Introduction ........................................................................... 470
20.6.2 Surface Quantity Data ........................................................... 476
20.6.3 Subcatchment Surface Data .................................................. 478
20.7 Groundwater ........................................................................................ 488
xvi
Table of Contents
20.7.1 Introduction ........................................................................... 488
20.7.2 Theory ................................................................................... 489
20.7.3 Limitations ............................................................................ 504
20.7.4 Computation sequence .......................................................... 504
20.7.5 Examples ............................................................................... 506
20.7.6 Conclusions ........................................................................... 507
20.7.7 Subsurface Flow Routing...................................................... 507
20.8 Water Quality ...................................................................................... 510
20.8.1 Introduction ........................................................................... 510
20.8.2 Buildup.................................................................................. 514
20.8.3 Washoff ................................................................................. 526
20.8.4 Street Cleaning ...................................................................... 527
20.8.5 Catchbasins ........................................................................... 532
20.8.6 Constituent Fractions ............................................................ 536
20.8.7 Precipitation Contributions ................................................... 537
20.8.8 Urban Erosion ....................................................................... 540
20.8.9 Subcatchment Quality Data .................................................. 540
20.8.10 Integrated Form of Complete Mixing Quality Routing ...... 540
References .................................................................................................... 542
Chapter 21 Introduction to Background Theory of
SWMM Transport
553
21.1 Introduction ......................................................................................... 553
21.1.1 Transport phase description .................................................. 553
21.1.2 Broad Description of Flow Routing...................................... 554
21.1.3 Broad Description of Quality Routing .................................. 554
21.2 Required Transport Phase Input Data ................................................. 554
21.2.1 Organization of Data Input ................................................... 554
21.2.2 Additional Hydraulic Data .................................................... 554
21.2.3 Physical Representation of the Drainage System ................. 557
21.2.4 Computational Controls ......................................................... 562
21.3 Quality ................................................................................................. 563
21.3.1 Constituents .......................................................................... 563
21.3.2 Decay .................................................................................... 564
21.3.3 Routing.................................................................................. 564
21.4 Drain Infiltration Model ...................................................................... 564
21.4.1 Description ............................................................................ 564
21.4.2 Dry Weather Drain Infiltration (DINFIL) ............................ 566
21.4.3 Residual Melting Ice and Frost Drain Infiltration (SINFIL) 566
21.4.4 Antecedent Precipitation (RINFIL) ...................................... 567
21.4.5 High Groundwater Table (GINFIL) ..................................... 568
21.4.6 Apportionment of Drain Infiltration ..................................... 568
21.4.7 Quality of Drain Infiltration .................................................. 569
21.4.8 Data Needs ............................................................................ 569
21.4.9 Summary of Drain Infiltration Procedures ........................... 570
21.5 Dry Weather Sanitary Sewage Flow Model (DWF) ........................... 570
xvii
Table of Contents
21.5.1 Methodology ......................................................................... 570
21.5.2 Quantity Estimates ................................................................ 571
21.5.3 Quality Estimates used in original SWMM .......................... 572
21.5.4 Summary of Dry Weather Flow Requirements in original
SWMM ........................................................................................ 575
21.6 Initialization ........................................................................................ 576
21.7 Inflows and Junctions .......................................................................... 577
21.8 Miscellaneous Transport Routine Tables ............................................ 577
21.9 Introduction To Dynamic Wave Routing ............................................ 585
21.10 Formulation of the Original Dynamic Wave Routine ....................... 585
21.10.1 General ................................................................................ 585
21.10.2 Conceptual representation of the transport system ............. 586
21.11 Unsteady Flow Equations ................................................................. 587
21.11.1 Derivation ........................................................................... 587
21.11.2 Basic Flow Equations ......................................................... 589
21.11.3 Solution of Flow Equation by Modified Euler Method ...... 591
21.11.4 Numerical Stability ............................................................. 592
21.11.5 Special Pipe Flow Considerations ...................................... 594
21.11.6 Head Computation during Surcharge and Flooding ........... 596
21.11.7 Flow Control Devices ......................................................... 599
21.11.8 Initial Conditions ................................................................ 606
21.11.9 Numerical Procedure .......................................................... 606
21.11.10 Additional Dynamic Wave Routine Solutions.................. 607
21.12 Instructions For Data Preparation ..................................................... 615
21.12.1 Introduction and Schematization ........................................ 615
21.12.2 Conduit and Junction Data .................................................. 618
21.12.3 Diversion Structures ........................................................... 621
21.12.4 Boundary Conditions and Hydrograph Inputs .................... 625
21.13 Tips For Trouble-Shooting ................................................................ 626
21.13.1 Introduction ......................................................................... 626
21.13.2 Stability ............................................................................... 626
21.13.3 Surcharge ............................................................................ 627
21.13.4 Simulation Length............................................................... 628
21.13.5 Conduit Length ................................................................... 628
21.13.6 Preliminary System Check.................................................. 628
21.14 General background to certain aspects of the original storage routines in
SWMM ................................................................................................ 629
21.14.1 Description ........................................................................... 629
21.14.2 Objectives ........................................................................... 629
21.15 Simulation Techniques ...................................................................... 629
21.15.1 Introduction ......................................................................... 629
21.15.2 Flow Routing ...................................................................... 629
21.15.3 Pollutant Routing ................................................................ 633
21.15.4 Pollutant Characterization ................................................... 635
References .................................................................................................... 635
xviii
Table of Contents
Chapter 22 Examples of SWMM 5 Applications
639
22.1 Example 1: Post-Development Runoff ............................................... 640
22.1.1 Problem Statement ................................................................ 640
22.1.2 System Representation .......................................................... 642
22.1.3 Model Setup – Undeveloped Site ......................................... 645
22.1.4 Model Results – Undeveloped Site ....................................... 649
22.1.5 Model Setup – Developed Site ............................................. 651
22.1.6 Model Results – Developed Site ........................................... 657
22.1.7 Summary ............................................................................... 658
22.2 Example 2: Surface Drainage Hydraulics ........................................... 659
22.2.1 Problem Statement ................................................................ 659
22.2.2 System Representation .......................................................... 660
22.2.3 Model Setup .......................................................................... 663
22.2.4 Model Results ....................................................................... 668
22.2.5 Summary ............................................................................... 672
22.3 Example 3: Detention Pond Design .................................................... 673
22.3.1 Problem Statement ................................................................ 673
22.3.2 System Representation .......................................................... 676
22.3.3 Model Setup .......................................................................... 678
22.3.4 Model Results ....................................................................... 690
22.3.5 Summary ............................................................................... 693
22.4 Example 4: Low Impact Development ............................................... 694
22.4.1 Problem Statement ................................................................ 694
22.4.2 System Representation .......................................................... 695
22.4.3 Model Setup – Filter Strips ................................................... 696
22.4.4 Model Setup – Infiltration Trenches ..................................... 701
22.4.5 Model Results ....................................................................... 703
22.4.6 Summary ............................................................................... 706
22.5 Example 5: Runoff Water Quality ...................................................... 707
22.5.1 Problem Statement ................................................................ 707
22.5.2 System Representation .......................................................... 709
22.5.3 Model Setup .......................................................................... 711
22.5.4 Model Results ....................................................................... 717
22.5.5 Summary ............................................................................... 724
22.6 Example 6: Runoff Treatment ............................................................. 724
22.6.1 Problem Statement ................................................................ 725
22.6.2 System Representation .......................................................... 727
22.6.3 Model Setup .......................................................................... 728
22.6.4 Model Results ....................................................................... 731
22.6.5 Summary ............................................................................... 736
22.7 Example 7: Dual Drainage Systems .................................................... 737
22.7.1 Problem Statement ................................................................ 738
22.7.2 System Representation .......................................................... 739
22.7.3 Model Setup .......................................................................... 742
22.7.4 Model Results ....................................................................... 748
22.7.5 Summary ............................................................................... 752
xix
Table of Contents
22.8 Example 8: Combined Sewer Systems ............................................... 753
22.8.1 Problem Statement ................................................................ 753
22.8.2 System Representation .......................................................... 754
22.8.3 Model Setup .......................................................................... 759
22.8.4 Model Results ....................................................................... 769
22.8.5 Summary ............................................................................... 775
22.9 Example 9: Continuous Simulation .................................................... 775
22.9.1 Problem Statement ................................................................ 776
22.9.2 System Representation .......................................................... 777
22.9.3 Model Setup .......................................................................... 780
22.9.4 Model Results ....................................................................... 783
22.9.5 Summary ............................................................................... 796
References .................................................................................................... 797
Chapter 23 Bibliography for the SWMM 4 Manual
799
Chapter 24 Useful Tables
815
24.1 SWMM 5 Units of Measurement ........................................................ 815
24.2 Soil Characteristics.............................................................................. 816
24.3 NRCS Hydrologic Soil Group Definitions ......................................... 816
24.4 SCS Curve Numbers1 .......................................................................... 817
24.5 Depression Storage.............................................................................. 818
24.6 Manning’s n – Overland Flow ............................................................ 818
24.7 Manning’s n – Closed Conduits .......................................................... 819
24.8 Manning’s n – Open Channels ............................................................ 819
24.9 Water Quality Characteristics of Urban Runoff .................................. 820
24.10 Culvert Code Numbers ...................................................................... 821
24.11 Culvert Entrance Loss Coefficients .................................................. 822
Chapter 25 Glossary
823
Sources ......................................................................................................... 870
Index 871
xx
Lists of Tables and Figures
Lists of Tables and Figures
Tables
Table 1.1
Table 1.2
Table 2.0
Table 2.1
Table 2.3
Short list of some simple response OFs.
Dominant processes and their potentially relevant objective functions.
Important dates in the history of SWMM.
ASCE sanctioned conferences.
USEPA sanctioned stormwater and urban water systems modeling
conferences and stormwater and water quality management
modelling conferences.
Table 5-1 Available cross section shapes for conduits.
Table 5-2 Available types of weirs.
Table 5-3 Fluxes shown in Figure 5-7.
Table 5-4 Layers used to model different types of LID units.
Table 15-1 Macros used as command line parameters for external tools.
Table 17-1 Geometric parameters of conduit cross sections.
Table 17-2 Available pollutant buildup functions.
Table 17-3 Pollutant wash off functions.
Table 19-1 Computational Settings Used for the Test Case Comparisons.
Table 19-2 Cross-Sectional Shapes Used in Example EXTRAN8.
Table 19-3 Operating Ranges for the Pumps of Example EXTRAN10
Table 19-4 Pumping Rates for Example EXTRAN10 at Elapsed
Time of 40 Minutes
Table 19-5 System-Wide Runoff Results for Example USER1.
Table 19-6 System-Wide Runoff Results for Example USER2
Table 19-7 System-Wide Water Balances for Runoff in Example USER3.
Table 19-8 System-Wide Water Balances for Flow Routing in Example USER3.
Table 19-9 System-Wide Water Balances for Runoff in Example USER4.
Table 19-10 System-Wide Water Balances for Runoff in Example USER5.
Table 19-11 Execution Times for the User-Supplied Test Examples.
Table 20-1 Time Zones and Standard Meridians
Table 20-2 Subcatchment Surface Classification
Table 20-3a Guidelines for Levels of Service in Snow Control
Table 20-3b Guidelines for Levels of Service in Ice Control
Table 20-4 Guidelines for Chemical Application Rates.
Table 20-5 Salting Rates Used in Ontario.
Table 20-6 Snowpack Free Water Holding Capacity
Table 20-7 Values of f∞ for Hydrologic Soil Groups
Table 20-8 Rate of Decay of Infiltration Capacity for Different Values of α
Table 20-9 Representative Values for fo.
Table 20-10 Typical Values of IMD (SMDMAX) for Various Soil Types.
Table 20-11 Typical values of Su (SUCT) for Various Soil Types.
Table 20-13 Estimates of Manning's Roughness Coefficients for Overland Flow
Table 20-14 Recent European Depression Storage Data
Table 20-15 Volumetric Moisture Content at Field Capacity and Wilting Point
Table 20-16 Fate of Runoff With and Without High Water Table Simulation
Table 20-17 Required Temporal Detail for Receiving Water Analysis.
xxi
12
13
20
24
25
58
62
77
89
228
257
264
264
289
317
325
326
357
364
374
374
382
388
404
418
420
423
423
442
442
444
458
459
460
465
466
485
486
499
507
513
Lists of Tables and Figures
Table 20-18 Measured Dust and Dirt Accumulation in Chicago.
Table 20-19 Milligrams of Pollutant Per Gram of Dust and Dirt (Parts
Per Thousand By Mass) For Four Chicago Land Uses..
Table 20-20 Buildup Equations and Units for Dust and Dirt.
Table 20-21 Buildup Equations for Constituents.
Table 20-22 Units for Input of Constituent Parameters
Table 20-23a Nationwide Data on Linear Dust and Dirt Buildup Rates
and on Pollutant Fractions
Table 20-23b
Table 20-24 Guidelines for Chemical Application Rates for Snow Control.
Table 20-26 Removal Efficiencies from Street Cleaner Path
for Various Street Cleaning Programs.*
Table 20-27. Constituent Concentrations in Catchbasins
Table 20-28 Rainfall and Runoff Concentrations For a Residential Area
Near Fort Lauderdale, Florida
Table 20-29 Representative Concentrations in Rainfall.
Table 21-1 Different conveyance types supplied with SWMM
Table 21-2 Summary of area relationships and required conveyance dimensionsa
Table 21-3 Parameters required for nodes.
Table 21-4 RINFIL equations for three study areas
Table 21-5 Average monthly degree-days for cities in the United States
Table 21-6 Guide for establishing water usage in commercial sewersheds.
Table 21-7 Guides for establishing water usage in industrial sewersheds
Table 21-8 Classes of Elements Included in the dynamic wave routine.
Table 21-9 Properties of Nodes and Links in the dynamic wave routine
Table 21-10 Values of CSUB as a function of degree of weir submergence.
Table 21-11 Geometric and hydraulic data for hypothetical reservoir.
Table 22-1 Properties of the undeveloped subcatchment
Table 22-2 Flow lengths and slopes of the undeveloped subcatchment
Table 22-3 Analysis options
Table 22-4 Summary of results for the undeveloped site
Table 22-5 Geometric properties of the subcatchments in the developed site
Table 22-6 Land use categories in the developed site
Table 22-7 Land use coverage and imperviousness for subcatchments
in the developed site
Table 22-8 Summary of results for post-development conditions
Table 22-9 Comparison of runoff for pre- and post-development conditions
Table 22-10 Invert elevations of junctions
Table 22-11 Subcatchment outlets
Table 22-12 Characteristics of the conduits used in the model
Table 22-13 Conduit properties
Table 22-14 Available culvert sizes
Table 22-15 Maximum depths and flows for conduits during the 100-yr event
Table 22-16 Comparison of runoff for post-development conditions
with and without routing
Table 22-17 Pre- and post-development peak discharges
Table 22-18 Post-development subcatchment data
Table 22-19 Design of the WQCV outlet
Table 22-20 Characteristics of the pond's outlet structure
Table 22-21 Subcatchments containing filter strips
Table 22-22 Properties of the new junctions
xxii
514
514
518
518
520
522
524
525
529
534
538
539
556
558
560
568
578
582
583
586
586
603
631
647
648
649
651
653
656
656
658
658
665
666
667
667
668
669
672
674
680
685
691
697
698
Lists of Tables and Figures
Table 22-23
Table 22-24
Table 22-25
Table 22-26
Table 22-27
Table 22-28
Table 22-29
Table 22-30
Table 22-31
Table 22-32
Table 22-33
Table 22-34
Table 22-35
Table 22-36
Table 22-37
Table 22-38
Table 22-39
Table 22-40
Table 22-41
Table 22-42
Table 22-43
Table 22-44
Table 22-45
Table 22-46
Table 22-47
Table 22-48
Table 22-49
Table 22-50
Table 22-51
Table 22-52
Table 22-53
Table 22-54
Table 22-55
Table 22-56
Table 22-57
Table 22-58
Table 22-59
Table 22-60
Table 22-61
Table 22-62
Properties of the new conduits
Properties of the subcatchments derived from S3 and S4
Widths of the filter strip subcatchments
Properties of the filter strip subcatchments
Properties of the subcatchments derived from S1 and S2
Subcatchments containing infiltration trenches
Properties of the infiltration trench subcatchments
Properties of the new junctions
Properties of the new conduits
Runoff coefficients for filter strips
Runoff coefficients for infiltration trenches
Rainfall time series for the 0.1 and 0.23 inch events
Typical dust and dirt buildup rates after Manning et al.
Parameters for TSS buildup
Curb length and land uses for each subcatchment
Washoff characteristics for each land use
Average TSS concentration for the 0.23 in. event
Storage curve for the re-designed pond
Properties of the pond’s re-designed outlet structure
Curb lengths and land uses for LID subcatchments
Detention pond TSS treatment performance summary
General drainage system criteria for Fort Collins
Cross section data for street transects
Junction invert elevations for dual drainage system
Conduit shapes and offsets for dual drainage system
Calculated gutter grades
Available drainage pipe sizes
Iterations for 2-yr storm pipe sizing
Properties of the combined sewer system nodes1
Properties of the combined sewer system conduits1
Subcatchment outlets
Properties of the regulator structures
Properties of the force main line
Pump curve data
Summary of dry weather flows
Summary of system performance for different storm events
Monthly evaporation for Fort Collins, CO
Summary statistics for various rainfall event properties
Ten most severe events based on duration, depth and intensity
Correspondence among the most severe events
xxiii
698
699
699
700
702
702
702
703
703
705
705
708
713
714
715
716
723
726
726
730
736
741
744
746
747
749
750
750
761
761
762
764
765
767
768
774
781
794
795
796
Lists of Tables and Figures
Figures
Figure 1.1 Relationship between calibration activities...................................................... 11
Figure 3-1 Example study area. ......................................................................................... 27
Figure 3-2 Default ID labeling for tutorial example. ........................................................ 28
Figure 3-3 Map Options dialog. ........................................................................................ 29
Figure 3-4 Subcatchments and nodes for example study area. ......................................... 31
Figure 3-5 Property Editor window. .................................................................................. 33
Figure 3-6 Group Editor dialog. ........................................................................................ 33
Figure 3-7 Time Series Editor dialog. ............................................................................... 35
Figure 3-8 Title/Notes Editor. ........................................................................................... 36
Figure 3-9 Simulation Options dialog. .............................................................................. 36
Figure 3-10 Portion of the Status Report for initial simulation run. ................................. 38
Figure 3-11 Example of viewing color-coded results on the Study Area Map. ................ 39
Figure 3-12 Time Series Plot dialog. ................................................................................. 40
Figure 3-13 Time Series plot of results from initial simulation run. ................................. 41
Figure 3-14 Profile Plot dialog. ......................................................................................... 42
Figure 3-15 Example of a Profile Plot. .............................................................................. 42
Figure 3-16 Dynamic Wave simulation options. ............................................................... 43
Figure 3-17 Pollutant Editor dialog. .................................................................................. 45
Figure 3-18 Land Use Editor dialog. ................................................................................. 45
Figure 3-19 Defining a TSS buildup function for Residential land use. ........................... 46
Figure 3-20 Land Use Assignment dialog. ........................................................................ 47
Figure 3-21 TSS concentration of runoff from selected subcatchments. .......................... 48
Figure 3-22 Statistics Selection dialog. ............................................................................. 49
Figure 3-23 Statistical Analysis report. ............................................................................. 50
Figure 5-1 Example of physical objects used to model a drainage system. ...................... 54
Figure 5-2 Areal Depletion curve for a natural area.......................................................... 64
Figure 5-3 An RDII unit hydrograph................................................................................. 66
Figure 5-4 Example of a natural channel transect. ............................................................ 67
Figure 5-5 Adjustment of subcatchment parameters after LID placement. ...................... 75
Figure 5-6 Conceptual view of surface runoff. ................................................................. 76
Figure 5-7 Two-zone groundwater model. ........................................................................ 77
Figure 5-8 Node-link representation of a drainage system in SWMM ............................. 82
Figure 13-1 The Margins page of the Page Setup dialog. ............................................... 211
Figure 13-2 The Headers/Footers page of the Page Setup dialog. .................................. 212
Figure 13-3 Example of the Copy dialog. ....................................................................... 213
Figure 14-1 Example of using the Combine utility to merge Routing files. ................... 222
Figure 15-1 SWMM’s Tools menu. ................................................................................ 225
Figure 15-2 The Tools Options dialog. ........................................................................... 226
Figure 15-3 The Tool Properties dialog. ......................................................................... 226
Figure 17-1 Example SWMM project file....................................................................... 241
Figure 17-1 Example SWMM project file (continued from previous page). .................. 242
Figure 17-2 Data for map shown in Figure 17-3. ............................................................ 274
Figure 17-3 Example study area map. ............................................................................. 274
Figure 19-1 Comparison of the SWMM 4 Explicit and Enhanced Explicit
Methods for the Outfall Flow in Example TEST5. ................................. 291
Figure 19-2 Comparison of the SWMM 4 Explicit and Iterative Methods and
SWMM 5 Results for Conduit 1602 of Example EXTRAN1. ................ 292
xxiv
Lists of Tables and Figures
Figure 19-3 Comparison of the SWMM 4 Explicit and Iterative Methods for
Conduit 6 of Example TEST4. ................................................................ 292
Figure 19-4 Schematic of the Drainage Network Used for Example EXTRAN1........... 293
Figure 19-5 External Inflows for Example EXTRAN1. ................................................. 294
Figure 19-6 Flow Comparison for Link 1602 of Example EXTRAN1........................... 294
Figure 19-7 Flow Comparison for Link 1030 of Example EXTRAN1........................... 295
Figure 19-8 Water Depth Comparison for Node 82309 of Example EXTRAN1. .......... 295
Figure 19-10 Comparison of Peak Flows Computed for the Conduits in Example
EXTRAN1. .............................................................................................. 296
Figure 19-9 Water Depth Comparison for Node 16009 of Example EXTRAN1. .......... 296
Figure 19-11 Comparison of Maximum Water Elevations for the Nodes of
Example EXTRAN1................................................................................ 297
Figure 19-12 Flow Comparison for Link 1030 of Example EXTRAN2......................... 297
Figure 19-13 Water Depth Comparison for Node 16009 of Example EXTRAN2. ........ 298
Figure 19-14 Comparison of Peak Flows for the Conduits of Example
EXTRAN2. .............................................................................................. 298
Figure 19-15 Comparison of Maximum Water Elevations for the Nodes of
Example EXTRAN2................................................................................ 299
Figure 19-16 Schematic of the Drainage Network Used for Example EXTRAN3......... 300
Figure 19-17 Comparison of Flow Through the Bottom Orifice of Example
EXTRAN3. .............................................................................................. 300
Figure 19-18 Comparison of Water Depth at the Inlet Node of the Orifice in
Example EXTRAN3................................................................................ 301
Figure 19-19 Flow Comparison for Link 1570 of Example EXTRAN3......................... 301
Figure 19-20 Water Depth Comparison for Node 15009 of Example EXTRAN3. ........ 302
Figure 19-21 Comparison of Peak Flows for the Conduits of Example
EXTRAN3. .............................................................................................. 302
Figure 19-22 Comparison of Maximum Water Elevations for the Nodes of
Example EXTRAN3................................................................................ 303
Figure 19-23 Comparison of Flow Through the Transverse Weir of Example
EXTRAN4. .............................................................................................. 304
Figure 19-24 Comparison of Water Depth at the Inlet Node of the Weir in
Example EXTRAN4................................................................................ 304
Figure 19-25 Comparison of Peak Flows for the Conduits of Example
EXTRAN4. .............................................................................................. 305
Figure 19-26 Comparison of Maximum Water Elevations for the Nodes of
Example EXTRAN4................................................................................ 305
Figure 19-27 Schematic of the Drainage Network Used for Example EXTRAN5......... 306
Figure 19-28 Comparison of Flow Through the Outlet Orifice of Example
EXTRAN5. .............................................................................................. 307
Figure 19-29 Comparison of Flow Through the Conduit Immediately
Downstream of the Outlet Orifice of Example EXTRAN5. ................... 307
Figure 19-30 Comparison of Water Depth at the Storage Node in Example
EXTRAN5. .............................................................................................. 308
Figure 19-31 Comparison of Water Depth at the Node Immediately Upstream of
the Storage Node in Example EXTRAN5. .............................................. 308
Figure 19-32 Comparison of Water Depth at the Node Immediately Downstream
of the Storage Node in Example EXTRAN5. ......................................... 309
Figure 19-33 Comparison of Peak Flows for the Conduits of Example
EXTRAN5. .............................................................................................. 309
xxv
Lists of Tables and Figures
Figure 19-34 Comparison of Maximum Water Elevations for the Nodes of
Example EXTRAN5................................................................................ 310
Figure 19-35 Schematic of the Drainage Network Used for Example EXTRAN6......... 311
Figure 19-36 Comparison of Flow Through the Pump of Example EXTRAN6. ........... 311
Figure 19-37 SWMM 4 Flows Leaving Node 82309 for Example EXTRAN6.............. 312
Figure 19-38 SWMM 5 Flows Leaving Node 82309 for Example EXTRAN6.............. 312
Figure 19-39 Comparison of Outfall Flows for Example EXTRAN6. ........................... 313
Figure 19-40 Schematic of the Drainage Network Used for Example EXTRAN7......... 314
Figure 19-41 Comparison of Flow Through the Pump of Example EXTRAN7. ........... 314
Figure 19-42 Comparison of Water Depth at the Inlet Node of the Pump in
Example EXTRAN7................................................................................ 315
Figure 19-43 Comparison of Water Depth at the Outlet Node of the Pump in
Example EXTRAN7................................................................................ 315
Figure 19-44 Comparison of Outfall Flows for Example EXTRAN7. ........................... 316
Figure 19-45 Comparison of Peak Flows for the Conduits of Example
EXTRAN7. .............................................................................................. 316
Figure 19-46 Comparison of Maximum Water Elevations for the Nodes of
Example EXTRAN7................................................................................ 317
Figure 19-47 Schematic of the Drainage Network Used for Example EXTRAN8......... 318
Figure 19-48 Geometry of Channels 10081 and 10082 in Example EXTRAN8. ........... 319
Figure 19-49 Flow Comparison for Link 10003 of Example EXTRAN8....................... 319
Figure 19-50 Flow Comparison for Link 10006 of Example EXTRAN8....................... 320
Figure 19-51 Flow Comparison for Outfall Link 10082 of Example EXTRAN8. ......... 320
Figure 19-52 Water Depth Comparison for Node 30006 of Example EXTRAN8. ........ 321
Figure 19-53 Comparison of Peak Flows for the Conduits of Example
EXTRAN8. .............................................................................................. 321
Figure 19-54 Comparison of Maximum Water Elevations for the Nodes of
Example EXTRAN8................................................................................ 322
Figure 19-55 Schematic of Example EXTRAN9 ............................................................ 322
Figure 19-56 Storage Unit Shape for Example EXTRAN9. ........................................... 323
Figure 19-57 Water Depth Comparison for the Storage Unit of Example
EXTRAN9. .............................................................................................. 323
Figure 19-58 Flow Comparison for the Side Orifice of Example EXTRAN9. ............... 324
Figure 19-59 Schematic of Example EXTRAN10. ......................................................... 324
Figure 19-60 Operating Curve for Pumps of Example EXTRAN 10 ............................. 325
Figure 19-61 Water Depth Comparison for the Storage Unit 401 of Example
EXTRAN10. ............................................................................................ 326
Figure 19-62 Water Depth Comparison for the Storage Unit 301 of Example
EXTRAN10. ............................................................................................ 327
Figure 19-63 Flow Comparison for Outflow Conduit 100 of Example
EXTRAN10. ............................................................................................ 327
Figure 19-64 Flow Comparison for Pump 90002 of Example EXTRAN10. .................. 328
Figure 19-65 Flow Comparison for Pump 90004 of Example EXTRAN10. .................. 328
Figure 19-66 Profile View of Example TEST1. .............................................................. 329
Figure 19-67 Flow Comparisons for Selected Conduits for Example TEST1 ................ 330
Figure 19-68 Depth Comparisons for Selected Nodes for Example TEST1................... 332
Figure 19-69 Profile View of Example TEST2. .............................................................. 334
Figure 19-70 Inflow Hydrograph for Example TEST2. .................................................. 334
Figure 19-71 Comparisons of Flow in Selected Conduits of Example TEST2 .............. 335
Figure 19-72 Water Depth Comparisons for Selected Nodes of Example TEST2 ......... 337
Figure 19-73 Profile View of Example TEST3. .............................................................. 338
xxvi
Lists of Tables and Figures
Figure 19-74
Figure 19-75
Figure 19-76
Figure 19-77
Inflow Hydrograph for Example TEST3. .................................................. 338
Comparisons of Flow in Selected Conduits of Example TEST3. ............. 339
Water Depth Comparisons for Selected Nodes of Example TEST3 ......... 341
Outfall Flow Comparison for Example TEST3 at a 30 Second Time
Step. ......................................................................................................... 343
Figure 19-78 Profile View of Example TEST4. .............................................................. 344
Figure 19-79 Inflow Hydrograph for Example TEST4. .................................................. 344
Figure 19-80 Comparisons of Flow in Selected Conduits of Example TEST4 .............. 345
Figure 19-81 Water Depth Comparisons for Selected Nodes of Example TEST4 ......... 347
Figure 19-82 Outfall Flow Comparison for Example TEST4 at a 10 Second Time
Step. ......................................................................................................... 349
Figure 19-83 Profile View of Example TEST5. .............................................................. 350
Figure 19-84 Inflow Hydrograph for Example TEST5. .................................................. 350
Figure 19-85 Comparisons of Flow in Selected Conduits of Example TEST5 .............. 351
Figure 19-86 Water Depth Comparisons for Selected Nodes of Example TEST5 ......... 353
Figure 19-87 Outfall Flow Comparison for Example TEST5 at a 10 Second Time
Step. ......................................................................................................... 354
Figure 19-88 Schematic of the Drainage Network for Example USER1. ....................... 355
Figure 19-90 Rainfall Hyetograph for the Design Storm Used for Example USER....... 356
Figure 19-91 Comparison of Peak Flows for All Conduits in Example USER1 ............ 357
Figure 19-92 Comparison of Flows at Select Locations for Example USER1. .............. 358
Figure 19-93 Comparison of Water Depths at Select Locations for Example
USER1 ..................................................................................................... 360
Figure 19-94 Schematic of the Drainage Network for Example USER2. ....................... 362
Figure 19-95 Configuration of Surface Storage Units with Road Overflows Used
Throughout Example USER2.................................................................. 363
Figure 19-96 Rainfall Hyetograph for the Design Storm Used for Example
USER2. .................................................................................................... 363
Figure 19-97 Comparison of Peak Flows for the Conduits in Example USER2. ........... 364
Figure 19-98 Flow Comparisons for Example USER2 at Selected Locations ................ 365
Figure 19-99 Depth Comparisons for Selected Nodes in Example USER2 ................... 367
Figure 19-100 Comparison of Surface Storage – Road Overflow Arrangement at
Location TW01240.................................................................................. 369
Figure 19-101 Schematic of the Drainage Network for Example USER3 ...................... 371
Figure 19-102 Detailed Schematics of the Outfalls for Example USER3. ..................... 372
Figure 19-103 Profile View of a Typical Manhole Structure in Example USER3 ......... 372
Figure 19-104 Rainfall Hyetograph for the Design Storm Used for Example
USER3. .................................................................................................... 373
Figure 19-105 Comparison of Peak Flows for the Conduits in Example USER3. ......... 374
Figure 19-106 Comparisons of Flows at Outfalls SAUBOUT, CAUBOUT, AND
SRUBOUT for Example USER3 ............................................................ 375
Figure 19-107 Comparisons of Flows at Outfalls SCANOUT, CMRYOUT, and
CCOROUT for Example USER3. ........................................................... 376
Figure 19-108 Comparison of Flows Along a Main Trunk Line of Example
USER3 ..................................................................................................... 377
Figure 19-109 Flow in Conduit SXANELG in the Original Model for Example
USER3. .................................................................................................... 379
Figure 19-110 Flow in Conduit SXANELG After Converting Storage Nodes to
Junctions Along its Trunk Line ............................................................... 379
Figure 19-111 Flow Comparisons for Selected Conduits of Example USER3 for a
5 Second Routing Time Step ................................................................... 380
xxvii
Lists of Tables and Figures
Figure 19-112
Figure 19-113
Figure 19-114
Figure 19-115
Figure 19-116
Figure 19-117
Schematic of the Drainage System for Example USER4 ........................ 381
Rainfall Hyetograph for Example USER4. ............................................. 382
Elevation Profiles of Trunk Lines A and B for Example USER4 ........... 383
Comparison of Peak Flows for the Conduits in Example USER4 .......... 384
Comparison of Flows in Selected Conduits for Example USER4 .......... 384
Comparison of Water Depths at the Upstream Nodes of Selected
Conduits for Example USER4 ................................................................ 386
Figure 19-118 Drainage System Schematic for Example USER5. ................................. 388
Figure 19-119 Design Storm Hyetograph Used in Example USER5.............................. 389
Figure 19-120 External Lateral Inflows for Example USER5. ....................................... 389
Figure 19-121 Comparison of Peak Flows Produced by SWMM 4 and 5 for
Example USER5 ..................................................................................... 390
Figure 19-122 Comparison of Flows in Conduit 746_modify for Example USER5 ...... 390
Figure 19-123 Comparison of Flows in Selected Conduits for Example USER5 .......... 391
Figure 19-124 Comparison of Flows in Selected Conduits for Example USER5 .......... 393
Figure 19-125 Comparison of Water Depths at the Upstream Nodes of Selected
Conduits for Example USER5 ................................................................ 395
Figure 19-126 Comparison of Water Depths at the Upstream Nodes of Selected
Conduits for Example USER5 ................................................................ 397
Figure 19-127 Schematic of Detail A Portion of Example USER5. ............................... 399
Figure 19-128 Elevation Profile of the Channels in the Detail A Portion of
Example USER5. .................................................................................... 400
Figure 19-129 Inflow to the Channel of Detail A for Example USER5. ........................ 400
Figure 19-130 Flow in the First Section of the Channel of Detail A for Example
USER5 ..................................................................................................... 401
Figure 19-131 Flow in the Third Section of the Channel of Detail A for Example
USER5. .................................................................................................... 401
Figure 19-132 Flow in the Third Section of the Channel of Detail A for Example
USER5 with Inertial Terms Ignored in SWMM 5. ................................. 402
Figure 19-133 Flow Computed at the Outfall of Example USER5 Using a 5
Second Routing Time Step ...................................................................... 403
Figure 20-1 Sinusoidal Interpolation of Hourly Temperatures ....................................... 416
Figure 20-2 Typical Gage Catch Deficiency Correction. ................................................ 419
Figure 20-3 Subcatchment Schematization With and Without Snowmelt
Simulation ............................................................................................... 421
Figure 20-4 Redistribution of Snow ................................................................................ 422
Figure 20-5 Seasonal Variation of Melt Coefficients...................................................... 428
Figure 20-6 Typical Areal Depletion Curve for Natural Area and Temporary
Curve for New Snow ............................................................................... 436
Figure 20-7 Effect of Snow Cover on Areal Depletion Curves. ..................................... 437
Figure 20-8 Schematic of Liquid Water Routing Through Snow Pack .......................... 440
Figure 20-9 Degree-day Equations for Snow Melt. ........................................................ 448
Figure 20-10 Freezing Point Depression Versus Roadway Salting Chemical
Concentration. Compiled from data from CRC. ..................................... 449
Figure 20-11 Horton Infiltration Curve and Typical Hyetograph. For the case
illustrated, runoff would be intermittent.................................................. 452
Figure 20-12 Cumulative Infiltration, F, is the Integral of f, i.e. the Area Under
the Curve. ................................................................................................ 453
Figure 20-13 Regeneration (Recovery) of Infiltration Capacity During Dry Time
Steps. ....................................................................................................... 455
xxviii
Lists of Tables and Figures
Figure 20-14 Subcatchment Schematization for Overland Flow Calculations.
Flow from each subarea is directly to an inlet (node) or gutter/pipe
(link). Flow from one subarea is not routed over another. ...................... 471
Figure 20-15 Non-linear Reservoir Model of Subcatchment. ......................................... 472
Figure 20-16 Richardson Extrapolation as used in the RUNOFF Block. ....................... 476
Figure 20-19 Different Subcatchment Shapes to Illustrate Effect of Subcatchment
Width. ...................................................................................................... 480
Figure 20-20 Subcatchment Hydrographs for Different Shapes of Figure 20-19. .......... 481
Figure 20-21 Percent Imperviousness vs Developed Population Density for Large
Urban Areas.. ........................................................................................... 484
Figure 20-22 Depression Storage vs. Catchment Slope. ................................................. 487
Figure 20-23 GROUND Parameters ............................................................................... 490
Figure 20-24 Tension, PSI and hydraulic conductivity, K versus moisture content. ...... 495
Figure 20-25 Tension, PSI and hydraulic conductivity, K versus moisture content. ...... 495
Figure 20-26 Tension, PSI and hydraulic conductivity, K versus moisture
content.. ................................................................................................... 496
Figure 20-27 Model Representation and Measured Hydraulic Conductivity
Curves for Three Types of Soil. .............................................................. 498
Figure 20-28 Kinds of Water in Soil. Note: Silt Loam Contains more than Twice
as Much Readily Available Water than Sandy Load. ............................. 499
Figure 20-29 Hydrograph of total flow and its two major components. ......................... 501
Figure 20-30 Definition sketch for Dupuit-Forcheimer approximation for drainage
to adjacent channel. ................................................................................. 502
Figure 20-31 Definition sketch for Hooghoudt’s Method for flow to circular
drains. ...................................................................................................... 503
Figure 20-32 Flowchart of Subsurface and Directly-connected Surface
Calculations. ............................................................................................ 505
Figure 20-33 Non-linear buildup of street solids. ........................................................... 516
Figure 20-34 Buildup of street solids in San Jose. .......................................................... 517
Figure 20-35 Comparison of linear and three non-linear buildup equations. Dust
and dirt, DD is used as an example. Numerical values have been
chosen arbitrarily. .................................................................................... 518
Figure 20-36 Hypothetical time sequence of linear buildup and street sweeping. .......... 531
Figure 20-37 Representative catchbasin designs. ............................................................ 532
Figure 20-38 Catchbasin flushing characteristics. Data are from APWA....................... 535
Figure 21-1 Intersection of the straight line and the normalized flow-area curve as
determined in SWMM. ............................................................................ 555
Figure 21-2 Selected sewer cross-sections. ..................................................................... 557
Figure 21-3 Cunnette section........................................................................................... 561
Figure 21-4 Components of drain infiltration. ................................................................ 565
Figure 21-5 Prescribed melting period. ........................................................................... 567
Figure 21-6 Representative daily flow variation. ............................................................ 571
Figure 21-7 Representative hourly flow variation........................................................... 572
Figure 21-8 Conceptual representation of the The dynamic wave routine model........... 587
Figure 21-9 Modified Euler method for discharge based on half-step, full-step
projection. ................................................................................................ 591
Figure 21-10 Special hydraulic cases in the dynamic wave routine flow
calculations. ............................................................................................. 595
Figure 21-11 Conceptual representation of a storage junction. ....................................... 599
Figure 21-12 Typical orifice diversions. ......................................................................... 600
Figure 21-13 Representation of weir diversions. ............................................................ 602
xxix
Lists of Tables and Figures
Figure 21-14 Schematic presentation of pump diversion. ............................................... 604
Figure 21-15 Definition sketch of an irregular cross-section. ......................................... 619
Figure 21-16 Definition sketch of a variable area storage junction. ............................... 621
Figure 21-17 Definition sketch of weir input data. ......................................................... 622
Figure 21-18 Definition sketch of pump input data. ....................................................... 623
Figure 21-19 Schematic presentation of pump diversion. ............................................... 624
Figure 21-20 Typical pump operating curve. .................................................................. 624
Figure 21-21 Well-mixed, variable-volume reservoir. .................................................... 633
Figure 22-1 Undeveloped site ......................................................................................... 641
Figure 22-2 Developed site ............................................................................................. 641
Figure 22-3 Idealized representation of a subcatchment ................................................. 642
Figure 22-4 SWMM representation of the undeveloped study area................................ 645
Figure 22-5 Computation of width of the undeveloped subcatchment ........................... 648
Figure 22-6 Design storm hyetographs ............................................................................ 649
Figure 22-7 Runoff hydrographs (flow Q versus time) for the undeveloped site ........... 651
Figure 22-8 Discretization of the developed site into subcatchments ............................. 652
Figure 22-9 Definition of overland flow length and slope for subcatchment S2 ............ 655
Figure 22-10 Width and slope computation for subcatchments S3 (a) and S4 (b).......... 655
Figure 22-11 Runoff hydrographs (flow Q versus time) for the developed site ............. 657
Figure 22-12 Pre-development site ................................................................................. 660
Figure 22-13 Post-development site without conveyance system ................................... 662
Figure 22-14 Links and Nodes ........................................................................................ 662
Figure 22-15 Post-development site with runoff conveyance added .............................. 664
Figure 22-16 SWMM representation of the post-development conveyance system ....... 665
Figure 22-17 Post-development outflow hydrographs for 2-yr storm ............................. 670
Figure 22-18 Post-development outflow hydrographs for 10-yr storm ........................... 671
Figure 22-19 Post-development outflow hydrographs for 100-yr storm ......................... 671
Figure 22-20 Detention pond location for the post-development site. ............................ 674
Figure 22-21 Schematic representation of a detention pond ........................................... 679
Figure 22-22 Water quality capture volume .................................................................... 680
Figure 22-23 Average depth of runoff producing storms in the US................................ 682
Figure 22-24 Geometry of the pond's WQCV ................................................................. 682
Figure 22-25 Study area map with storage unit SU1 ...................................................... 684
Figure 22-26 Properties of storage unit SU1 ................................................................... 684
Figure 22-27 WQCV drainage times for the iterations shown in Table 22-19 ............... 686
Figure 22-28 Final design of the detention pond and outlet structure ............................. 690
Figure 22-29 Detail of the pond outlet structure ............................................................. 691
Figure 22-30 Outlet hydrographs for the 2-yr storm ....................................................... 692
Figure 22-31 Outlet hydrographs for the 10-yr storm ..................................................... 692
Figure 22-32 Outlet hydrographs for the 100-yr storm ................................................... 693
Figure 22-33 Post-development site with LIDs in place ................................................. 694
Figure 22-34 Schematic representation of a filter strip ................................................... 695
Figure 22-35 Schematic representation of an infiltration trench ..................................... 696
Figure 22-36 Re-discretization of subcatchments S3 and S4 .......................................... 698
Figure 22-37 Representation of subcatchments S_FS_1, S3.1, and S3.2........................ 699
Figure 22-38 Representation of subcatchments S_FS_3, S_FS_4, S4.1, S4.2,
and S4.3 ................................................................................................... 700
Figure 22-39 Re-discretization of subcatchments S1 and S2 for infiltration
trenches .................................................................................................... 701
Figure 22-40 Influent and effluent hydrographs for filter strip S_FS_1 ......................... 704
Figure 22-41 Influent and effluent hydrographs for infiltration trench S_IT_1 .............. 704
xxx
Lists of Tables and Figures
Figure 22-42 Comparison of outlet discharges with and without LID controls .............. 705
Figure 22-43 Percent reduction in outlet peak flows and runoff volumes with
LIDs ......................................................................................................... 706
Figure 22-44 Post-development site with no runoff controls .......................................... 708
Figure 22-45 TSS buildup curve ..................................................................................... 714
Figure 22-46 TSS concentrations for the 0.1 in. storm with EMC washoff .................... 718
Figure 22-47 TSS concentrations for the 0.23 in. storm with EMC washoff .................. 719
Figure 22-48 TSS concentration at site outlet with EMC washoff ................................. 720
Figure 22-49 Runoff flow and TSS load at site outlet for the 0.1 in. storm with
EMC washoff .......................................................................................... 720
Figure 22-50 TSS concentrations for the 0.1 in. storm with Exponential washoff ......... 721
Figure 22-51 TSS concentrations for the 0.23 storm with Exponential washoff ............ 722
Figure 22-52 TSS concentrations for the 2-yr storm with Exponential washoff ............ 722
Figure 22-53 TSS concentration at the site outlet for Exponential washoff ................... 723
Figure 22-54 Developed site with LIDs and detention pond .......................................... 725
Figure 22-55 Schematic of the re-designed pond outlet structure ................................... 727
Figure 22-56 TSS and runoff reduction through filter strip S_FS_1 for
the 0.1 in. storm ....................................................................................... 732
Figure 22-57 TSS and runoff reduction through infiltration trench S_IT_4 for
the 2-yr storm .......................................................................................... 732
Figure 22-58 TSS concentrations in pond SU2 with and without treatment ................... 733
Figure 22-59 TSS mass load released by pond SU2 for the 0.23 in storm...................... 734
Figure 22-60 TSS concentrations in pond SU2 with and without treatment ................... 735
Figure 22-61 TSS mass load released by pond SU2 for the 0.23 in. storm..................... 735
Figure 22-62 Total TSS load discharged at site outlet under different treatment
scenarios .................................................................................................. 737
Figure 22-63 Post-development site with simple drainage system ................................. 738
Figure 22-64 Parallel pipe and gutter conveyance .......................................................... 739
Figure 22-65 Elements of streets defined in the drainage criteria ................................... 741
Figure 22-66 Three-dimensional layout of the site's dual drainage system .................... 742
Figure 22-67 Full_Street cross section; the Half_Street section is half of this
section ...................................................................................................... 744
Figure 22-68 Post-development site with dual drainage system ..................................... 747
Figure 22-69 Examples of surcharge and flooding ......................................................... 748
Figure 22-70 Flows in pipes P5 and P6 during the 100-yr storm .................................... 751
Figure 22-71 Surcharge behavior along the eastern boundary of the site ....................... 752
Figure 22-72 Combined sewer system study area ........................................................... 754
Figure 22-73 Conceptual representation of overflows in a combined system ................ 755
Figure 22-74 Transverse weir flow regulator .................................................................. 756
Figure 22-75 Alternative ways to represent tranverse weir flow regulators in
SWMM .................................................................................................... 758
Figure 22-76 (a) Pump Property Editor and (b) Pump Curve Editor .............................. 758
Figure 22-77 Schematic representation of the combined sewer system .......................... 759
Figure 22-78 Layout of the combined sewer system before adding regulators and
pump ........................................................................................................ 762
Figure 22-79 Force main line .......................................................................................... 765
Figure 22-80 Final combined sewer system model layout .............................................. 768
Figure 22-81 Flow (Q) along sections of the stream for the 0.23 in. storm .................... 769
Figure 22-82 Flow (Q) along sections of the interceptor for the 0.23 in. storm ............. 770
Figure 22-83 Flow (Q) diverted from each regulator to the interceptor for the 0.23
in. storm ................................................................................................... 770
xxxi
Lists of Tables and Figures
Figure 22-84
Figure 22-85
Figure 22-86
Figure 22-87
Figure 22-88
Figure 22-89
Figure 22-90
Figure 22-91
Figure 22-92
Flow (Q) along sections of the stream for the 2-yr storm .......................... 771
Flow (Q) along the sections of the interceptor for the 2-yr storm ............. 772
Flows (Q) in regulators R1 and R4 for the 2-yr storm .............................. 772
Pump behavior for the 0.23 in. storm: (a) wet well water depth, .............. 773
Drainage system and detention pond (SU1) designed in Example 3......... 776
Ten year rainfall record for Fort Collins, CO ............................................ 781
Rainfall event producing the largest flow rates to the detention pond ...... 784
Water depth in the detention pond between days 3061 and 3069 ............. 785
Inflow and outflow (Q) for the detention pond between
days 3061 and 3069 ................................................................................. 785
Figure 22-93 Losses for subcatchment S1 between days 3061 and 3069 ....................... 786
Figure 22-94 Statistics Selection dialog for analyzing peak pond outflows ................... 787
Figure 22-95 Summary statistics for peak inflow to node J_out (same as
peak pond outflow) .................................................................................. 788
Figure 22-96 Event listing of peak inflow to node J_out (same as peak pond
outflow) ................................................................................................... 789
Figure 22-97 Histogram of peak inflow to node J_out (same as peak pond
outflow) ................................................................................................... 790
Figure 22-98 Cumulative frequency of peak inflow to node J_out (same as peak
pond outflow) .......................................................................................... 790
Figure 22-99 Statistical query for daily peak water depth in the detention pond............ 791
Figure 22-100 Frequency plot of daily peak water depth in the detention pond
rainfall statistics ....................................................................................... 792
Figure 22-101 Selection of an MIT for analyzing a rainfall record ................................ 793
Figure 22-102 Frequency plots for event duration and depth ......................................... 794
xxxii
USEPA Documentation Equivalence
Lists of USEPA SWMM 4 Manual Equivalents
(Tables, Figures and Equations)
Tables
In this manual,
Table
was in the EPA SWMM 4
Manual, Table
In this manual,
Table
was in the EPASWMM 4
Manual,Table
20-1
20-2
20-3
20-4
20-5
20-6
20-7
20-8
20-9
20-10
20-11
20-12 deleted
20-13
20-14
20-15
20-16
20-17
20-18
20-19
20-20
20-21
SWMM Manual II-1
SWMM Manual II-2
SWMM Manual II-3
SWMM Manual II-4
SWMM Manual II-5
SWMM Manual 4-2
SWMM Manual 4-7
SWMM Manual 4-8
SWMM Manual 4-9
SWMM Manual 4-10
SWMM Manual 4-11
n/a
SWMM Manual 4-5
SWMM Manual 4-6
SWMM Manual X-1
SWMM Manual X-2
SWMM Manual 4-13
SWMM Manual 4-14
SWMM Manual 4-15
SWMM Manual 4-16
SWMM Manual 4-17
20-22
20-23
20-24
20-25 deleted
20-26
20-27
20-28
20-29
21-1
21-2
21-3
21-4
21-5
21-6
21-7
21-8
21-9
21-10
21-11
21-12
SWMM Manual 4-18
SWMM Manual 4-19
SWMM Manual 4-20
deleted
SWMM Manual 4-22
SWMM Manual 4-23
SWMM Manual 4-24
SWMM Manual 4-25
SWMM Manual 6-2
SWMM Manual 6-3
SWMM Manual 6-4
SWMM Manual 6-5
SWMM Manual 6-6
SWMM Manual VIII-1
SWMM Manual VIII-2
SWMM Manual VIII-3
EXTRAN Manual 5-1
EXTRAN Manual 5-2
EXTRAN Manual 5-3
SWMM Manual IV-1
xxxiii
USEPA Documentation Equivalence
Figures
In this manual,
Figure
was in theEPA SWMM 4
Manual,Figure
In this manual,
Figure
Was, in theEPA SWMM 4
Manual, Figure
20-1
20-2
20-3
20-4
20-5
20-6
20-7
20-8
20-9
20-10
20-11
20-12
20-13
20-14
20-15
20-16
20-17 deleted
20-18 deleted
20-19
20-20
20-21
20-22
20-23
20-24
20-25
20-26
20-27
20-28
20-29
SWMM Manual II-1
SWMM Manual II-2
SWMM Manual II-3
SWMM Manual II-4
SWMM Manual II-5
SWMM Manual II-6
SWMM Manual II-7
SWMM Manual II-8
SWMM Manual 4-23
SWMM Manual 4-24
SWMM Manual V-1
SWMM Manual V-2
SWMM Manual V-3
SWMM Manual V-4
SWMM Manual V-5
SWMM Manual V-7
n/a
n/a
SWMM Manual 4-14
SWMM Manual 4-15
SWMM Manual 4-17
SWMM Manual 4-18
SWMM Manual X-1
SWMM Manual X-2
SWMM Manual X-3
SWMM Manual X-4
SWMM Manual X-5
SWMM Manual X-6
SWMM Manual X-7
20-30
20-31
20-32
20-33
20-34
20-35
20-36
20-37
20-38
21-1
21-2
21-3
21-4
21-5
21-6
21-7
21-8
21-9
21-10
21-11
21-12
21-13
21-14
21-15
21-16
21-17
21-18
21-19
21-20
SWMM Manual X-8
SWMM Manual X-9
SWMM Manual X-10
SWMM Manual 4-27
SWMM Manual 4-28
SWMM Manual 4-29
SWMM Manual 4-38
SWMM Manual 4-39
SWMM Manual 4-40
SWMM Manual 6-2
SWMM Manual 6-3
SWMM Manual 6-4
SWMM Manual 6-7
SWMM Manual 6-8
SWMM Manual 6-10
SWMM Manual 6-11
EXTRAN Manual 5-2
EXTRAN Manual 5-3
EXTRAN Manual 5-4
EXTRAN Manual 5-5
EXTRAN Manual 5-6
EXTRAN Manual 5-7
EXTRAN Manual 5-8
EXTRAN Manual 2-4
EXTRAN Manual 2-6
EXTRAN Manual 2-7
EXTRAN Manual 2-8
EXTRAN Manual 2-9
EXTRAN Manual 2-10
xxxiv
USEPA Documentation Equivalence
Equations
In this manual
Equation:
was, in the EPA Manual,
Equation
In this manual
Equation:
was, in the EPA Manual,
Equation
20-1
20-2
20-3
20-4
20-5
20-6
20-7
20-8
20-9
20-10
20-11
20-12
20-13
20-14
20-15
20-16
20-17
20-18
20-19
20-20
20-21
20-22
20-23
20-24
20-25
20-26
20-27
20-28
20-29
20-30
20-31
20-32
20-33
20-34
20-35
20-36
20-37
20-38
20-39
20-40 deleted
20-41 deleted
20-42 deleted
SWMM II-1
SWMM II-2
SWMM II-3
SWMM II-4
SWMM II-5
SWMM II-6
SWMM II-7
SWMM II-8
SWMM II-9
SWMM II-10
SWMM II-11
SWMM II-12
SWMM II-13
SWMM II-14
SWMM II-15
SWMM II-16
SWMM III-1
SWMM III-2
SWMM III-3
SWMM III-4
SWMM III-5
SWMM III-6
SWMM III-7
SWMM III-8
SWMM III-9
SWMM III-10
SWMM III-11
SWMM III-12
SWMM III-13
SWMM III-14
SWMM III-15
SWMM 4-1 and II-17
SWMM 4-2 and II-18
SWMM 4-3 and II-19
SWMM II-20
SWMM II-21
SWMM II-22
SWMM II-23
SWMM II-24
n/a
n/a
n/a
20-43
20-44
20-45
20-46
20-47
20-48
20-49
20-50
20-51
20-52
20-53
20-54
20-55
20-56
20-57
20-58
20-59
20-60
20-61
20-62
20-63
20-64
20-65
20-66 deleted
20-67 deleted
20-68 deleted
20-69
20-70
20-71
20-72
20-73
20-74
20-75
20-76
20-77
20-78
20-79
20-80
20-81
20-82
20-83
20-84
SWMM 4-24
SWMM 4-25
SWMM 4-18mod & V-1
SWMM V-2
SWMM V-3
SWMM V-4
SWMM V-5
SWMM V-6
SWMM V-7
SWMM V-8
SWMM V-9
SWMM V-10
SWMM V-11
SWMM V-12
SWMM V-13
SWMM V-14
SWMM 4-19mod & V-15
SWMM 4-20 & V-16
SWMM V-17
SWMM V-18
SWMM V-19
SWMM V-20
SWMM V-21
n/a
n/a
n/a
SWMM 4-21
SWMM V-22
SWMM V-23
SWMM V-24
SWMM V-25
SWMM V-26
SWMM V-27
SWMM V-28
SWMM V-29
SWMM V-30
SWMM V-31
SWMM 4-22
SWMM 4-23
SWMM V-32
SWMM V-33
SWMM V-34
xxxv
USEPA Documentation Equivalence
Equations continued
In this manual
Equation:
was, in the EPA Manual,
Equation
In this manual
Equation:
was, in the EPA Manual,
Equation
20-85
20-86
20-87
20-88
20-89
20-90
20-91
20-92
20-93
20-94
20-95
20-96
20-97
20-98
20-99
20-100
20-101
20-102
20-103
20-104
20-105
20-106
20-107
20-108
20-109
20-110
20-111
20-112
20-113
20-114
20-115
20-116
20-117
20-118
20-119
20-120
20-121
20-122
20-123
20-124
20-125
20-126
20-127
SWMM V-35
SWMM V-36
SWMM V-37
SWMM 4-9
SWMM 4-10
SWMM 4-11
SWMM 4-12
SWMM 4-13
SWMM 4-14
SWMM 4-16
SWMM 4-17
SWMM X-1
SWMM X-2
SWMM X-3
SWMM X-4
SWMM X-5
SWMM X-6
SWMM X-7
SWMM X-8
SWMM X-9
SWMM X-10
SWMM X-11
SWMM X-12
SWMM X-13
SWMM X-14
SWMM X-15
SWMM X-16
SWMM X-17
SWMM X-18
SWMM X-19
SWMM X-20
SWMM X-21
SWMM X-22
SWMM X-23
SWMM X-24
SWMM X-25
SWMM X-26
SWMM X-27
SWMM X-28
SWMM X-29
SWMM X-30
SWMM 4-41
SWMM 4-42
20-128
20-129
20-130
20-131
20-132
20-133
20-134
20-135
20-136
21-1
21-2
21-3
21-4
21-5
21-6
21-7
21-8
21-9
21-10
21-11
21-12
21-13
21-14
21-15
21-16
21-17
21-18
21-19
21-20
21-21
21-22
21-23
21-24
21-25
21-26
21-27
21-28
21-29
21-30
21-31
21-32
21-33
21-34
SWMM 4-43
SWMM 4-44
SWMM 4-45
SWMM 4-46
SWMM IX-1
SWMM IX-2
SWMM IX-3
SWMM IX-4
SWMM IX-5
SWMM 6-1
SWMM 6-2
SWMM 6-3
SWMM 6-5
SWMM 6-6
SWMM 6-7
SWMM 6-8
SWMM 6-9
SWMM 6-10
SWMM 6-11
SWMM VI-12
EXTRAN A-1
EXTRAN A-2
EXTRAN A-3
EXTRAN A-4
EXTRAN A-5
EXTRAN A-6
EXTRAN A-7
EXTRAN A-8
EXTRAN A-9
EXTRAN A-10
EXTRAN 5-1
EXTRAN 5-2
EXTRAN 5-3
EXTRAN 5-4
EXTRAN 5-5
EXTRAN 5-6
EXTRAN 5-7
EXTRAN 5-8
EXTRAN 5-9
EXTRAN 5-10
EXTRAN 5-11
EXTRAN 5-12
EXTRAN 5-13
xxxvi
USEPA Documentation Equivalence
Equations continued
In this manual
Equation:
was, in the EPA Manual,
Equation
In this manual
Equation:
was, in the EPA Manual,
Equation
21-35
21-36
21-37
21-38
21-39
21-40
21-41
21-42
21-43
21-44
21-45
21-46
21-47
21-48
21-49
21-50
21-51
21-52
21-53
21-54
21-55
21-56
21-57
21-58
21-59
21-60
21-61
21-62
21-63
21-64
EXTRAN 5-14
EXTRAN 5-15
EXTRAN 5-16
EXTRAN 5-17
EXTRAN 5-18
EXTRAN 5-19
EXTRAN 5-20
EXTRAN 5-21
EXTRAN 5-22
EXTRAN 5-23
EXTRAN 5-24
EXTRAN 5-25
EXTRAN 5-26
EXTRAN 5-27
EXTRAN 5-28
EXTRAN 5-29
EXTRAN 5-30
EXTRAN 5-31
EXTRAN C-1
EXTRAN C-2
EXTRAN C-3
EXTRAN C-4
EXTRAN C-5
EXTRAN C-6
EXTRAN C-7
EXTRAN C-8
EXTRAN C-9
EXTRAN C-10
EXTRAN C-11
EXTRAN C-12
21-65
21-66
21-67
21-68
21-69
21-70
21-71
21-72
21-73
21-74
21-75
21-76
21-77
21-78
21-79
21-80
21-81
21-82
21-83
21-84
21-85
21-86
21-87
21-88
21-89
21-90
21-91
21-92
21-93
21-94
EXTRAN C-13
EXTRAN C-14
EXTRAN C-16
EXTRAN C-17
EXTRAN C-18
EXTRAN 2-1
EXTRAN 2-2
EXTRAN 2-3
EXTRAN 2-4
EXTRAN 2-5
EXTRAN 2-6
EXTRAN 2-9
EXTRAN 2-10
EXTRAN 2-11
EXTRAN 2-12
EXTRAN 2-13
EXTRAN 2-14
SWMM IV-1
SWMM IV-2
SWMM IV-3
SWMM IV-4
SWMM IV-5
SWMM IV-6
SWMM IV-7
SWMM IV-8
SWMM IV-9
SWMM IV-10
SWMM IV-11
SWMM IV-12
SWMM IV-13
xxxvii
USEPA Documentation Equivalence
xxxviii
S.I.–U.S. Units Equivalence
Conversion of SI units to U.S. customary units
We use Canadian spelling here (metres for meters and litres for liters).
To convert from (SI)
Conversion factor
To get U.S. Customary
Length and velocity
Metres (m)
Metres
Metres per second (m/s)
Centimeters (cm)
Milimeters (mm)
Kilometers (km)
m3/(m2-day) = m/day
Multiply by 3.28
Multiply by 1.094
Multiply by 2.237
Multiply by 0.39
Divide by 25.4
Divide by 1.608
Multiply by 24.6
Feet (ft)
Yards
Miles per hour (mph)
Inches (in.)
Inches
Miles (mi)
gpd/ft2
Area
cm2
m2
Hectare (ha = 10 000 m2)
km2 ( = 100 ha = 106 m2)
Divide by 6.45
Multiply by 10.76
Multiply by 2.46
Multiply by 0.387
Square inch
Square foot (ft2)
Acre
Square mile
Volume
Litres ( = 1 dm3)
cubic metre (m3)
Litres (L)
Litres (L)
Litres/(s-ha)
m3
m3
m3
Liters per second (L/s)
(L/s)
Liters/m2
Divide by 28.3
Multiply by 35.4
Divide by 3.78
Divide by 4.54
Multiply by 0.014
Divide by 3 780
Multiply by 8.54
Divide by 1 230
Divide by 43.75
Multiply by 15.87
Divide by 40.76
Cubic foot (ft3)
ft3
U.S. gal
Imp. gal
Inches/hour
Million U.S. gal (mg/MG)
Barrel
Acre-ft
Million U.S. gal/day (mgd)
gal/min (gpm)
gal/ft2
Mass
Gram (g)
Gram
Kilogram(kg = 1 000 g)a
Newton ( = 0.1 kgb)
Tonne Metric ton ( = 1 000 kg)
Tonne (t)
Divide by 454
Multiply by 15.43
Multiply by 2.2
Multiply by 0.225
Multiply by 1.1
Multiply by 0.98
Pounds (lb)
Grain
Pounds
Pounds
U.S. ton
English ton
a
Metric kilograms in this table are weight kilograms which equal
9.81 (m/s2) x kg (mass) = 9.81 Newtons.
xxxix
S.I.–U.S. Units Equivalence
To convert from (SI)
Conversion factor
To get U.S. Customary
Multiply by 1.0
Parts per million (ppm)
Divide by 2.29
Multiply by 1.0
Grain/ft3
Parts per billion (ppb)
Density
kg/m3
g/m3
m3/kg
Divide by 16
Multiply by 6.24 x 10-5
Multiply by 16.03
lb/ft3
lb/ft3
ft3/lb
Pressure
g/m2
Bar ( = 105 N/m2)
kg/m2
kg/cm2
Divide by 4 885
Multiply by 14.2
Divide by 4.89
Multiply by 14.49
lb/ft2
psi ( = lb/in.2)
lb/ft2
psi
Multiply by 3.41
Multiply by 1.34
Multiply by 3 409.5
Multiply by 5
Multiply by 176
Multiply by 53.6
Divide by 252
Btu/hr
Horsepower (hp)
Btu
hp/mg
Btu/ft2/°F
Btu/ft3/°F
Btu
Multiply °C by 1.8
and add 32
Degrees Fahrenheit (°F)
Concentration
Milligram per liter
(mg/liter = g/m3)
mg/liter
Microgram per liter
(µg/liter = 10-3 g/m3)
Energy etc.
Watt (W = N x m/s)
Kilowatts (kW = 1 000 W)
Kilowatt-hours (kW-hr)
W/m3
kW-hr/(m2x°C)
kW-hr/(m3x°C)
Calories (gram)
1 calorie = 1.16 x 10-6 kW-hr
Degree celsius (°C)
Some constants
1 m3 of water weighs 1 000 kg.
1 ft3 of water weighs 62.4 lb.
1 U.S. gal of water weighs 8.34 lb.
1 Imp. (English) gal of water weighs 10 lb.
1 day has 1 440 minutes and 86 400 seconds.
Some magnitude prefixes for SI units
G
giga
109
M
mega
106
k
kilo
103
m
milli
10-3
µ
micro
10-6
Time abbreviations
Second
s
Minute
min
Hour
h
Day
d
Week
week
Month
month
Year
y
xl
Chapter 1
Introduction
Chapter 1 has been extensively edited by William James, most recently in October 2010.
1.1 What Is SWMM?
The USEPA Storm Water Management Model (SWMM) is a computer program
that computes dynamic rainfall-runoff for single event and long-term (continuous or period-of-record) runoff quantity and quality from developed urban and
undeveloped or rural areas. The runoff component of SWMM operates on a collection of subcatchment areas that receive precipitation and generate runoff and
pollutant loads. The routing portion of SWMM transports this runoff overland
and underground through a system of pipes, channels, storage and treatment devices, pumps, and regulators. SWMM tracks the quantity and quality of runoff
generated within each subcatchment, and the flow rate, flow depth, and quality
of water in each pipe and channel during a simulation period comprised of multiple time steps.
SWMM was first developed in 19711 and has undergone several major upgrades since then.2 It continues to be widely used throughout the world for
planning, analysis, design, management and litigation related to storm water
runoff, combined sewers, sanitary sewers, and other drainage systems in urban
areas, with many applications in non-urban areas as well. The current edition,
Version 5, is a complete re-write of the previous release. SWMM 5 provides an
integrated environment for editing study area input data, running hydrologic,
hydraulic and water quality simulations, and viewing the results in a variety of
formats. These include color coded drainage area and conveyance system maps,
time series graphs and tables, profile plots, and statistical frequency analyses.
This rewrite of SWMM was produced by the Water Supply and Water Resources Division of USEPA’s National Risk Management Research Laboratory
with assistance from the consulting firm of CDM, Inc.
1
Metcalf & Eddy, Inc., University of Florida, Water Resources Engineers, Inc. Storm Water Management
Model, Volume I – Final Report, 11024DOC07/71, Water Quality Office, Environmental Protection
Agency, Washington, DC, July 1971.
2
Huber, W. C. and Dickinson, R.E., Storm Water Management Model, Version 4: User’s Manual,
EPA/600/3-88/001a, Environmental Research Laboratory, U.S. Environmental Protection Agency, Athens, GA, October 1992.
1
2
Introduction
1.2 Modeling Capabilities
SWMM accounts for various hydrologic processes that produce runoff
from urban areas. These include:
• time-varying rainfall;
• evaporation of standing surface water;
• snow accumulation and melting;
• rainfall interception in depression storage;
• infiltration of rainfall into unsaturated soil layers;
• percolation of infiltrated water into groundwater layers;
• interflow between groundwater and the drainage system;
• nonlinear reservoir routing of overland flow; and
• capture and retention of rainfall/runoff with various types of low
impact development (LID) practices.
Spatial variability in all of these processes is achieved by dividing a study area into a collection of smaller, homogeneous (to the extent that their processses
can be reasonably represented by parameters averaged over the sub-area) subcatchment areas, each containing its own fraction (or not) of pervious and
impervious sub-areas. Overland flow can be routed between sub-areas, between
subcatchments, or between entry points of a drainage system.
SWMM also contains flexible hydraulic modeling capabilities to route runoff
and external inflows through the drainage system network of surfaces, pipes,
channels, storage/treatment units and diversion structures. These include the
ability to:
• handle networks of unlimited size;
• use a wide variety of standard closed and open conduit shapes as
well as natural channels;
• model special elements such as storage/treatment units, flow dividers, pumps, weirs, and orifices;
• apply external flows and water quality inputs from surface runoff,
groundwater interflow, rainfall-dependent infiltration/inflow, dry
weather sanitary flow, and user-defined inflows;
• utilize steady-state, kinematic wave or full dynamic wave flow routing methods;
• model various flow regimes, such as free-surface, backwater, surcharging, reverse flow, surface ponding and surface flooding;
• apply rating curves for inlet controls; and
• apply user-defined dynamic control rules to simulate the operation of
pumps, orifice openings, and weir crest levels.
In addition to modeling the generation and transport of runoff flows,
SWMM 5 can also estimate the production of pollutant loads associated with
this runoff, or generated in wastewater (dry-weather) flows. The following pro-
Introduction
3
cesses can be modeled for any number of user-defined water quality constituents:
• dry-weather pollutant buildup over different land uses;
• pollutant washoff from specific land uses during storm events;
• direct contribution of rainfall deposition;
• reduction in dry-weather buildup due to street cleaning;
• reduction in washoff load due to LIDs and BMPs;
• entry of dry weather sanitary flows and user-specified external inflows at any point in the drainage system;
• routing of water quality constituents through the drainage system;
and
• reduction in constituent concentration through treatment in storage
units or by natural processes in conduits (pipes and channels).
1.3 Typical Applications Of SWMM
Since its inception, SWMM has been used in many thousands of sewer and
stormwater studies throughout the world. Typical applications include:
• design and sizing drainage system components for flood control;
• sizing detention facilities and their appurtenances for flood control
and water quality protection;
• mapping flood plains in natural channel systems;
• designing control strategies for minimizing combined sewer overflows;
• evaluating the impact of inflow and infiltration on sanitary sewer
overflows;
• with PCSWMM’s radar-rainfall software, viewing and managing in
real-time the flows in a drainage system;
• with PCSWMM’s GIS software, computing the translation of unsteady surface waves in a pseudo-two-dimensional drainage system;
• generating non-point source pollutant loadings for waste load allocation studies; and
• evaluating the effectiveness of LIDs and BMPs for reducing wet
weather pollutant loadings.
1.4 Installing EPA SWMM
USEPA SWMM Version 5 is designed to run under the Windows
98/NT/ME/2000/XP/Vista/7 operating system of an IBM/Intel-compatible personal computer It is distributed as a single file, epaswmm5_setup.exe, which
contains a self-extracting setup program. To install USEPA SWMM:
1. Select Run from the Windows Start menu.
4
Introduction
2. Enter the full path and name of the epaswmm5_setup.exe file or
click the Browse button to locate it on your computer.
3. Click the OK button type to begin the setup process.
The setup program will ask you to choose a folder (directory) where the
SWMM program files will be placed. The default folder is c:\Program
Files\EPA SWMM 5.0. After the files are installed your Start Menu will have a
new item named EPA SWMM 5.0. To launch SWMM, simply select this item
off of the Start Menu, and then select EPA SWMM 5.0 from the submenu that
appears. (The name of the executable file that runs SWMM under Windows is
epaswmm5.exe.)
Under Windows 2000, XP, Vista and 7, a user’s personal settings for running
SWMM are stored in a folder named EPASWMM under the user’s Application
Data directory. If you need to save these settings to a different location, you can
install a shortcut to SWMM 5 on the desktop whose target entry includes the
name of the SWMM 5 executable followed by /s <userfolder>, where
<userfolder> is the name of the folder where the personal settings will be stored.
An example might be:
“c:\Program Files\EPA SWMM 5.0\epaswmm5.exe” /s “My Folders\SWMM5\”.
To remove USEPA SWMM from your computer:
1. Select Settings from the Windows Start menu;
2. Select Control Panel from the Settings menu;
3. Double-click on the Add/Remove Programs item;
4. Select EPA SWMM 5.0 from the list of programs that appears; and
5. Click the Add/Remove button.
1.5 Steps In Using SWMM
One typically carries out the following steps when using SWMM to model
stormwater runoff over a study area:
1. Specify a default set of options and object properties to use (see
chapter 3.2);
2. Draw a network representation of the physical components of the
study area (see chapter 3.3);
3. Edit the properties of the objects that make up the system (see chapter 3.4);
4. Select a set of analysis options (see chapter 3.5);
5. Run a simulation (see chapter 3.5).; and
6. View the results of the simulation (see chapter 3.5).
Alternatively, instead of developing a new model as in steps 1 through 4, one
may convert an input file from another datafile or even from an older version of
SWMM.
Introduction
5
1.6 TIPS For Getting Started
This chapter presents a wide range of tips for getting your SWMM model up and
running. It includes a description of the latest SWMM engines, lists some
sources of help and of example files, and ends with a discussion of sound modeling strategy. The website www.CHIwater.com is a source of more help,
andyou may also get help by emailing CHI staff at [email protected]
A tip for beginners is to develop your data file from the simple examples
provided in the various sources below, and let the program help determine the
source of the problem, by repeatedly re-running the data file and examining the
output file for the termination message and termination point. When you get
stuck, which will happen if you are normal, the information in this chapter may
prove crucial to your progress.
Welcome to the rewarding world of modeling better engineered environments, our SWMMer’s world.
1.6.1 Use The Latest SWMM Engine
Corrections and updates to SWMM 5 from USEPA are available from the website http://www.epa.gov/ednnrmrl/swmm/.
It is sound practice to use the most recent version of SWMM, which ipso facto has the most corrections and options. Having said that, information on
SWMM 4, is available at http://cce.oregonstate.edu/water/swmm/.
1.7 Sources Of Help
1.7.1 Users’ Group Meetings
Another step that you can take is to attend users' group meetings, which are held
each year in Toronto in February, organised by CHI, and officially recognized
by USEPA, the ASCE Urban Water Resources Research Council, the AWRA,
the CSCE, the Ontario MOE, and Conservation Ontario. Information on these
conferences is available at www.CHIwater.com, the CHI website. Usually attended by more than 100 professionals, they are convivial, inexpensive,
informative, and the proceedings constitute the collection of peer-reviewed,
high-quality reference books listed in the front papers of this manual. Individual
chapters from these proceedings (or monographs), from 1992 onwards, are
available for purchase as downloadable PDF files at the CHI website.
1.7.2 List Server
A further step is to join the Internet discussion group, SWMM-USERS, hosted
by the University of Guelph. List servers provide a means for subscribers to get
quick answers to questions and participate in discussions relating to the list serv-
6
Introduction
er topics. SWMM-USERS is a forum for more than 700 (in September 2010)
users of the public-domain USEPA SWMM program to share ideas and ask
questions on issues related to urban drainage management modeling. Subscription is free, and subscribers receive all the email that is sent to the list and can in
turn send email to the list. Many SWMM errors, questions and problems are
resolved within this busy but noise-free discussion group, and changes to
SWMM are announced here. You can ask other subscribers for help as probably
your problems have been encountered by others and already solved. A searchable archive of past questions and answers is available through CHI’s SWMM
Q&A database. The ever-expanding searchable archive of SWMM-USERS
questions and answers is an excellent resource for past SWMM-USERS dialog
and for storm water management modeling information in general. To see
whether a solution already exists, search the Q&A archive (described below).
Subscribing to SWMM-USERS
To subscribe to the list, send an email to [email protected] Do not
put anything in the subject line and, in the body of the message, include the following line (with no other text and no brackets):
SUBSCRIBE SWMM-USERS [first name] [last name]
For example,
SUBSCRIBE SWMM-USERS JANE DOE
It is very important to subscribe to the list from the email account you wish
to use for SWMM-USERS communications (your reply to email address is used
by the list server). Also, if you are changing or terminating an email address,
please remember to unsubscribe from that address before you close it.
Once subscribed, you will receive a confirmation email detailing the email
address to send SWMM-USERS communications to, and providing other information about the list server. Please archive all of those emails for future
reference.
Unsubscribing from SWMM-USERS
To leave the list, send this message (with no other text and no brackets) to the
subscription address ([email protected]):
SIGNOFF SWMM-USERS
Other information
When you are temporarily away from your email account, you may find it
convenient to receive SWMM-USERS communications in digest form. To do
this, send the following line (from your subscribed email account) to
[email protected]:
SET SWMM-USERS MAIL DIGEST
Introduction
7
Guidelines for posting to the SWMM-USERS list server are posted at
http://www.CHIwater.com. It is important to read them, as transgressing one or
more of the guidelines will probably result in termination of your list server subscription.
1.7.3 SWMM Q&A
All items in our SWMM Q&A knowledge base were derived from discussion on
the SWMM-USERS Internet list server. SWMM-USER list server subscribers
can view the original archived posts by sending an email to
[email protected], with the following message in the body:
Get SWMM-USERS logfilename.
Disclaimer
Neither the writer nor CHI cannot be held responsible for any consequences
incurred from following the advice in the knowledge base. We suggest that interested parties obtain the archived posts and contact the original contributors
before acting on any specific advice.
The knowledge base is updated regularly. Topics can be viewed by subject,
chronologically, or searched by keywords-in-context.
Before posting your question to the list, please search the archive for similar
or better questions and answers.
1.7.4 On-Line Help
In common with a few other organizations, CHI offers certain services for both
SWMM, and PCSWMM, e.g. telephone, fax, email and web-based support,
workshops at locations across the United States, Canada, and abroad, in-house
and on-line seminars, upgrades, and customized software. The following utilities
are also provided.
Bibliographic database
PCSWMM provides instant access to reference information on 10 000 papers
given at SWMM users' meetings and other conferences. The database includes
full, searchable abstracts for many of these, two powerful search engines, and an
intuitive user interface.
On-line assistance
PCSWMM comes with extensive, online, indexed and searchable help (over
60 000 words) which provides a variety of key modeling information. Step-bystep instructions are available for all PCSWMM procedures, with known trouble
spots highlighted for quick explanation. PCSWMM also provides complete
online help for all aspects of SWMM data file development. As indicated previously, continuously updated help is available through the searchable SWMM
Q&A knowledge base (over 3 000 modeling questions and answers).
8
Introduction
1.7.5 Useful Practice SWMM Runs That You Can Execute
Sample exercises are available from time to time on the PCSWMM Getting
Started link at the CHI website (www.chiwater.com).
1.8 Continuous Modeling Philosophy
A common concern is the reliability of the interpretation of the model output.
The point of this part of this manual is to help you develop a robust method for
reliable, long-term SWMM modeling. Further guidance in general modeling
philosophy is given in the 300 page book Rules for Responsible Modeling by
William James, ISBN 0-9683681-5-8.
The effort starts with a clear statement of the design problems to be addressed by the modeling exercise, and ends with careful interpretation of the
model results, their uncertainty, and their relationship to the design questions.
To come to terms with the task of relating the modeling to the design problems, the problems may at the outset be formulated as a list of questions (James
and Robinson, 1981a;1981b), each with a question mark. For example:
• What is the cheapest, or smallest, storm water sewer or conveyance
necessary to convey flows from Foxran Developments?
• What is the cheapest, or smallest geometry, culvert at Cross St.?
• What will be the mean annual flooding and pollution damages
(costs) downstream as a result of the Foxran Developments?
• What size, or volume, of detention storage is necessary at Cross St.
to ensure that there will be no net increase in flux of storm water or
associated pollutants into Mud Creek as a result of the Foxran Estates development?
• What capacity of pump station is required to eliminate all combined
sewer overflows to Parkside Beach from the Cross St interceptor?
• What is the maximum quantity, or flow rate, of sewage treatment
plant effluent, or storm water, that can be added to Mud Creek at
Cross St. during low flows in July, without violating federal and local water quality objectives?
The precise questions should be formally established by mutual discussions
between the client, engineering committee, and the modelers. When design
questions are formulated in this simple manner, it is much easier to relate the
design problems to the required model output, to select the best objective functions and evaluation criteria, and to provide quantitative solutions.
Unfortunately, for a novel, proposed structure, for example, where no suitable
code is available, model users often fudge the input to simulate the required process using a similar, existing process. You should be wary of becoming trapped
in an uncertain procedure, and rather you should openly seek the approval of
Introduction
9
your clients and publics before doing so. General approval of stated questions
will help you to approximate the required processes, so far as they are known.
In the surface water quality modeling litany, models that disregard all dryweather processes are referred to as event models, while models that include
code for processes that are active during dry weather, such as pollutant build-up,
evapo-transpiration, storage depletion, recovery of loss rates, and so on, are
termed continuous (or period of record) models. Continuous models also usually
include processes associated with winter seasons. The difficulty with event
modeling is that every model run is governed by arbitrary assumptions of startup
conditions, which are themselves not subject to careful modeling scrutiny, such
as sensitivity analysis, calibration, and error analysis. Event models are obviously only run for short durations. To the extent that the effect of these initial
conditions persists through the model run, the computed results may be unreliable. There is a great deal of hydrology literature asserting that these start-up
effects are indeed important (James and Robinson, 1986a, provide a review).
Klemes (1987) eloquently condemns event modelers who claim to be able to
compute risk and reliability.
Event modeling evolved in bygone times before computing, and it is simply
no longer appropriate to adopt such simplistic methodology (James and Shivalingaiah, 1986). However, short runs for both dry and wet events, and events that
are combinations thereof, are recommended for analysis of sensitivity, parameter estimates and error. In these cases there is no start-up error, because the
initial state is given by the observed record.
The major difficulty associated with continuous models, on the other hand,
relates to the copious amounts of input, state, and output information that must
be managed. SWMM provides code for this purpose, but inexperienced continuous model users can soon mismanage computer storage capacity. Although
storage capacity for the computed response functions is probably the most stringent constraint, requiring gigabytes for even moderate design problems, the
literature has focused rather on computer time, as there are limits on the duration
of the simulation that inexpensive workstations can handle in the span of a routine day in the design office. Contrary to widespread belief, it is unnecessary to
have long observed time series to develop a reliable, continuous model; there
need only be sufficient, good, observed time series to cover the number of
events needed for the parameter optimization. It turns out that the total field data
collection effort (for calibration) is not significantly different for event and continuous models. This is because the dry weather inter-event records can be
obtained at virtually no increase in cost. Sometimes, when good data is available
only in nearby drainage systems, or elsewhere in the system, two models are
developed, and the optimized parameters transposed to the model lacking data.
In either case, the observed time series, which must be accurate, say, for a duration of a year or two, must be searched for the requisite events for calibration.
Occasionally, for simple single purpose design objectives, this can be managed
for records as short as a few months.
10
Introduction
Of course, a credible long input time series is required for the inferential
runs, as-was scenario, or when all the alternative to-be arrays of LIDs and BMPs
are to be compared. But this long input time series need only be transposed from
a similar hydrometeorologic region, or it may be generated synthetically from a
reasonably long observed time series in the same hydrologic region. The important point here is that the continuous input time series driving the continuous
model, will not be used for calibration, but only for comparing various scenarios. It is only necessary, then, for the long-term input time series to be entirely
plausible; the test is: Could this input time series have equally likely or reasonably occurred at this point? Is it credible?
The implicit design problem is to find the optimum cost effective array of
BMPs. The solution may be stated: If the 75 year rainfall time series that occurred at the International Airport had in fact occurred at Foxran Estates, then
plan 126 would have been the most cost effective of the 329 plans examined, had
they all existed over this time. This is the sort of statement usually sought by
decision makers.
Of course, the derivation procedure for design storms on the other hand results in a loss of information: the variability is reduced to simplistic
representations. But, note that once the long term continuous rain record has
been developed (i.e. processed, transposed, or generated) it is available for all
studies in that hydrologic region, much like standard design storms. It is not often recognized that the basic information is exactly the same as that originally
used to derive the design storms for that area, and that no additional data collection effort is required, unless the local design storms are in fact entirely arbitrary
or imaginary – what Klemes (1987) refers to as wishful thinking.
Model builders and model users should quantify and present the uncertainty
of their model output, to allow end-users the opportunity to evaluate the results,
and the confidence that should be placed in them. In the case of SWMM, many
applications make arbitrary judgments about parameter selection and estimation,
and use deficient data, and so the uncertainty and sensitivity to these assumptions are critical to end-users, but seldom reported.
Continuous modeling requires a sequence of two modeling activities: calibration and inference. Calibration activities involve parameter estimation and
optimization against short-term, accurate, observed input functions. Inference
activities involve long-term, continuous, synthetic or transposed input functions,
and error analysis. Figure 1.1 shows the relationship between some of these activities, namely: short-term calibration input functions (IFs); model; response
functions (RFs); objective functions (OFs); performance evaluation functions
(EFs); sensitivity analysis; parameter optimization; long-term continuous input
functions; error analysis; long-term, continuous fuzzy response functions; and
output interpretation or inference. Figure 1.1 is meant to be schematic and conceptual, and only to show the average sequence of activities in the broadest of
terms.
Introduction
11
Figure 1.1 Relationship between calibration activities.
The driving input hydro-meteorological time series for a surface WQM is
termed the input function, or input variable. Typical examples are rainfall, evapotranspiration, wind speed, wind direction, snowfall, radiation, humidity,
temperature, and some pollutant generating mechanisms such as traffic. Other
coefficients that are also input, but less likely to form very long times series at a
fine time resolution, and generally control independent component processes,
are termed parameters. It is sometimes not clear how to distinguish between input variables and environmental parameters. The computed hydrological and
water quality time series, output by SWMM, is termed the response function. An
objective function is a statistic or a representative number derived from the response function.
Programs like SWMM may be fed a large number of very long input functions (IFs), and can then provide very many response functions (RFs), for
example pollutographs (pollutant concentration), loadographs (pollutant flux),
hydrographs, cost estimates, and capacities and geometries of storages and conveyances and at many points. Many other responses can be simply inferred from
the model output. Post-processors compute several objective functions (OFs),
such as event peaks, event means, numbers and durations of exceedances and
deficits, for most of these input and response functions. There are of course also
similar objective functions for the equivalent measured or observed time series.
12
Introduction
The OF should not be confused with the evaluation function (EF), used as the
measure of agreement between the observed OFs and the computed OFs. An
example of an EF is the sum of the squares of the deviations between the observed event peak flows and the computed event peak flows in a calibration plot.
Many OFs and EFs are provided in PCSWMM.
Table 1.1 Short list of some simple response OFs.
OF1:
(t2,1 – t1,1)
duration of wet event
OF2:
(t2,2 – t1,3)
duration of dry event
OF3:
RF(t1,3)
peak flow, flux or concentration
OF4:
RF(t1,1)
minimum flow, flux or concentration
OF5:
*INT (t1,4 – t1,1)
total wet event flow or flux
OF6:
(t1,4 – t1,2)
duration of exceedance
OF7:
(t2,2 – t1,4)
duration of deficit
OF8:
n[RF >RFcrit]
number of exceedances
OF9:
n[RF <RFcrit]
number of deficits
OF10:
*INT (t2,2 – t1,4)
volume of deficit
OF11:
*INT (t1,4 – t1,2)
volume of excess
OF12:
OF5/OF1
wet event mean concentration
OF13:
*INT (t2,1 – t1,4)
total dry event flow or flux
OF14:
OF13/OF2
dry event mean concentration
* INT denotes intergral; note that the OFs and time variable are not subscripted in the table,
to save space.
The response functions computed by SWMM include both complete and
summaries of hydrographs and pollutographs, placed at the end of each output
file.These summaries for selected nodes include certain TS statistics such as
flow-weighted-average, standard deviation, maximum, minimum flow rates and
total volume of runoff for the hydrographs and flow weighted average, standard
deviation, maximum, minimum concentrations and total load for pollutants and
constituents. Such statistical derivatives from the computed response functions
are called objective functions herein, because they do not depend on the error
when compared to an observed record. Except for the flow-weighted standard
deviation, the above output objective functions are commonly used, the four
most common being the peak and total (flows and pollutants). Each of the eight
objective function types (four each for hydrographs and pollutographs) are user
selectable in PCSWMM.
The four OFs in Table 1.1 that require integration are:
t 1, 4
OF 5 = ∫ RF(t)dt
t 1, 1
t 2,2
OF 10 =
∫ [RF
t 1,4
crit
- RF(t)]dt
Introduction
13
t 1,4
OF 11 =
∫ [RF(t) - RF ]dt
crit
t 1,2
t 2,1
OF 13 = ∫ RF(t)dt
t 1,4
In Table 1.1, only fourteen simple OFs are shown, yet for (say) sixteen pollutants, the total number of possible response function OFs would be 238 per
location (of which there may be tens of thousands).
Careful selection of the best OF is necessary, a point which is perhaps seldom stressed enough. Users must themselves thoughtfully choose both the RFs
and the OFs that most closely relate to the questions to be answered (which is
why we suggested formulating them in the first place). Also, the number of OFs
should be minimized, if the amount of computed output time series is to be kept
within manageable limits. Some guidance is provided below. In the literature,
some researchers have reported that it is difficult to calibrate certain WQMs to
more than one OF (Seo, 1991).
It is important to realize that not all OFs are relevant to all parameters, or design questions. The applicability is quite restricted. In matching them, Table 1.2
(referring to just the OFs listed in Table 1.1) may be used as a first guide.
Depending on the application, the choice of OF may predicate which of the
model parameters are eventually optimized, and their absolute values. RiveraSantos (1988) and Han (1981) further discuss OFs. In an event-oriented, wateronly study to select the best OF using ILLUDAS, SWMM and MINNOUR, Han
found that the sum of the squares of the deviations between the observed and the
computed hydrograph ordinates gave the best overall performance.
Table 1.2 Dominant processes and their potentially relevant objective functions.
Dominant process
Objective function
Overland flow over impervious areas
OF3
Infiltration into the upper soil mantle
OF4
pollutantwashoff
OF5
Erosion
OF1
overland flow over pervious areas
OF3
pollutant build-up
OF5
recovery of storages
OF2
recovery of loss (infiltration) rates
OF4
recession of storages
OF7
evaporation
*IF8
snowmelt
*IF11
snow accumulation
*IF7
* Some WQMs such as SWMM can produce event analysis of
input time series, so that in this Table, IF refers to input function
(in this case, air temperature and/or wind speed); the OFs are not
subscripted to save space in the table.
14
Introduction
Jewell et al. (1978) chose the standard error of estimate (SEE, listed as EF11)
as a representative statistic to measure the accuracy of fit between observed and
SWMM-computed data:
1
2
⎡ n
2⎤
(
)
COF
OOF
i
i
∑
⎢
⎥
⎥
SEE = ⎢ i=1
n-2
⎢
⎥
⎢⎣
⎥⎦
(1.1)
where:
n = number of predicted and measured data points,
COF = predicted value of the ith data point, and
OOFi = measured value of the ith data point.
The following equation has been used to quantify overall goodness of fit:
1
" n ( COF i - OOF i ) 2 % 2
EF t = (1.0 - W ) x $!
' + (W x | OPF p - CPF p |)
n
# i=1
&
where:
(1.2)
EFt = total error statistic (m3/s),
W = weighting factor,
n = number of measured hourly flows,
OOF = measured flow (m3/s),
COF = computed flow (m3/s),
OPF = measured peak flow (m3/s), and
CPF = computed peak flow (m3/s).
Assigning a value of 1.0 to W results in a complete focusing upon matching
the peak flow. Reasonable balances between hydrograph shape and peak were
obtained with W = 0.2.
It has been shown that, for SWMM model calibration purposes, the sum of
the squared deviations between the observed and computed flows gave the best
overall performance out of a total of seventeen objective functions reviewed:
EF = !(OOF i - COF i ) 2
where:
W = the sum of squared deviations,
OOFi = the observed hydrograph ordinates, and
COFi = the calculated hydrograph ordinates.
(1.3)
Introduction
15
1.9 Error Analysis
Definitions:
Error is the difference between a computed and an observed value;
Uncertainty is taken to mean a possible value an error may have;
Variability, the different values that a parameter may have;
Variance, the square of the standard deviation (a measure of uncertainty);
and
Model complexity is a measure of the number of uncertain parameters in
a model.
There are several sources of error associated with modeling, and all should
be kept under control during design applications. In practical applications, the
most common errors may be traced to wrong data in the input files, caused by
blunders, data entry errors, and user/modeler misconceptions. But the most serious errors are probably those that are made well after the model runs are
completed: poor interpretation of the results, their inherent error, and reliability,
by model builders, users and decision-makers alike. This point perhaps needs to
be kept in mind, because the errors most commonly dealt with in the literature
exclude them, but cover others such as:
1. Observation error , related to field instrumentation, comprising two
components, one random and the other systematic;
2. Sampling error, associated with the timing and location of the field
equipment;
3. Numerical error, identified with the numerical mathematics used in
the code;
4. Structural error, related to disaggregation (the number and resolution
of the processes active);
5. Structural error, related to discretization (the spatial resolution);
6. Structural error, related to poor formulation of one or more of the
component process relations and code; and
7. Propagated error, related to erroneously estimated values of input parameters.
Observation and sampling errors, and the structural error due to process disaggregation, are related to the inherent variability of natural hydrological and
ecological systems. Models require spatial averaging, even where the spatial
heterogeneity in nature may be very large. The only way to deal with this difficulty is to increase the spatial discretization, and thus the amount of data
collection, preparation and the computing. Increasing the model complexity in
this way obviously results in increased design office costs.
The structural error due to disaggregation and poor component process models, is also called framework error. The propagated error is also known as
parameter error, and is the focus of PCSWMM. The framework error is difficult
16
Introduction
to estimate, and is therefore generally taken to be the difference between the
total model error and the parameter error.
There is some evidence that the effect of several of these sources of error can
be mitigated by careful parameter estimation. Certainly the perhaps unintentional effect in much surface water quality modeling, is to correct for what are
sometimes gross errors in all seven categories, by a substantial parameter optimization effort. To put it crudely: it is poor rain data that is often the cause of
poor computed results – by manipulating parameters controlling soil surface
infiltration capacities, calibration may be nothing more than a thoughtless quick
fix of the defective rain data.
1.10 Some Useful Websites
For ease of access, the URLs which are referenced at various points in this volume are gathered together here.As you find other helpful sites, you might want
to add them to this list.
USEPA For SWMM 5 downloads, QA Report, test data sets,test examples, updates,etc. www.epa.gov/ednnrmrl/swmm.
Oregon State University For SWMM 4 downloads and SWMM 4 documentation, etc. ftp://ftp.engr.orst.edu/pub/swmm/pc/.
NOAA NCDC For hourly precipitation data; max-min daily temperatures data sets, etc. www.ncdc.noaa.gov.
EarthInfo For hourly precipitation data; max-min daily temperatures data sets, etc. www.earthinfo.com/databases/databases.htm;
email [email protected]
Hydrosphere For hourly precipitation data; max-min daily temperatures
data sets, etc. http://hydrosphere.com or http://www.sni.net/earthinfo.
Environment Canada For Canadian data sets (e.g. rainfall IDF graphs)
and statistics, etc. www.cmc.ec.gc.ca or
www.climate.weatheroffice.ec.gc.ca.
Computational Hydraulics Inc (CHI) For SWMM and
PCSWMM.NET help, etc. www.CHIwater.com and
www.PCSWMM.NET/gettingstarted.html
SWMM Q&A archive www.swmmkb.com.
References
Han, J. 1981. Investigation and development of urban hydrologic models.Ph.D. thesis
Purdue 308pp.
James, W. 2003 Rules for Responsible Modelling.by CHI Guelph. 200 pp.
James, W. and Robinson, M.A. 1981a. Standard terms of reference to ensure satisfactory
computer-based urban drainage design studies. Can J Civ. Engrg 8:294-303.
Introduction
17
James, W. and Robinson, M.A. 1981b. Standards for Computer-based Design Studies, J.
of the Hydraulics Division, ASCE, 107(HY7) Proc. Paper 16385: 919-930, July.
James, W. and Robinson, M.A. 1986a.Continuous Deterministic Urban Runoff Modeling.
Int. Symp. in Urban Drainage Modeling, Dubrovnik, Yugoslavia, published by Pergamon Press, London, pp. 347-378, Apr 1986.
James, W. and Shivalingaiah, Boregowda, 1986. Continuous Mass Balance of Pollutant
Build-up Processes, Proc. NATO Advanced Research Workshop on Urban Runoff
Pollution, Montpellier, France, Aug 25-30, 1985, published by Springer-Verlag in Urban Runoff Pollution (Series G. Vol. 10), pp. 243-271, 1986.
Jewell, T.K., Nunno, T.J. and Adrian, D.D. 1978. Methodology for calibrating stormwater
models. Proc. Stormwater and water quality model users group meeting, May 4-5
1978. USEPA 600/9-78-019 pp 125-169.
Klemes, V.1987.Empirical and causal models in hydrologic reliability analysis.Procs
NATO Institute on Engineering reliability and risk in water resources, Tucson, Ariz.
May19-Jun2. 1985. ISBN 90-247-3492-4. pp391-403.
Rivera Santos, J. 1988.A methodology for parameter estimation in conceptual precipitation-runoff models with emphasis on error analysis. Ph.D. thesis. U.Colorado
Boulder.279 pp.
Seo, Dong-il. 1991. Optimal complexity analysis of total phosphorus models. Ph.D. thesis.
U. of Michigan Ann Arbor. 173 pp.
18
Introduction
Chapter 2
Background
2.1 Introduction
The early development of SWMM is described in “Introduction to the SWMM
Environment”, Chapter 1 in New Techniques for Modeling the Management of
Stormwater Quality Impacts, 1993, pp 1-28, published by Lewis Publishers.
Parts of that description are incorporated below, with slight edits by William
James (last dated Oct 2010) for readability.
2.1.1 Capsule History
SWMM was unusual at the time: a major U.S. Environmental Protection Agency (EPA) funding effort devoted solely to hydrologic software development
(another example was the conversion of HSP to HSPF, funded by EPA CEAM).
From 1974 there was close collaboration with Canadians - notably the Ontario
Ministry of the Environment, Environment Canada and several consultants (also
an unusual if not unique effort). Table 2.0, overleaf, encapsulates some relevant
dates.
2.2 SWMM History
Here, briefly, are some highlights from the perspective of an academic involved
marginally in SWMM development. It was written to help new users understand
the background to the code and manuals, and to lead a path through some of the
confusing literature. Textbooks, manuals and reports are not covered
Most urban stormwater code has been written and distributed for commercial
reasons. However, the ancestry, development and continuing support of SWMM
is probably unique. USEPA provided intermittent support, and research groups
at several different universities, including that of the author (William James,
lately at the University of Guelph), the University of Florida and Oregon State
University, and engineers at agencies and in consulting offices, have intermittently contributed ideas (or more materially) to the development of SWMM.
The SWMM environment is a natural consequence of active participation in
scientific, technical and engineering conferences, symposia, seminars, workshops and other meetings. Besides workshops and short courses given by CHI,
the more common meetings include:
19
20
Background
Table 2.0 Important dates in the history of SWMM.
1971 Version 1. The EPA Stormwater Management Model SWMM was developed in 19691971 and was one of the first of such models. A result of generous funding from the
USEPA, the prime contractor was Metcalf and Eddy Inc. of Palo Alto (M&E), and the
sub-contractors were University of Florida (UoF), and Water Resources Engineers
Inc. of Walnut Creek California (WRE). The joint venture was suggested by the EPA
predecessor agency, the Federal Water Quality Administration, following receipt of
three separate proposals. WRE wrote the original RUNOFF quantity, RECEIV and
GRAPH routines; M&E wrote the RUNOFF quality and STORAGe/treatment routines; and UoF wrote the TRANSPORT routines. Original documentation was
produced in four volumes by Metcalf and Eddy et al.
1973 WRE TRANS model added (later became EXTRAN). Developed out of the original
RECEIV block for an application in San Francisco
1974 – onwards. Twice yearly SWMM User Group Meetings started by Harry Torno then of
the US EPA - latterly the meetings have became known as the Stormwater and Urban
Water Systems Modeling Conferences held in Canada annually and occasionally in
the US.
1975 Version 2 produced by UoF Added: USLE, design routine in TRANS, new STORAG
equations, COMBINE block; updated manual.
1976 Canadian version by Proctor and Redfern Ltd and James F. MacLaren Ltd. Their snowmelt routines form the basis of the snowmelt in the current model.
1977 SWMM ported to minicomputer by W James (then at McMaster U). User-friendly front
end was known as FASTSWMM, and SWESWMM.
1977 EXTRAN added by CDM. Documentation elaborated to include continuous simulation.
1981 Version 3 published by UoF STORAG made generic, line IDs, metric capability, RAIN,
TEMP and STATS blocks added, RECEIV block deleted, separate users and
EXTRAN manuals issued.
1984 PCSWMM - first user-friendly personal computer version, distributed commercially with
improved documentation by CHI.
1988 Version 4 - USEPA public domain personal computer version. Free-format data entry,
natural cross-sections added. User’s manual adapted from the CHI manual published.
Temporary end of EPA support.
1991 Version 4.05 by UoF
1992 Version 4.2 by UoF
1993 Version 4.21 by Oregon State University (OSU)
1993 PCSWMM ported to Windows environment
1993 SWMM News & Notes started by CHI.
1994 SWMM-USERS listserver started in January by William James at U. of Guelph (UoG).
1994 EPA Windows SWMM for TMDL analysis in Windows environment (later abandoned).
1994 Version 4.3 by EPA CEAM (Lahey Fortran with extended memory replaced 640kB RM
Fortran as the standard).
1995 Version 4.31 by OSU and others.
1997 Version 4.4 by OSU and others.
1999 Version 4.4gu
2001 Version 4.4h
2002 Version 4.4h update
2004 Version 5 by USEPA – first release of a complete rewrite of SWMM, to run under Windows, by the Water Supply and Water Resources Division of USEPA’s National Risk
Management Research Laboratory in a joint development effort with Camp Dresser
and McKee, Inc. (CDM).
2005 Utility for converting SWMM 4 data files to SWMM 5 files. Version 1.2 by CDM.
2010 Version 5.0.018 of SWMM 5 by USEPA is the current version at the time of writing
(October 2010), with the EPA SWMM 5 Manual available as a 300 page PDF file.
Continuing development involves enhancements by USEPA, and shells by commercial software distributors, academics and other consultants.
Background
•
21
irregular six- and twelve-monthly user group conferences in the United
States and Canada. Since the early 1990s, meetings have been held annually in Toronto, and occasional meetings have been held in the United
States (although none since the 1980s);
• a series of Specialty and Engineering Foundation conferences (both
involving the Urban Water Resources Research Council of the
American Society of Civil Engineers or ASCE); and
• a series of regular international conferences every three years.
A study of the papers shows that consulting engineers, planners, geographers, aquatic biologists and related professionals concerned with urban
development and its impact on aquatic environments have contributed to the rich
literature. Graduate students have been an important feature.
Proceedings of these conferences are generally difficult to locate in libraries
or elsewhere, and the author has made available (as part of PCSWMM and the
CHI website) abstracts of most of the papers. They cover many topics of intense
interest to users of SWMM, and nicely encapsulate the changing emphasis over
the past two decades. Topics range from water flows to interdisciplinary ecosystems in the evolving networked workstation design environment.
SWMM has been under more or less continuous development for more than
three decades. Manuals were produced occasionally in response to EPA contract
agreements. Under Reaganomics, USEPA support fell away, and in the late 80s,
virtually dried up. Nevertheless, a few die-hard professors and consultants continued to support the code, despite the lack of funds.
For each major issue of the documentation, the evolving code has been bundled up and given a new version number. Software archaeologists should take
care not to infer that the historic versions of the documentation reflect the then
contemporary SWMM code; available documentation clearly lags code development by up to several decades!
The four volumes of the 1971 Stormwater Management Model report marks
an early starting point. Two volumes related to the theoretical background, and
to code validation. Volume 3 comprised the first user's manual, and volume 4
the original source code listing. That program was very limited in comparison
with later versions. Version 1 did not include a COMBINE block. The user's
manual for version 2 was published in March 1975. The program still incorporated a RECEIVing block, but no EXTRAN block.
In November 1977, interim SWMM documentation was published (still version 2 officially), and it included snowmelt, better continuous simulation, and
EXTRAN documentation. In November 1981 the user's manual for version 3
was published. The RECEIVing block was deleted, and a separate Addendum
for EXTRAN was published under the authorship of CDM of Annandale, Virginia. The program was still big-batch-mainframe oriented, and distributed on 9track tape. Later, version 3.3 was distributed by the EPA for use on microcomputer. Note that this version did not in fact include a RECEIVing block.
22
Background
Starting in 1977, William James and his group ported the code to minicomputer and later to microcomputer systems. Free-format input, 80-column output,
screen-oriented graphics, error-checking and transparent file handling was added. The documentation was rewritten in user-friendly style, the code stored on
diskettes, and the package distributed by CHI as PCSWMM.
Version 4 was the second EPA version that could run on microcomputers,
and appeared with published documentation in August 1988. It was an EPA response to PCSWMM which was a commercial product, and version 4 included
most of the attributes of PCSWMM as well as a wide range of enhancements.
The new EPA documentation reflected many of the contributions of PCSWMM,
particularly the tables of input data requirements. It was configured for operation
on hard disk, but retained much of the big-batch mainframe architecture. It was
now much better configured for continuous simulation and time-series management, incorporating a RAIN block and a TEMPERATURE block.
Version 4.30 from EPA CEAM was released in May 1994, followed by version 4.31 from OSU in January 1997. The OSU version had corrections for most
known errors but did not include some needed updates and modifications. Both
the EPA CEAM and OSU versions used the better Lahey 5.20 compiler (utilizing extended memory and giving faster run times) and had larger array sizes
than earlier OSU versions compiled with RM Fortran. But both versions now
required about 4 MB of extended memory in which to execute. All error corrections are summarized in the SWMMRDME file in the OSU version, and errors
corrected since the May 1994 EPA CEAM Version 4.30 release are identified.
Version 4.4gu (1999) was based on modifications made by Camp, Dresser and
McKee (CDM) and OSU, and had the most corrections and options. It was the
preferred option unless you had a need for an earlier version. Version 4.4gu was
then followed by SWMM 4.4h in 2001.
In 2002, USEPA’s Water Supply and Water Resources Division partnered
with the consulting firm CDM to develop a completely re-written version of
SWMM. The goal of this project was to apply modern software engineering
techniques to produce a more maintainable, extensible, and easier to use model.
The result of this effort, SWMM 5 (Rossman, 2005), consists of a platformindependent computational engine written in C as well as a graphical user interface for the Microsoft Windows operating system written in Delphi. A rigorous
quality assurance (QA) program was developed to ensure that the numerical results produced from the new SWMM 5 model would be compatible with those
obtained from SWMM 4.4 (Schade, 2002). The new SWMM 5 software was
released to the public in October of 2004.
The most numerically challenging sub-model to implement within SWMM 5
was the dynamic wave flow routing routine known as Extran (for Extended
Transport). It routes non-steady flows through a general network of open channels, closed conduits, storage facilities, pumps, orifices and weirs. In contrast to
simpler routing methods, this procedure can model such phenomena as backwater effects, flow reversals, pressurized flow, and entrance/exit energy losses.
Background
23
Rather than simply encode a line-for-line copy of Extran, SWMM 5 restructured
the code in a more readable and maintainable fashion. It also employed a slightly modified computational scheme with the intent of producing more
numerically stable solutions in less time.
In 2004 SWMM 5 was formally released by USEPA, and a SWMM 5 manual was prepared by Lewis Rossman (EPA/600/R-05/040).
By April 2008, SWMM 5, running under Windows, provided an integrated
environment for editing study area input data, running hydrologic, hydraulic and
water quality simulations, and for viewing the results in a variety of formats,
including color-coded drainage area and conveyance system maps, time series
graphs and tables, profile plots, and statistical frequency analyses.
This CHI SWMM manual, an adaptation of the EPA manuals, in which the
material was rearranged, edited and indexed for ease of use, first appeared in
1998. Regularly updated, the CHI SWMM manual was re-named User’s Guide
to SWMM in the May 2003 edition. The current User’s Guide to SWMM 5 includes the most recent USEPA SWMM 5 Manual material to October 2010, and
the September 2006 Quality Assurance Report: Dynamic Wave Flow Routing.
Regrettably there are no background theory manuals for SWMM 5 (yet), but the
SWMM 4 background theory included in this manual is still largely relevant.
The Stormwater Management Model Applications Manual (EPA /600/R-09/077)
was incorporated in Ocober 2010.
2.2.1 Derivatives Of SWMM
In the early 1990s a number of derivative codes became available in the private
domain, of which PCSWMM is one. PCSWMM uses the unadulterated EPA
SWMM 5 hydrology and hydraulics engine, and extends its capability with
many group-decision support tools that enhance professional and scientific use
of SWMM 5. As such, it is well suited to the teaching environment of universities as well as to the needs of the profession, as it includes various techniques to
expose the inherent assumptions, uncertainties and errors in the model.
2.2.2 Serial Literature
In this section we deal with the specialized serial literature only; textbooks,
manuals, research reports, and other one-off documentation are not covered.
Serials here are taken to be the result of more-or-less regular technical meetings,
particularly in North America and Europe. Australian meetings and conferences
on Urban Stormwater Quality Modeling are not listed here.
As SWMM was evolving, the literature was growing, and several textbooks
appeared. From 1976 to 1985 the University of Kentucky ran an annual conference on urban hydrology, hydraulics and sediment transport every July. The
Urban Water Resources Research Council (UWRRC) of the ASCE sponsored
sessions at various ASCE Division Specialty conferences, as well as a number
of special meetings. For a period, a conference was arranged every few years
24
Background
under the close support of the UWRRC by the Engineering Foundation. The
proceedings for all these conferences, as well as a number of related manuals,
were published by the ASCE.
Table 2.1 ASCE sanctioned conferences.
Date, Place; Title of Conference
1989, Davos, Switz; Urban Stormwater Quality Enhancement - Source Control, Retrofitting,
and Combined Sewer Tech.
1988, Potosi, MO. Design of Urban Runoff Quality Controls
1986, Hennicker, NH; Urban Runoff Quality - Impact & Quality Enhancement Technology
1983, Baltimore, MD; Urban Hydrology
1983, Niagara-on-the- Lake, ON; Emerging Computer Techniques in Stormwater and Flood
Management
1982, Hennicker, NH; Stormwater Detention Facilities
1980, Blacksburg, VA; Urban Stormwater Management in Coastal Areas
1978, Hennicker, NH; Water Problems of Urbanizing Areas
1976, Easton, MD; Guide for Prediction Analysis and Use of Urban Stormwater Data
1974, Rindge, NH; Urban Runoff Quantity and Quality
1971, Deerfield, MA; Urban Water Resources Management
Table 2.2 Some international conferences.
Date, Place, Title and Volumes of Proceedings
2008 Edinburgh, Scotland. Proc. 11th Int. Conf. on Urban Storm Drainage 11ICUD (on CD).
2005 Copenhagen, Denmark Proc. 10th Int. Conf. on Urban Storm Drainage (on CD).
2002, Portland, OR, USA. Proc. 9th Int. Conf. on Urban Storm Drainage (on CD).
1999, Sydney, Australia; Proc. 8th Int. Conf. on Urban Storm Drainage. 280 papers.
1996, Hannover,Germany; Proc. 7th . Int. Conf. on Urban Storm Drainage. 2 volumes.
Jul 93, Niagara Falls, ON; Proc. 6th Int. Conf. on Urban Storm Drainage. 2 volumes.
Jul 90, Tokyo, Japan; Proc. 5th Int. Conf. on Urban Storm Drainage. 3 volumes.
Apr 88, Duisburg West Germany; Hydrological Processes and Water Management in Urban
Areas. 1 volume.
Aug 87, Lausanne, Switzerland; Topics in Urban Stormwater Quality, Planning and Management: Proc. 4th Int. Conf. on Urban Storm Drainage. 2 volumes.
Apr 86, Dubrovnik Yugoslavia; Urban Drainage Modelling - Symposium on Comparison of
Urban Drainage Models with Real Catchment Data. 3 volumes.
Aug 85, Montpellier France; NATO Advanced Science Institute: Urban Runoff Pollution. 1
volume.
Jun 84, Goteborg Sweden; Proc. 3rd Int. Conf. on Urban Storm Drainage. 4 volume.
Jun 81, Urbana IL; Urban Stormwater Quality Management and Planning: Proc. 2nd Int.
Conf. on Urban Storm Drainage. 2 volumes.
Apr 78, Southampton UK; Proc. 1st Int. Conf. on Urban Storm Drainage. 1 volume.
25
Background
Table 2.3 USEPA sanctioned stormwater and urban water systems modeling conferences and stormwater and water quality management modelling
conferences.
Date
Feb 11,
Feb 10,
Feb 09,
Feb 08,
Feb 07,
Feb 06,
Feb 05,
Feb 04,
Feb 03,
Feb 02,
Feb 01,
Feb 00,
Feb 99,
Feb 98,
Feb 97,
Feb 96,
Feb 95,
Feb 94,
Feb 93,
Feb 92,
Apr 90,
Oct 88,
Oct 87,
Mar 87,
Sep 86,
Mar 86,
Dec 85,
Jan 85,
Sep 84,
Apr 84,
Sep 83,
Jan 83,
Oct 82,
Mar 82,
Sep 81,
Jan 81,
Jun 80,
Jan 80,
May 79,
Nov 78,
May 78,
Mar 77,
Oct 76,
Pages
,
x,
x,
544
503,
596
620,
586,
826,
511,
459,
549,
478,
455,
504,
535,
476,
519,
501,
559,
XX,
233,
175,
249,
463,
334,
426,
268,
261,
298,
274,
282,
274,
298,
551,
257,
238,
329,
413,
238,
244,
389,
334,
Source
Place
NTIS/ISBN
CHI, W. James; Toronto, ON. ISBN: tba
CHI, W. James; Toronto, ON. ISBN: tba
CHI, W. James; Toronto, ON. ISBN: tba
CHI, W. James; Toronto, ON. ISBN: 978-0-9808853-3-0
CHI, W. James; Toronto, ON. ISBN: 0-978-0-9808853-0-9
CHI, W. James; Toronto, ON. ISBN: 0-9736716-3-7
CHI, W. James; Toronto, ON. ISBN: 0-9736716-2-9
CHI, W. James; Toronto, ON. ISBN: 0-9683681-0-2
CHI, W. James; Toronto, ON. ISBN: 0-9683681-9-0
CHI, W. James; Toronto, ON. ISBN: 0-9683681-7-4
CHI, W. James; Toronto, ON. ISBN:0-9683681-6-6
CHI, W. James; Toronto, ON. ISBN:0-9683681-4-X
CHI, W. James; Toronto, ON. ISBN:0-9683681-3-1
CHI, W. James; Toronto, ON. ISBN:0-9697422-9-0
CHI, W. James; Toronto, ON. ISBN:0-9697422-8-2
CHI, W. James; Toronto, ON. ISBN:0-9697422-7-4
CHI, W. James; Toronto, ON. ISBN:0-9697422-5-8
CHI, W. James; Toronto, ON. ISBN: 0-9697422-X-X
CHI, W. James; Toronto, ON. ISBN: 1-56670-052-3
CHI, W. James; Toronto, ON. ISBN: 0-87371-898-4
unknown, T.Najarian; Eatontown, NJ
EPA-600/9-89-001, PB89 195002/AS, NTIS; Denver,CO
Howard Assocs, C. Howard; Victoria, BC
EPA-600/9-87-016, PB88-125430, Try NTIS; Denver,CO
U of Ottawa, P.Wisner; Toronto, ON
EPA-600/9-86-023, PB87-117438, Try NTIS; Orlando,FL
CHI-R149, W.James; Toronto, ON
EPA-600/9-85-016, NTIS; Gainesville,FL
CHI-R128, PB85-228302, W. James; Burlington, ON
EPA-600/9-85-003, PB85-168003, Try NTIS; Detroit, MI
GREMU 83/02, P. Beron; Montreal, PQ
EPA-600/9-83-015, PB84-118454, NTIS; Gainesville,FL
U of Ottawa, P. Wisner; Ottawa, ON
EPA-600/9-82-015, PB83 145540, NTIS; Washington,DC
CHI-R81, W. James; NiagaraFalls,ON
CHI-R83, W. James; Austin, TX
EPA-600/9-80-064, PB81 173858, NTIS; Toronto, ON
EPA-600/9-80-017, PB80 177876, NTIS; Gainesville,FL
EPA-600/9-79-026, PB80 105663, NTIS; Montreal, PQ
EPA-600/9-79-003, PB290 742/6BE, NTIS; Annapolis,MD
EPA-600/9-78-019, PB285 993/2BE, NTIS; Ottawa, ON
Conf. Proc. No.5, MOE; Toronto, ON
Conf. Proc. No.4, MOE; Toronto, ON
26
Background
A list of some relevant, focused conferences in the period 1971–89 whose
proceedings are available from the ASCE is provided in Table 2.1. The list is
not exhaustive, does not cover conferences with broader coverage than urban
stormwater management, and does not include other conferences, such as
those of the Canadian Society of Civil Engineering (CSCE).
Three-yearly international meetings were also organized by a joint committee of the International Association for Hydraulic Research and the International
Association for Water Pollution Research and Control. Venues were Southampton (UK), Urbana (IL), Gothenburg (Sweden), Lausanne (Switzerland), Osaka
(Japan), Niagara Falls (Ontario), Hannover (Germany), Sydney (Australia),
Portland (Oregon) and Edinburgh (Scotland). Other smaller, more specialized
meetings were held in Dubrovnik, Davos, Montpelier, Wageningen, Duisberg,
and elsewhere.
The UWRRC was instrumental in arranging participation by US agencies
and academics. Table 2.2 lists a selection of those meetings and their titles.
Early co-operation was established between groups in Canada and the US,
and the proceedings of several SWMM user group conferences were published
in The Storm Water Management Modeler: A bulletin to the users of the EPA’s
SWMM. The writer holds copies for meetings held in Toronto, April 1st 1976; in
Toronto October 26th 1976; Gainesville (FL) April 4–5 1977; and Milwaukee
Nov 3–4 1977. In addition, the Ontario Ministry of the Environment published
proceedings, of which the writer holds the following: Toronto, Oct 19–21 1976;
and Toronto March 28–30 1977.
Subsequent SWMM user conferences were then organized by various users,
sponsored by USEPA inter alia, and held approximately twice a year, alternating
between Canada and the U.S. The title of the conference became Stormwater
and Water Quality Management Modelling and later Stormwater and Urban
Water Systems Modeling or something similar. The proceedings of the conferences, and sources, known to the writer, are shown in reverse chronology in
Table 2.3.
References
Crawford, N.H. and Linsley, R.K., “Digital Simulation in Hydrology: Stanford Watershed
Model IV,” Tech. Report No. 39, Civil Engineering Department, Stanford University,
Palo Alto, CA, July 1966.
Johanson, R.C., Imhoff, J.C. and Davis, H.H., “User's Manual for Hydrological Simulation Program - Fortran (HSPF),” EPA-600/9-80-015, Environmental Protection
Agency, Athens, GA, April 1980.
Linsley, R.K. and Crawford, N.H., “Continuous Simulation Models in Urban Hydrology,”
Geophysical Research Letters, Vol. 1, No. 1, May 1974, pp. 59-62.
Chapter 3
SWMM 5 Quick Start Tutorial
(External To PCSWMM)
This chapter is abstracted verbatim from the EPA manual, and provides a tutorial on how to use EPA SWMM 5 externally of PCSWMM. If you are not
familiar with the elements that comprise a drainage system, and how these are
represented in a SWMM model, you might want to first review the material in
Chapter 5, Conceptual Model.
3.1 Example Study Area
In this tutorial we will model the drainage system serving a 12-acre residential
area. The system layout is shown in Figure 3-1 and consists of subcatchment
areas3 S1 through S3, storm sewer conduits C1 through C4, and conduit junctions J1 through J4. The system discharges to a creek at the point labeled Out1.
We will first go through the steps of creating the objects shown in this diagram
on SWMM's study area map and setting the various properties of these objects.
Then we will simulate the water quantity and quality response to a 3-inch, 6-h
rainfall event, as well as a continuous, multi-year rainfall record.
Figure 3-1 Example study area.
3
A subcatchment is an area of land containing a mix of pervious and impervious surfaces whose runoff
drains to a common outlet point, which could be either a node of the drainage network or another subcatchment.
27
28
SWMM 5 Quick Start Tutorial
3.2 Project Setup
Our first task is to create a new SWMM project and make sure that certain default options are selected. Using these defaults will simplify the data entry tasks
later on.
1. Launch EPA SWMM if it is not already running and select File >>
New from the Main Menu bar to create a new project.
2. Select Project >> Defaults to open the Project Defaults dialog.
3. On the ID Labels page of the dialog, set the ID Prefixes as shown in
Figure 3-2. This will make SWMM automatically label new objects
with consecutive numbers following the designated prefix.
Figure 3-2 Default ID labeling for tutorial example.
4. On the Subcatchments page of the dialog set the following default
values:
Area
4
Width
400
% Slope
0.5
% Imperv.
50
N-Imperv.
0.01
N-Perv.
0.10
Dstore-Imperv.
0.05
Dstore-Perv
0.05
%Zero-Imperv.
25
SWMM 5 Quick Start Tutorial
29
Infil. Model
<click to edit>
- Method
Green-Ampt
- Suction Head
3.5
- Conductivity
0.5
- Initial Deficit
0.26
5. On the Nodes/Links page set the following default values:
Node Invert
0
Node Max. Depth
4
Node Ponded Area
0
Conduit Length
400
Conduit Geometry
<click to edit>
- Barrels
1
- Shape
Circular
- Max. Depth
1.0
Conduit Roughness
0.01
Flow Units
CFS
Link Offstes
DEPTH
Routing Model
Kinematic Wave
6. Click OK to accept these choices and close the dialog. If you wanted
to save these choices for all future new projects you could check the
Save box at the bottom of the form before accepting it.
Figure 3-3 Map Options dialog.
Next we will set some map display options so that ID labels and symbols will
be displayed as we add objects to the study area map, and links will have direction arrows.
1. Select View >> Map Options to bring up the Map Options dialog
(see Figure 3-3).
30
SWMM 5 Quick Start Tutorial
2. Select the Subcatchments page, set the Fill Style to Diagonal and the
Symbol Size to 5.
3. Then select the Nodes page and set the Node Size to 5.
4. Select the Annotation page and check off the boxes that will display
ID labels for Subcatchments, Nodes, and Links. Leave the others unchecked.
5. Finally, select the Flow Arrows page, select the Filled arrow style,
and set the arrow size to 7.
6. Click the OK button to accept these choices and close the dialog.
Before placing objects on the map we should set its dimensions.
1. Select View >> Dimensions to bring up the Map Dimensions dialog.
2. You can leave the dimensions at their default values for this example.
3. Finally, look in the status bar at the bottom of the main window and
check that the Auto-Length feature is off.
3.3 Drawing Objects
We are now ready to begin adding components to the Study Area Map 4. We will
start with the subcatchments.
1. Begin by clicking the button on the Object Toolbar. (If the toolbar
is not visible then select View >> Toolbars >> Object). Notice how
the mouse cursor changes shape to a pencil.
2. Move the mouse to the map location where one of the corners of
subcatchment S1 lies and left-click the mouse.
3. Do the same for the next three corners and then right-click the mouse
(or hit the Enter key) to close up the rectangle that represents subcatchment S1. You can press the Esc key if instead you wanted to
cancel your partially drawn subcatchment and start over again. Don't
worry if the shape or position of the object isn't quite right. We will
go back later and show how to fix this.
4. Repeat this process for subcatchments S2 and S35.
Observe how sequential ID labels are generated automatically as we add objects to the map.
4
Drawing objects on the map is just one way of creating a project. For large projects it might be more
convenient to first construct a SWMM project file external to the program. The project file is a text file
that describes each object in a specified format as described in Appendix D of this manual. Data extracted
from various sources, such as CAD drawings or GIS files, can be used to create the project file.
5
If you right-click (or press Enter) after adding the first point of a subcatchment's outline, the subcatchment will be shown as just a single point.
SWMM 5 Quick Start Tutorial
31
Next we will add in the junction nodes and the outfall node that comprise part of
the drainage network.
1. To begin adding junctions, click the button on the Object Toolbar.
2. Move the mouse to the position of junction J1 and left-click it. Do
the same for junctions J2 through J4.
3. To add the outfall node, click the
button on the Object Toolbar,
move the mouse to the outfall's location on the map, and left-click.
Note how the outfall was automatically given the name Out1.
At this point your map should look something like that shown in Figure 3.4.
Figure 3-4 Subcatchments and nodes for example study area.
Now we will add the storm sewer conduits that connect our drainage system
nodes to one another. (You must have created a link's end nodes as described
previously before you can create the link.) We will begin with conduit C1,
which connects junction J1 to J2.
1. Click the
button on the Object Toolbar. The mouse cursor
changes shape to a crosshair.
2. Click the mouse on junction J1. Note how the mouse cursor changes shape to a pencil.
3. Move the mouse over to junction J2 (note how an outline of the
conduit is drawn as you move the mouse) and left-click to create the
conduit. You could have cancelled the operation by either right
clicking or by hitting the <Esc> key.
4. Repeat this procedure for conduits C2 through C4.
Although all of our conduits were drawn as straight lines, it is possible to draw a
curved link by left-clicking at intermediate points where the direction of the link
changes before clicking on the end node.
To complete the construction of our study area schematic we need to add a rain
gage.
1. Click the Rain Gage button
on the Object Toolbar.
2. Move the mouse over the Study Area Map to where the gage should
be located and left-click the mouse.
32
SWMM 5 Quick Start Tutorial
At this point we have completed drawing the example study area. Your system
should look like the one in Figure 3-1. If a rain gage, subcatchment or node is
out of position you can move it by doing the following:
1. If the
button is not already depressed, click it to place the map in
Object Selection mode.
2. Click on the object to be moved.
3. Drag the object with the left mouse button held down to its new position.
To re-shape a subcatchment's outline:
1. With the map in Object Selection mode, click on the subcatchment's
centroid (indicated by a solid square within the subcatchment) to select it.
2. Then click the
button on the Map Toolbar to put the map into
Vertex Selection mode.
3. Select a vertex point on the subcatchment outline by clicking on it
(note how the selected vertex is indicated by a filled solid square).
4. Drag the vertex to its new position with the left mouse button held
down.
5. If need be, vertices can be added or deleted from the outline by
right-clicking the mouse and selecting the appropriate option from
the popup menu that appears.
6. When finished, click the
button to return to Object Selection
mode.
This same procedure can also be used to re-shape a link.
3.4 Setting Object Properties
As visual objects are added to our project, SWMM assigns them a default set of
properties. To change the value of a specific property for an object we must select the object into the Property Editor (see Figure 3-5). There are several
different ways to do this. If the Editor is already visible, then you can simply
click on the object or select it from the Data page of the Browser Panel of the
main window. If the Editor is not visible then you can make it appear by one of
the following actions:
• double-click the object on the map,
• or right-click on the object and select Properties from the pop-up
menu that appears,
• or select the object from the Data page of the Browser panel and
then click the Browser’s
button.
SWMM 5 Quick Start Tutorial
33
Figure 3-5 Property Editor window.
Whenever the Property Editor has the focus you can press the F1 key to obtain a
more detailed description of the properties listed.
Two key properties of our subcatchments that need to be set are the rain gage
that supplies rainfall data to the subcatchment and the node of the drainage system that receives runoff from the subcatchment. Since all of our subcatchments
utilize the same rain gage, Gage1, we can use a shortcut method to set this property for all subcatchments at once:
1. From the main menu select Edit >>Select All.
2. Then select Edit >> Group Edit to make a Group Editor dialog appear (see Figure 3-6).
Figure 3-6 Group Editor dialog.
3. Select Subcatchment as the type of object to edit, Rain Gage as
the property to edit, and type in Gage1 as the new value.
34
SWMM 5 Quick Start Tutorial
4. Click OK to change the rain gage of all subcatchments to Gage1. A
confirmation dialog will appear noting that 3 subcatchments have
changed. Select “No” when asked to continue editing.
Because the outlet nodes vary by subcatchment, we must set them individually
as follows:
1. Double click on subcatchment S1 or select it from the Data Browser
and click the Browser's button to bring up the Property Editor.
2. Type J1 in the Outlet field and press Enter. Note how a dotted line
is drawn between the subcatchment and the node.
3. Click on subcatchment S2 and enter J2 as its Outlet.
4. Click on subcatchment S3 and enter J3 as its Outlet.
We also wish to represent area S3 as being less developed than the others.
Select S3 into the Property Editor and set its % Imperviousness to 25.
The junctions and outfall of our drainage system need to have invert elevations
assigned to them. As we did with the subcatchments, select each junction individually into the Property Editor and set its Invert Elevation to the value shown
below6.
Node
Invert
J1
96
J2
90
J3
93
J4
88
Out1
85
Only one of the conduits in our example system has a non-default property
value. This is conduit C4, the outlet pipe, whose diameter should be 1.5 instead
of 1 ft. To change its diameter select conduit C4 into the Property Editor and set
the Max Depth value to 1.5.
In order to provide a source of rainfall input to our project we need to set the
rain gage’s properties. Select Gage1 into the Property Editor and set the following properties:
Rain Format
INTENSITY
Rain Interval
1:00
Data Source
TIMESERIES
Series Name
TS1
As mentioned earlier, we want to simulate the response of our study area to a
3-inch, 6-hour design storm. A time series named TS1 will contain the hourly
rainfall intensities that make up this storm. Thus we need to create a time series
object and populate it with data. To do this:
6
An alternative way to move from one object of a given type to the next in order (or to the previous one)
in the Property Editor is to hit the Page Down (or Page Up) key.
SWMM 5 Quick Start Tutorial
35
1. From the Data Browser select the Time Series category of objects.
2. Click the button on the Browser to bring up the Time Series Editor dialog (see Figure 3-7)7.
3. Enter TS1 in the Time Series Name field.
4. Enter the values shown in Figure 3.7 into the Time and Value columns of the data entry grid (leave the Date column blank8).
5. You can click the View button on the dialog to see a graph of the
time series values. Click the OK button to accept the new time series.
Figure 3-7 Time Series Editor dialog.
Having completed the initial design of our example project it is a good idea
to give it a title and save our work to a file at this point. To do this:
1. Select the Title/Notes category from the Data Browser and click the
button.
2. In the Project Title/Notes dialog that appears (see Figure 3-8), enter
“Tutorial Example” as the title of our project and click the OK button to close the dialog.
3. From the File menu select the Save As option.
4. In the Save As dialog that appears, select a folder and file name under which to save this project. We suggest naming the file
tutorial.inp. (An extension of .inp will be added to the file name if
one is not supplied.)
5. Click Save to save the project to file.
The project data are saved to the file in a readable text format. You can view
what the file looks like by selecting Project >> Details from the main menu. To
7
The Time Series Editor can also be launched directly from the Rain Gage Property Editor - select the
editor's Series Name field and double click on it.
Leaving off the dates for a time series means that SWMM will interpret the time values as hours from
the start of the simulation. Otherwise, the time series follows the date/time values specified by the user.
8
36
SWMM 5 Quick Start Tutorial
open our project at some later time, you would select the Open command from
the File menu.
Figure 3-8 Title/Notes Editor.
3.5 Running A Simulation
Setting Simulation Options
Before analyzing the performance of our example drainage system we need to
set some options that determine how the analysis will be carried out.
Figure 3-9 Simulation Options dialog.
To do this:
1. From the Data Browser, select the Options category and click the
button.
2. On the General page of the Simulation Options dialog that appears
(see Figure 3-9), select Kinematic Wave as the flow routing method. The infiltration method should already be set to Green-Ampt.
The Allow Ponding option should be unchecked.
SWMM 5 Quick Start Tutorial
37
3. On the Dates page of the dialog, set the End Analysis time to
12:00:00.
4. On the Time Steps page, set the Routing Time Step to 60 seconds.
5. Click OK to close the Simulation Options dialog.
Running A Simulation
We are now ready to run the simulation.
To run the simulation, select Project >> Run Simulation (or click the
button). If there was a problem with the simulation, a Status Report will appear
describing what errors occurred. Upon successfully completing a run, there are
numerous ways in which to view the results of the simulation. We will illustrate
just a few here.
Viewing The Status Report
The Status Report contains useful summary information about the results of a
simulation run. To view the report, select Report >> Status. A portion of the
report for the system just analyzed is shown in Figure 3-10.
The full report indicates the following:
• The quality of the simulation is quite good, with negligible mass
balance continuity errors for both runoff and routing (-0.05% and
0.06%, respectively, if all data were entered correctly).
• Of the 3 inches of rain that fell on the study area, 1.75 infiltrated into the ground and essentially the remainder became runoff.
• The Node Flooding Summary table (not shown in Figure 3-10) indicates there was internal flooding in the system at node J29.
• The Conduit Surcharge Summary table (also not shown in Figure 310) shows that Conduit C2, just downstream of node J2, was surcharged and therefore appears to be slightly undersized.
9
In SWMM, flooding will occur whenever the water surface at a node exceeds the maximum defined
depth. Normally such water will be lost from the system. The option also exists to have this water pond
atop the node and be re-introduced into the drainage system when capacity exists to do so.
38
SWMM 5 Quick Start Tutorial
Figure 3-10 Portion of the Status Report for initial simulation run.
SWMM 5 Quick Start Tutorial
39
Viewing Results On The Map
Simulation results (as well as some design parameters, such as subcatchment
area, node invert elevation, and link maximum depth) can be viewed in colorcoded fashion on the study area map. To view a particular variable in this fashion:
Figure 3-11 Example of viewing color-coded results on the Study Area
Map.
1. Select the Map page of the Browser panel.
2. Select the variables to view for Subcatchments, Nodes, and Links
from the dropdown combo boxes appearing in the Themes panel.
In Figure 3-11, subcatchment runoff and link flow have been selected for viewing.
3. The color-coding used for a particular variable is displayed with a
legend on the study area map. To toggle the display of a legend,
select View >> Legends.
4. To move a legend to another location, drag it with the left mouse
button held down.
5. To change the color-coding and the breakpoint values for different colors, select View >> Legends >> Modify and then the
pertinent class of object (or if the legend is already visible, simply right-click on it). To view numerical values for the variables
being displayed on the map, select Tools >> Map Display Options and then select the Annotation page of the Map Options
dialog. Use the check boxes for Subcatchment Values, Node
40
SWMM 5 Quick Start Tutorial
Values, and Link Values to specify what kind of annotation to
add.
6. The Date / Time of Day / Elapsed Time controls on the Map
Browser can be used to move through the simulation results in
time. Figure 3-11 depicts results at 5 hours and 45 minutes into
the simulation.
7. You can use the controls in the Animator panel of the Map
Browser (see Figure 3.11) to animate the map display through
time. For example, pressing the button will run the animation
forward in time.
Viewing A Time Series Plot
To generate a time series plot of a simulation result:
1. Select Report >> Graph >> Time Series or simply click
on the
Standard Toolbar and select Time Series from the pull-down menu
that appears.
2. A Time Series Plot dialog will appear. It is used to select the objects
and variables to be plotted.
Figure 3-12 Time Series Plot dialog.
For our example, the Time Series Plot dialog can be used to graph the flow in
conduits C1 and C2 as follows (refer to Figure 3-12):
1. Select Links as the Object Category.
2. Select Flow as the Variable to plot.
3. Click on conduit C1 (either on the map or in the Data Browser) and
then click in the dialog to add it to the list of links plotted. Do the
same for conduit C2.
4. Press OK to create the plot, which should look like the graph in
Figure 3-13.
SWMM 5 Quick Start Tutorial
41
Figure 3-13 Time Series plot of results from initial simulation run.
After a plot is created you can:
• customize its appearance by selecting Report >> Customize or
right clicking on the plot,
• copy it to the clipboard and paste it into another application by selecting Edit >> Copy To or clicking
on the Standard Toolbar
• print it by selecting File >> Print or File >> Print Preview (use
File >> Page Setup first to set margins, orientation, etc.).
Viewing A Profile Plot
SWMM can generate profile plots showing how water surface depth varies
across a path of connected nodes and links. Let's create such a plot for the conduits connecting junction J1 to the outfall Out1 of our example drainage
system. To do this:
1. Select Report >> Graph >> Profile or simply click
on the
Standard Toolbar.
2. Either enter J1 in the Start Node field of the Profile Plot dialog that
appears (see Figure 3-14) or select it on the map or from the Data
Browser and click the button next to the field.
3. Do the same for node Out1 in the End Node field of the dialog.
4. Click the Find Path button. An ordered list of the links forming a
connected path between the specified Start and End nodes will be
displayed in the Links in Profile box. You can edit the entries in this
box if need be.
5. Click the OK button to create the plot, showing the water surface profile as it exists at the simulation time currently selected in the Map
Browser (see Figure 3-15).
42
SWMM 5 Quick Start Tutorial
Figure 3-14 Profile Plot dialog.
Figure 3-15 Example of a Profile Plot.
As you move through time using the Map Browser or with the Animator control,
the water depth profile on the plot will be updated. Observe how node J2 becomes flooded between hours 2 and 3 of the storm event. A Profile Plot’s
appearance can be customized and it can be copied or printed using the same
procedures as for a Time Series Plot.
Running A Full Dynamic Wave Analysis
In the analysis just run we chose to use the Kinematic Wave method of routing
flows through our drainage system. This is an efficient but simplified approach
that cannot deal with such phenomena as backwater effects, pressurized flow,
flow reversal, and non-dendritic layouts. SWMM also includes a Dynamic Wave
routing procedure that can represent these conditions. This procedure, however,
requires more computation time, due to the need for smaller time steps to maintain numerical stability.
Most of the effects mentioned above would not apply to our example. However we had one conduit, C2, which flowed full and caused its upstream
SWMM 5 Quick Start Tutorial
43
junction to flood. It could be that this pipe is actually being pressurized and
could therefore convey more flow than was computed using Kinematic Wave
routing. We would now like to see what would happen if we apply Dynamic
Wave routing instead.
Figure 3-16 Dynamic Wave simulation options.
To run the analysis with Dynamic Wave routing:
5. From the Data Browser, select the Options category and click the
button.
6. On the General page of the Simulation Options dialog that appears,
select Dynamic Wave as the flow routing method.
7. On the Dynamic Wave page of the dialog, use the settings shown in
Figure 3-1610.
8. Click OK to close the form and select Project >> Run Simulation
(or click the
button) to re-run the analysis.
If you look at the Status Report for this run, you will see that there is no longer
any junction flooding and that the peak flow carried by conduit C2 has been
increased from 3.52 cfs to 4.04 cfs.
3.6 Simulating Water Quality
In the next phase of this tutorial we will add water quality analysis to our example project. SWMM has the ability to analyze the buildup, washoff, transport
10
Normally when running a Dynamic Wave analysis, one would also want to reduce the routing time step
(on the Time Steps page of the dialog). In this example, we will continue to use a 4 minute time step.
44
SWMM 5 Quick Start Tutorial
and treatment of any number of water quality constituents. The steps needed to
accomplish this are:
1. Identify the pollutants to be analyzed.
2. Define the categories of land uses that generate these pollutants.
3. Set the parameters of buildup and washoff functions that determine
the quality of runoff from each land use.
4. Assign a mixture of land uses to each subcatchment area
5. Define pollutant removal functions for nodes within the drainage
system that contain treatment facilities.
We will now apply each of these steps, with the exception of number 5, to our
example project11.
We will define two runoff pollutants; total suspended solids (TSS), measured
as mg/L, and total Lead, measured in µg/L. In addition, we will specify that the
concentration of Lead in runoff is a fixed fraction (0.25) of the TSS concentration. To add these pollutants to our project:
1. Under the Quality category in the Data Browser, select the Pollutants sub-category beneath it.
2. Click the button to add a new pollutant to the project.
3. In the Pollutant Editor dialog that appears (see Figure 3-17), enter
TSS for the pollutant name and leave the other data fields at their
default settings.
4. Click the OK button to close the Editor.
5. Click the button on the Data Browser again to add our next pollutant.
6. In the Pollutant Editor, enter Lead for the pollutant name, select
µg/L for the concentration units, enter TSS as the name of the CoPollutant, and enter 0.25 as the Co-Fraction value.
7. Click the OK button to close the Editor.
In SWMM, pollutants associated with runoff are generated by specific land
uses assigned to subcatchments. In our example, we will define two categories:
Residential and Undeveloped. To add these land uses to the project:
1. Under the Quality category in the Data Browser, select the Land
Uses sub-category and click the button.
2. In the Land Use Editor dialog that appears (see Figure 3-18), enter
Residential in the Name field and then click the OK button.
3. Repeat steps 1 and 2 to create the Undeveloped land use category.
11
Aside from surface runoff, SWMM allows pollutants to be introduced into the nodes of a drainage
system through user-defined time series of direct inflows, dry weather inflows, groundwater interflow,
and rainfall dependent inflow/infiltration.
45
SWMM 5 Quick Start Tutorial
Figure 3-17 Pollutant
Editor dialog.
Figure 3-18 Land Use Editor
dialog.
Next we need to define buildup and washoff functions for TSS in each of our
land use categories. Functions for Lead are not needed since its runoff concentration was defined to be a fixed fraction of the TSS concentration. Normally,
defining these functions requires site-specific calibration.
In this example we will assume that suspended solids in Residential areas
builds up at a constant rate of 1 pound per acre per day until a limit of 50 lbs per
acre is reached. For the Undeveloped area we will assume that buildup is only
half as much. For the washoff function, we will assume a constant event mean
concentration of 100 mg/L for Residential land and 50 mg/L for Undeveloped
land. When runoff occurs, these concentrations will be maintained until the
avaliable buildup is exhausted. To define these functions for the Residential land
use:
1. Select the Residential land use category from the Data Browser and
click the button.
2. In the Land Use Editor dialog, move to the Buildup page (see Figure 3-19).
3. Select TSS as the pollutant and POW (for Power function) as the
function type.
4. Assign the function a maximum buildup of 50, a rate constant of
1.0, a power of 1 and select AREA as the normalizer.
5. Move to the Washoff page of the dialog and select TSS as the pollutant, EMC as the function type, and enter 100 for the coefficient.
Fill the other fields with 0.
46
SWMM 5 Quick Start Tutorial
6. Click the OK button to accept your entries.
Figure 3-19 Defining a TSS buildup function for Residential land use.
Now do the same for the Undeveloped land use category, except use a maximum buildup of 25, a buildup rate constant of 0.5, a buildup power of 1, and a
washoff EMC of 50.
The final step in our water quality example is to assign a mixture of land uses
to each subcatchment area:
1. Select subcatchment S1 into the Property Editor.
2. Select the Land Uses property and click the ellipsis button (or press
<Enter>).
3. In the Land Use Assignment dialog that appears, enter 75 for the %
Residential and 25 for the % Undeveloped (see Figure 3-20). Then
click the OK button to close the dialog.
4. Repeat the same three steps for subcatchment S2.
5. Repeat the same for subcatchment S3, except assign the land uses as
25% Residential and 75% Undeveloped.
SWMM 5 Quick Start Tutorial
47
Figure 3-20 Land Use Assignment dialog.
Before we simulate the runoff quantities of TSS and Lead from our study area, an initial buildup of TSS should be defined so it can be washed off during
our single rainfall event. We can either specify the number of antecedent dry
days prior to the simulation or directly specify the initial buildup mass on each
subcatchment. We will use the former method:
1. From the Options category of the Data Browser, select the Dates
sub-category and click the button.
2. In the Simulation Options dialog that appears, enter 5 into the Antecedent Dry Days field.
3. Leave the other simulation options the same as they were for the
dynamic wave flow routing we just completed.
4. Click the OK button to close the dialog.
5. Now run the simulation by selecting Project >> Run Simulation or
by clicking
on the Standard Toolbar.
When the run is completed, view its Status Report. Note that two new sections have been added for Runoff Quality Continuity and Quality Routing
Continuity. From the Runoff Quality Continuity table we see that there was an
initial buildup of 47.5 lbs of TSS on the study area and an additional 2.2 lbs of
buildup added during the dry periods of the simulation. About 47.9 lbs were
washed off during the rainfall event. The quantity of Lead washed off is a fixed
percentage (25% times 0.001 to convert from mg to µg) of the TSS as was specified.
If you plot the runoff concentration of TSS for subcatchment S1 and S3 together on the same time series graph, as in Figure 3-21, you will see the
difference in concentrations resulting from the different mix of land uses in these two areas. You can also see that the duration over which pollutants are
washed off is much shorter than the duration of the entire runoff hydrograph (i.e.
1 h versus about 6 h). This results from having exhausted the available buildup
of TSS over this period of time.
48
SWMM 5 Quick Start Tutorial
Figure 3-21 TSS concentration of runoff from selected subcatchments.
3.7 Running A Continuous Simulation
As a final exercise in this tutorial we will demonstrate how to run a long-term
continuous simulation using a historical rainfall record and how to perform a
statistical frequency analysis on the results. The rainfall record will come from a
file named sta310301.dat that was included with the example data sets provided
with EPA SWMM. It contains several years of hourly rainfall beginning in January 1998. The data are stored in the National Climatic Data Center's DSI 3240
format, which SWMM can automatically recognize.
To run a continuous simulation with this rainfall record:
1. Select the rain gage Gage1 into the Property Editor.
2. Change the selection of Data Source to FILE.
3. Select the File Name data field and click the ellipsis button (or press
the <Enter> key) to bring up a standard Windows File Selection dialog.
4. Navigate to the folder where the SWMM example files were stored,
select the file named sta310301.dat, and click Open to select the
file and close the dialog.
5. In the Station No. field of the Property Editor enter 310301.
6. Select the Options category in the Data Browser and click the
button to bring up the Simulation Options form.
7. On the General page of the form, select Kinematic Wave as the
Routing Method (this will help speed up the computations).
8. On the Date page of the form, set both the Start Analysis and Start
Reporting dates to 01/01/1998, and set the End Analysis date to
01/01/2000.
9. On the Time Steps page of the form, set the Routing Time Step to
300 seconds.
SWMM 5 Quick Start Tutorial
49
10. Close the Simulation Options form by clicking the OK button and
start the simulation by selecting Project >> Run Simulation (or by
clicking
on the Standard Toolbar).
After our continuous simulation is completed we can perform a statistical frequency analysis on any of the variables produced as output. For example, to
determine the distribution of rainfall volumes within each storm event over the
two-year period simulated:
Figure 3-22 Statistics Selection dialog.
1. Select Report >> Statistics or click the
button on the Standard
Toolbar.
2. In the Statistics Selection dialog that appears, enter the values
shown in Figure 3-22.
3. Click the OK button to close the form.
The results of this request will be a Statistics Report form (see Figure 3-23)
containing four tabbed pages: a Summary page, an Events page containing a
rank-ordered listing of each event, a Histogram page containing a plot of the
occurrence frequency versus event magnitude, and a Frequency Plot page that
plots event magnitude versus cumulative frequency.
The summary page shows that there were a total of 213 rainfall events. The
Events page shows that the largest rainfall event had a volume of 3.35 inches
and occurred over a 24-h period. There were no events that matched the 3-inch,
6-h design storm event used in our previous single-event analysis that had produced some internal flooding. In fact, the status report for this continuous
simulation indicates that there were no flooding or surcharge occurrences over
the simulation period.
50
SWMM 5 Quick Start Tutorial
Figure 3-23 Statistical Analysis report.
We have only touched the surface of SWMM's capabilities. Some additional
features of the program that you will find useful include:
• utilizing additional types of drainage elements, such as storage
units, flow dividers, pumps, and regulators, to model more complex
types of systems
• using control rules to simulate real-time operation of pumps and
regulators
• employing different types of externally-imposed inflows at drainage
system nodes, such as direct time series inflows, dry weather inflows, and rainfall-derived infiltration/inflow
• modeling groundwater interflow\ between aquifers beneath subcatchment areas and drainage system nodes
• modeling snow fall accumulation and melting within subcatchments
• adding calibration data to a project so that simulated results can be
compared with measured values
• utilizing a background street, site plan, or topo map to assist in laying out a system's drainage elements and to help relate simulated
results to real-world locations.
You can find more information on these and other features in later chapters in
this manual.
Chapter 4
PCSWMM Quick Start Tutorial
PCSWMM, first released in 1984 (or as FastSWMM and SWESWMM in 1977),
has been continuously developed with regular updates, and with substantially
upgraded versions being released every other year. With the release of SWMM
5, PCSWMM was completely rewritten to complement and extend the capability
of this entirely new software, in July 2007.
Currently, PCSWMM is being further enhanced because SWMM 5 releases
require changes. This provides greater opportunity to develop additional features
in PCSWMM. At the time of printing this User’s Guide to SWMM 5 (October
2010), updates of PCSWMM with advanced capability are being released every
few weeks.
Because of this rate of development, a quick-start tutorial, set in a book that
is only updated every few years, would quickly become of limited, and diminishing, value. The reader is therefore advised to refer to the Getting Started with
PCSWMM directions, which are regularly updated on the CHI website
http://www.CHIwater.com. These step-by-step instructions can be accessed by
following the URL:
http://CHIwater.com/Support/PCSWMM.NET/gettingstarted.asp
Future editions of the User’s Guide to SWMM 5 will include a basic tutorial
for PCSWMM in this chapter, when it will be of more enduring value.
51
Background 52
Chapter 5
Conceptual Model
This chapter discusses how SWMM models the objects and operational parameters that constitute a stormwater drainage system. Details about how this
information is entered into the program are presented in later chapters. An
overview is also given on the computational methods that SWMM uses to simulate the hydrology, hydraulics and water quality transport behavior of a
drainage system, including a comparison of SWMM 4 and SWMM 5 dynamic
wave routing procedures.
5.1 Introduction
SWMM conceptualizes a drainage system as a series of water and material flows
between several major environmental compartments. These compartments and
the SWMM objects they contain include:
• The Atmosphere compartment, from which precipitation falls and
pollutants are deposited onto the land surface compartment. SWMM
uses Rain Gage objects to represent rainfall inputs to the system.
• The Land Surface compartment, which is represented through one
or more Subcatchment objects. It receives precipitation from the
Atmospheric compartment in the form of rain or snow; it sends outflow in the form of infiltration to the Groundwater compartment and
also as surface runoff and pollutant loadings to the Transport compartment.
• The Groundwater compartment receives infiltration from the Land
Surface compartment and transfers a portion of this inflow to the
Transport compartment. This is modeled using Aquifer objects.
• The Transport compartment contains a network of conveyance elements (channels, pipes, pumps, and regulators) and
storage/treatment units that transport water to outfalls or to treatment facilities. Inflows to this compartment can come from surface
runoff, groundwater interflow, sanitary dry weather flow, or from
user-defined hydrographs. The components of the Transport compartment are modeled with Node and Link objects
Not all compartments need appear in a particular SWMM model. For example, one could model just the transport compartment, using pre-defined
hydrographs as inputs.
53
54
Conceptual Model
5.2 Visual Objects
Figure 5-1 depicts how a collection of SWMM’s visual objects might be arranged together to represent a stormwater drainage system. These objects can be
displayed on a map in the SWMM workspace. The following sections describe
each of these objects.
Figure 5-1 Example of physical objects used to model a drainage system.
5.2.1 Rain Gages
Rain Gages supply precipitation data for one or more subcatchment areas in a
study region. The rainfall data can be either a user-defined time series or come
from an external file. Several different popular rainfall file formats currently in
use are supported, as well as a standard user-defined format.
The principal input properties of rain gages include:
• rainfall data type (e.g., intensity, volume, or cumulative volume)
• recording time interval (e.g., hourly, 15-minute, etc.)
• source of rainfall data (input time series or external file)
• name of rainfall data source
5.2.2 Subcatchments
Subcatchments are hydrologic units of land whose topography and drainage system elements direct surface runoff to a single discharge point. The user is
responsible for dividing a study area into an appropriate number of subcatchments, and for identifying the outlet point of each subcatchment. Discharge
outlet points can be either nodes of the drainage system or other subcatchments.
Subcatchments can be divided into pervious and impervious subareas. Surface runoff can infiltrate into the upper soil zone of the pervious subarea, but not
through the impervious subarea. Impervious areas are themselves divided into
two subareas - one that contains depression storage and another that does not.
Conceptual Model
55
Runoff flow from one subarea in a subcatchment can be routed to the other subarea, or both subareas can drain to the subcatchment outlet.
Infiltration of rainfall from the pervious area of a subcatchment into the unsaturated upper soil zone can be described using three different models:
• Horton infiltration;
• Green-Ampt infiltration; and
• SCS Curve Number infiltration.
To model the accumulation, re-distribution, and melting of precipitation that
falls as snow on a subcatchment, it must be assigned a Snow Pack object. To
model groundwater flow between an aquifer underneath the subcatchment and a
node of the drainage system, the subcatchment must be assigned a set of
Groundwater parameters. Pollutant buildup and washoff from subcatchments are
associated with the Land Uses assigned to the subcatchment. Capture and retention of rainfall/runoff using different types of low impact development practices
(such as bio-retention cells, infiltration trenches, porous pavement, vegetative
swales, and rain barrels) can be modeled by assigning a set of predesigned LID
controls to the subcatchment.
The other principal input parameters for subcatchments include:
• assigned rain gage;
• outlet node or subcatchment;
• assigned land uses;
• tributary surface area;
• imperviousness;
• slope;
• characteristic width of overland flow;
• Manning's n for overland flow on both pervious and impervious areas;
• depression storage in both pervious and impervious areas; and
• percent of impervious area with no depression storage.
5.2.3 Junction Noder
Junctions are drainage system nodes where links join together. Physically they
can represent the confluence of natural surface channels, manholes in a sewer
system, or pipe connection fittings. External inflows can enter the system at
junctions. Excess water at a junction can become partially pressurized while
connecting conduits are surcharged and can either be lost from the system or be
allowed to pond atop the junction and subsequently drain back into the junction.
The principal input parameters for a junction are:
• invert elevation;
• height to ground surface;
• ponded surface area when flooded (optional); and
• external inflow data (optional).
56
Conceptual Model
5.2.4 Outfall Nodes
Outfalls are terminal nodes of the drainage system used to define final downstream boundaries under Dynamic Wave flow routing. For other types of flow
routing they behave as a junction. Only a single link can be connected to an outfall node.
The boundary conditions at an outfall can be described by any one of the following stage relationships:
• the critical or normal flow depth in the connecting conduit;
• a fixed stage elevation;
• a tidal stage described in a table of tide height versus hour of the
day; and
• a user-defined time series of stage versus time.
The principal input parameters for outfalls include:
• invert elevation;
• boundary condition type and stage description; and
• presence of a flap gate to prevent backflow through the outfall.
5.2.5 Flow Divider Nodes
Flow Dividers are drainage system nodes that divert inflows to a specific conduit in a prescribed manner. A flow divider can have no more than two conduit
links on its discharge side. Flow dividers are only active under Kinematic Wave
routing and are treated as simple junctions under Dynamic Wave routing.
There are four types of flow dividers, defined by the manner in which inflows are diverted:
Cutoff Divider: diverts all inflow above a defined cutoff value;
Overflow Divider: diverts all inflow above the flow capacity of the nondiverted conduit;
Tabular Divider: uses a table that expresses diverted flow as a function
of total inflow; and
Weir Divider: uses a weir equation to compute diverted flow.
The flow diverted through a weir divider is computed by the following equation:
Qdiv = C w ( fH w )1.5
where Qdiv = diverted flow, Cw = weir coefficient, Hw = weir height and f is
computed as
f =
Qin − Qmin
Qmax − Qmin
where Qin is the inflow to the divider, Qmin is the flow at which diversion begins,
and Qmax = CwHw1.5. The user-specified parameters for the weir divider are Qmin,
Hw, and Cw.
57
Conceptual Model
The principal input parameters for a flow divider are:
• junction parameters (see above);
• name of the link receiving the diverted flow; and
• method used for computing the amount of diverted flow.
5.2.6 Storage Units
Storage Units are drainage system nodes that provide storage volume. Physically
they could represent storage facilities as small as a catch basin or as large as a
lake. The volumetric properties of a storage unit are described by a function or
table of surface area versus height.
The principal input parameters for storage units include:
• invert elevation;
• maximum depth;
• depth-surface area data;
• evaporation potential;
• ponded surface area when flooded (optional); and
• external inflow data (optional).
5.2.7 Conduits
Conduits are pipes or channels that move water from one node to another in the
conveyance system. Their cross-sectional shapes can be selected from a variety
of standard open and closed geometries as listed in Table 5-1.
Most open channels can be represented with a rectangular, trapezoidal, or user-defined irregular cross-section shape. For the latter, a Transect object is used
to define how depth varies with distance across the cross-section (see Section
5.3.5 below). The most common shapes for new drainage and sewer pipes are
circular, elliptical, and arch pipes. They come in standard sizes that are published by the American Iron and Steel Institute in Modern Sewer Design and by
the American Concrete Pipe Association in the Concrete Pipe Design Manual.
The Filled Circular shape allows the bottom of a circular pipe to be filled with
sediment and thus limit its flow capacity. The Custom Closed Shape allows any
closed geometrical shape that is symmetrical about the center line to be defined
by supplying a Shape Curve for the cross section (see Section 5.3.11 below).
SWMM uses the Manning equation to express the relationship between flow
rate (Q), cross-sectional area (A), hydraulic radius (R), and slope (S) in all conduits. For standard U.S. units,
Q=
1.49
AR 2/3 S 1/2
n
where n is the Manning roughness coefficient. The slope S is interpreted as either the conduit slope or the friction slope (i.e., head loss per unit length),
depending on the flow routing method used.
58
Conceptual Model
Table 5-1 Available cross section shapes for conduits.
Name
Circular
Parameters
Full Height
Shape
Name
Parameters
Circular Force Full Height,
Main
Roughness
Filled Circular Full Height,
Filled Depth
Rectangular Closed
Full Height,
Width
Rectangular –
Open
Full Height,
Width
Trapezoidal
Full Height,
Base Width,
Side Slopes
Triangular
Full Height,
Top Width
Horizontal
Ellipse
Full Height,
Max. Width
Vertical Ellipse Full Height,
Max. Width
Arch
Full Height,
Max. Width
Parabolic
Full Height,
Top Width
Power
Full Height,
Top Width,
Exponent
RectangularTriangular
RectangularRound
Modified Basket-handle
Full Height,
Top Width,
Triangle
Height
Full Height,
Top Width
Egg
Full Height,
Top Width,
Bottom Radius
Full Height
Horseshoe
Full Height
Gothic
Full Height
Catenary
Full Height
Semi-Elliptical Full Height
Basket-handle
Full Height
Semi-Circular
Irregular Natu- Transect
ral Channel
Coord-inates
Full Height
Custom Closed Full Height,
Shape
Shape Curve
Coord-inates
Shape
59
Conceptual Model
For pipes with Circular Force Main cross-sections either the Hazen-Williams
or Darcy-Weisbach formula is used in place of the Manning equation for fully
pressurized flow. For U.S. units the Hazen-Williams formula is:
Q = 1.318 C A R 0.63 S 0.54
where C is the Hazen-Williams C-factor which varies inversely with surface
roughness and is supplied as one of the cross-section’s parameters. The DarcyWeisbach formula is:
Q=
8g
AR 1/2 S 1/2
f
where g is the acceleration of gravity and f is the Darcy-Weisbach friction factor. For turbulent flow, the latter is determined from the height of the roughness
elements on the walls of the pipe (supplied as an input parameter) and the flow’s
Reynolds Number using the Colebrook-White equation. The choice of which
equation to use is a user-supplied option.
A conduit does not have to be assigned a Force Main shape for it to pressurize. Any of the closed cross-section shapes can potentially pressurize
and thus function as force mains that use the Manning equation to compute friction losses.
A conduit can also be designated to act as a culvert if a Culvert Inlet Geometry code number is assigned to it. These code numbers are listed in Table A10 of
Appendix A. Culvert conduits are checked continuously during dynami wave
flow routing to see if they operate under Inlet Control as defined in the Federal
Highway Administration’s publication Hydraulic Design of Highway Culverts
(Publication No. FHWA-NHI-01-020, May 2005). Under inlet control a culvert
obeys a particular flow versus inlet depth rating curve whose shape depends on
the culvert’s shape, size, slope, and inlet geometry.
The principal input parameters for conduits are:
• names of the inlet and outlet nodes;
• offset height or elevation above the inlet and outlet node inverts;
• conduit length;
• Manning's roughness;
• cross-sectional geometry;
• entrance/exit losses (optional); and
• presence of a flap gate to prevent reverse flow (optional).
5.2.8 Pumps
Pumps are links used to lift water to higher elevations. A pump curve describes
the relation between a pump's flow rate and conditions at its inlet and outlet
nodes. Four different types of pump curves are supported:
60
Conceptual Model
Type 1
An off-line pump with a wet
well where flow increases incrementally with available wet
well volume.
Type 2
An in-line pump where flow increases incrementally with inlet
node depth.
Type 3
An in-line pump where flow
varies continuously with head
difference between the inlet
and outlet nodes.
Type 4
A variable speed in-line pump
where flow varies continuously
with inlet node depth.
Ideal
An ideal transfer pump whose flow rate equals the inflow rate at its inlet node.
No curve is required. The pump must be the only outflow link from its inlet
node. Used mainly for preliminary design.
The on/off status of pumps can be controlled dynamically by specifying
startup and shutoff water depths at the inlet node or through user-defined Control Rules. Rules can also be used to simulate variable speed drives that
modulate pump flow.
The principal input parameters for a pump include:
• names of its inlet and outlet nodes;
• name of its pump curve;
• initial on/off status; and
• startup and shutoff depths.
5.2.9 Flow Regulators
Flow Regulators are structures or devices used to control and divert flows within
a conveyance system. They are typically used to:
• control releases from storage facilities;
• prevent unacceptable surcharging; and
61
Conceptual Model
• divert flow to treatment facilities and interceptors.
SWMM can model the following types of flow regulators:
• Orifices;
• Weirs; and
• Outlets.
Orifices
Orifices are used to model outlet and diversion structures in drainage systems,
which are typically openings in the wall of a manhole, storage facility, or control
gate. They are internally represented in SWMM as a link connecting two nodes.
An orifice can have either a circular or rectangular shape, be located either at the
bottom or along the side of the upstream node, and have a flap gate to prevent
backflow.
Orifices can be used as storage unit outlets under all types of flow routing. If
not attached to a storage unit node, they can only be used in drainage networks
that are analyzed with Dynamic Wave flow routing.
The flow through a fully submerged orifice is computed as
Q = CA 2 gh
where Q = flow rate, C = discharge coefficient, A = area of orifice opening, g =
acceleration of gravity, and h = head difference across the orifice. The height of
an orifice's opening can be controlled dynamically through user-defined Control
Rules. This feature can be used to model gate openings and closings.
The principal input parameters for an orifice include:
• names of its inlet and outlet nodes;
• configuration (bottom or side);
• shape (circular or rectangular);
• height or elevation above the inlet node invert;
• discharge coefficient; and
• time to open or close.
Weirs
Weirs, like orifices, are used to model outlet and diversion structures in a drainage system. Weirs are typically located in a manhole, along the side of a
channel, or within a storage unit. They are internally represented in SWMM as a
link connecting two nodes, where the weir itself is placed at the upstream node.
A flap gate can be included to prevent backflow.
Four varieties of weirs are available, each incorporating a different formula
for computing flow across the weir as listed in Table 5-2.
Weirs can be used as storage unit outlets under all types of flow routing. If not
attached to a storage unit, they can only be used in drainage networks that are
analyzed with Dynamic Wave flow routing.
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Conceptual Model
The height of the weir crest above the inlet node invert can be controlled dynamically through user-defined Control Rules. This feature can be used to model
inflatable dams.
The principal input parameters for a weir include:
• names of its inlet and outlet nodes;
• shape and geometry;
• crest height or elevation above the inlet node invert; and
• discharge coefficient.
Table 5-2 Available types of weirs.
Weir Type
Cross Section Shape
Flow Formula
Transverse
Rectangular
C w Lh 3 / 2
Side flow
Rectangular
C w Lh 5 / 3
V-notch
Triangular
C w Sh 5 / 2
Trapezoidal
Trapezoidal
C w Lh 3 / 2 + C ws Sh 5 / 2
Cw = weir discharge coefficient,
L = weir length,
S = side slope of V-notch or trapezoidal weir,
h = head difference across the weir, and
Cws = discharge coefficient through sides of trapezoidal weir.
Outlets
Outlets are flow control devices that are typically used to control outflows from
storage units. They are used to model special head-discharge relationships that
cannot be characterized by pumps, orifices, or weirs. Outlets are internally represented in SWMM as a link connecting two nodes. An outlet can also have a
flap gate that restricts flow to only one direction.
Outlets attached to storage units are active under all types of flow routing. If
not attached to a storage unit, they can only be used in drainage networks analyzed with Dynamic Wave flow routing.
A user-defined rating curve determines an outlet's discharge flow as a function of the head difference across it. Control Rules can be used to dynamically
adjust this flow when certain conditions exist.
The principal input parameters for an outlet include:
• names of its inlet and outlet nodes;
• height or elevation above the inlet node invert; and
• function or table containing its head-discharge relationship.
5.2.10 Map Labels
Map Labels are optional text labels added to SWMM's Study Area Map to help
identify particular objects or regions of the map. The labels can be drawn in any
Windows font, freely edited and be dragged to any position on the map.
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63
5.3 Non-Visual Objects
In addition to physical objects that can be displayed visually on a map, SWMM
utilizes several classes of non-visual data objects to describe additional characteristics and processes within a study area.
5.3.1 Climatology
Temperature
Air temperature data are used when simulating snowfall and snowmelt processes
during runoff calculations. They can also be used to compute daily evaporation
rates. If these processes are not being simulated then temperature data are not
required. Air temperature data can be supplied to SWMM from one of the following sources:
• a user-defined time series of point values (values at intermediate
times are interpolated); and
• an external climate file containing daily minimum and maximum
values (SWMM fits a sinusoidal curve through these values depending on the day of the year).
For user-defined time series, temperatures are in degrees F for US units and
degrees C for metric units. The external climate file can also be used to directly
supply evaporation and wind speed as well.
Evaporation
Evaporation can occur for standing water on subcatchment surfaces, for subsurface water in groundwater aquifers, and for water held in storage units.
Evaporation rates can be stated as:
• a single constant value;
• a set of monthly average values;
• a user-defined time series of daily values;
• values computed from the daily temperatures contained in an external climate file; and
• daily values read directly from an external climate file.
If rates are read directly from a climate file, then a set of monthly pan coefficients should also be supplied to convert the pan evaporation data to free water
surface values. An option is also available to allow evaporation only in periods
with no precipitation.
Wind Speed
Wind speed is an optional climatic variable that is only used for snowmelt calculations. SWMM can use either a set of monthly average speeds or wind speed
data contained in the same climate file used for daily minimum/maximum temperatures.
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Conceptual Model
Snowmelt
Snowmelt parameters are climatic variables that apply across the entire study
area when simulating snowfall and snowmelt. They include:
• the air temperature at which precipitation falls as snow;
• heat exchange properties of the snow surface; and
• study area elevation, latitude, and longitude correction.
Areal Depletion
Areal depletion refers to the tendency of accumulated snow to melt nonuniformly over the surface of a subcatchment. As the melting process proceeds,
the area covered by snow gets reduced. This behavior is described by an Areal
Depletion Curve that plots the fraction of total area that remains snow covered
against the ratio of the actual snow depth to the depth at which there is 100%
snow cover. A typical ADC for a natural area is shown in Figure 5-2. Two such
curves can be supplied to SWMM, one for impervious areas and another for
pervious areas.
Figure 5-2 Areal Depletion curve for a natural area.
5.3.2 Snow Packs
Snow Pack objects contain parameters that characterize the buildup, removal,
and melting of snow over three types of sub-areas within a subcatchment:
• the Plowable snow pack area consists of a user-defined fraction of
the total impervious area and is meant to represent such areas as
streets and parking lots where plowing and snow removal can be
done;
• the Impervious snow pack area covers the remaining impervious area of a subcatchment; and
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65
•
the Pervious snow pack area encompasses the entire pervious area
of a subcatchment.
Each of these three areas is characterized by the following parameters:
• minimum and maximum snow melt coefficients;
• minimum air temperature for snow melt to occur;
• snow depth above which 100% areal coverage occurs;
• initial snow depth; and
• initial and maximum free water content in the pack.
In addition, a set of snow removal parameters can be assigned to the Plowable area. These parameters consist of the depth at which snow removal begins
and the fractions of snow moved onto various other areas.
Subcatchments are assigned a snow pack object through their Snow Pack
property. A single snow pack object can be applied to any number of subcatchments. Assigning a snow pack to a subcatchment simply establishes the melt
parameters and initial snow conditions for that subcatchment. Internally,
SWMM creates a "physical" snow pack for each subcatchment, which tracks
snow accumulation and melting for that particular subcatchment based on its
snow pack parameters, its amount of pervious and impervious area, and the precipitation history it sees.
5.3.3 Aquifers
Aquifers are sub-surface groundwater areas used to model the vertical movement of water infiltrating from the subcatchments that lie above them. They also
permit the infiltration of groundwater into the drainage system, or exfiltration of
surface water from the drainage system, depending on the hydraulic gradient
that exists. The same aquifer object can be shared by several subcatchments.
Aquifers are only required in models that need to explicitly account for the exchange of groundwater with the drainage system or to establish baseflow and
recession curves in natural channels and non-urban systems.
Aquifers are represented using two zones – an unsaturated zone and a saturated zone.
Their behavior is characterized using such parameters as soil porosity, hydraulic conductivity, evapotranspiration depth, bottom elevation, and loss rate to
deep groundwater. In addition, the initial water table elevation and initial moisture content of the unsaturated zone must be supplied.
Aquifers are connected to subcatchments and to drainage system nodes as
defined in a subcatchment's Groundwater Flow property. This property also contains parameters that govern the rate of groundwater flow between the aquifer's
saturated zone and the drainage system node.
5.3.4 Unit Hydrographs
Unit Hydrographs (UHs) estimate rainfall-dependent infiltration/inflow (RDII)
into a sewer system. A UH set contains up to three such hydrographs, one for a
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Conceptual Model
short-term response, one for an intermediate-term response, and one for a longterm response. A UH group can have up to 12 UH sets, one for each month of
the year. Each UH group is considered as a separate object by SWMM, and is
assigned its own unique name along with the name of the rain gage that supplies
rainfall data to it.
Figure 5-3 An RDII unit hydrograph.
Each unit hydrograph, as shown in Figure 5-3, is defined by three parameters:
• R: the fraction of rainfall volume that enters the sewer system;
• T: the time from the onset of rainfall to the peak of the UH in hours;
and
• K: the ratio of time to recession of the UH to the time to peak.
Each unit hydrograph can also have a set of Initial Abstraction (IA) parameters associated with it. These determine how much rainfall is lost to interception
and depression storage before any excess rainfall is generated and transformed
into RDII flow by the hydrograph. The IA parameters consist of:
• a maximum possible depth of IA (inches or mm),
• a recovery rate (inches/day or mm/day) at which stored IA is depleted during dry periods
• an initial depth of stored IA (inches or mm)
To generate RDII into a drainage system node, the node must identify
(through its Inflows property) the UH group and the area of the surrounding
sewershed that contributes RDII flow.
An alternative to using unit hydrographs to define RDII flow is to create
an external RDII interface file, which contains RDII time series data.
5.3.5 Transects
Transects refer to the geometric data that describe how bottom elevation varies
with horizontal distance over the cross section of a natural channel or irregularshaped conduit. Figure 5-4 displays an example transect for a natural channel.
Each transect must be given a unique name. Conduits refer to that name to
represent their shape. A special Transect Editor is available for editing the sta-
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Conceptual Model
tion-elevation data of a transect. SWMM internally converts these data into tables of area, top width, and hydraulic radius versus channel depth. In addition,
as shown in the diagram above, each transect can have a left and right overbank
section whose Manning's roughness can be different from that of the main channel. This feature can provide more realistic estimates of channel conveyance
under high flow conditions.
Figure 5-4 Example of a natural channel transect.
5.3.6 External Inflows
In addition to inflows originating from subcatchment runoff and groundwater,
drainage system nodes can receive three other types of external inflows:
• Direct Inflows - These are user-defined time series of inflows added
directly into a node. They can be used to perform flow and water
quality routing in the absence of any runoff computations (as in a
study area where no subcatchments are defined).
• Dry Weather Inflows - These are continuous inflows that typically
reflect the contribution from sanitary sewage in sewer systems or
base flows in pipes and stream channels. They are represented by an
average inflow rate that can be periodically adjusted on a monthly,
daily, and hourly basis by applying Time Pattern multipliers to this
average value.
• Rainfall-Dependent Infiltration/Inflow (RDII) - These are stormwater flows that enter sanitary or combined sewers due to inflow
from direct connections of downspouts, sump pumps, foundation
drains, etc. as well as infiltration of subsurface water through
cracked pipes, leaky joints, poor manhol connections, etc. RDII can
be computed for a given rainfall record based on set of triangular
unit hydrographs (UH) that determine a short-term, intermediateterm, and long-term inflow response for each time period of rainfall.
Any number of UH sets can be supplied for different sewershed ar-
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Conceptual Model
eas and different months of the year. RDII flows can also be specified in an external RDII interface file.
Direct, Dry Weather, and RDII inflows are properties associated with each
type of drainage system node (junctions, outfalls, flow dividers, and storage
units) and can be specified when nodes are edited. It is also possible to make the
outflows generated from an upstream drainage system be the inflows to a downstream system by using interface files. See Chapter 14 Files Used by SWMM,
section 14.7, for further details.
5.3.7 Control Rules
Control Rules determine how pumps and regulators in the drainage system will
be adjusted over the course of a simulation. Some examples of these rules are:
Simple time-based pump control:
RULE R1
IF SIMULATION TIME > 8
THEN PUMP 12 STATUS = ON
ELSE PUMP 12 STATUS = OFF
Multiple-condition orifice gate control:
RULE R2A
IF NODE 23 DEPTH > 12
AND LINK 165 FLOW > 100
THEN ORIFICE R55 SETTING = 0.5
RULE R2B
IF NODE 23 DEPTH > 12
AND LINK 165 FLOW > 200
THEN ORIFICE R55 SETTING = 1.0
RULE R2C
IF NODE 23 DEPTH <= 12
OR LINK 165 FLOW <= 100
THEN ORIFICE R55 SETTING = 0
Pump station operation:
RULE R3A
IF NODE N1 DEPTH > 5
THEN PUMP N1A STATUS = ON
RULE R3B
IF NODE N1 DEPTH > 7
THEN PUMP N1B STATUS = ON
RULE R3C
IF NODE N1 DEPTH <= 3
THEN PUMP N1A STATUS = OFF
AND PUMP N1B STATUS = OFF
Modulated weir height control:
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69
RULE R4
IF NODE N2 DEPTH >= 0
THEN WEIR W25 SETTING = CURVE C25
Chapter 7 (Section 7.3) describes the control rule format in more detail and
the special Editor used to edit them.
5.3.8 Pollutants
SWMM can simulate the generation, inflow and transport of any number of user-defined pollutants. Required information for each pollutant includes:
• pollutant name;
• concentration units (i.e. mg/L, µg/L, or counts/L);
• concentration in rainfall;
• concentration in groundwater;
• concentration in direct infiltration/inflow;
• concentration in dry weather flow; and
• first-order decay coefficient.
Co-pollutants can also be defined in SWMM. For example, pollutant X can
have a co-pollutant Y, meaning that the runoff concentration of X will have
some fixed fraction of the runoff concentration of Y added to it.
Pollutant buildup and washoff from subcatchment areas are determined by
the land uses assigned to those areas. Input loadings of pollutants to the drainage
system can also originate from external time series inflows as well as from dry
weather inflows.
5.3.9 Land Uses
Land Uses are categories of development activities or land surface characteristics assigned to subcatchments. Examples of land use activities are residential,
commercial, industrial, and undeveloped. Land surface characteristics might
include rooftops, lawns, paved roads, undisturbed soils, etc. Land uses are used
solely to account for spatial variation in pollutant buildup and washoff rates
within subcatchments.
The SWMM user has many options for defining land uses and assigning
them to subcatchment areas. One approach is to assign a mix of land uses for
each subcatchment, which results in all land uses within the subcatchment having the same pervious and impervious characteristics. Another approach is to
create subcatchments that have a single land use classification along with a distinct set of pervious and impervious characteristics that reflects the
classification.
The following processes can be defined for each land use category:
• pollutant buildup;
• pollutant washoff; and
• street cleaning.
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Conceptual Model
Pollutant Buildup
Pollutant buildup that accumulates within a land use category is described (or
normalized) by either a mass per unit of subcatchment area or per unit of curb
length. Mass is expressed in pounds for US units and kilograms for metric units.
The amount of buildup is a function of the number of preceding dry weather
days and can be computed using one of the following functions:
Power Function: Pollutant buildup (B) accumulates proportionally to time (t)
raised to some power, until a maximum limit is achieved,
B = Min(C1 , C 2 t C3 )
where C1 = maximum buildup possible (mass per unit of area or curb
length), C2 = buildup rate constant, and C3 = time exponent.
Exponential Function: Buildup follows an exponential growth curve that approaches a maximum limit asymptotically,
B = C1 (1 − e − C2t )
where C1 = maximum buildup possible (mass per unit of area or curb length)
and C2 = buildup rate constant (1/days).
Saturation Function: Buildup begins at a linear rate that continuously declines
with time until a saturation value is reached,
B=
C1t
C2 + t
where C1 = maximum buildup possible (mass per unit area or curb length) and
C2 =half-saturation constant (days to reach half of the maximum
buildup).
External Time Series: This option allows one to use a Time Series to describe
the rate of buildup per day as a function of time. The values placed in the time
series would have units of mass per unit area (or curb length) per day. One can
also provide a maximum possible buildup (mass per unit area or curb length)
with this option and a scaling factor that multiplies the time series values.
Pollutant Washoff
Pollutant washoff from a given land use category occurs during wet weather
periods and can be described in one of the following ways:
Exponential Washoff: The washoff load (W) in units of mass per hour is proportional to the product of runoff raised to some power and to the amount of
buildup remaining,
W = C1 q C2 B
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71
where C1 = washoff coefficient, C2 = washoff exponent, q = runoff rate per unit
area (inches/h or mm/h), and B = pollutant buildup in mass units. The buildup
here is the total mass (not per area or curb length) and both buildup and washoff
mass units are the same as used to express the pollutant's concentration (milligrams, micrograms, or counts).
Rating Curve Washoff: The rate of washoff W in mass per second is proportional
to the runoff rate raised to some power,
W = C1Q C2
where C1 = washoff coefficient, C2 = washoff exponent, and Q = runoff rate
in user-defined flow units.
Event Mean Concentration: This is a special case of Rating Curve Washoff
where the exponent is 1.0 and the coefficient C1 represents the washoff pollutant
concentration in mass per liter (Note: the conversion between user-defined flow
units used for runoff and liters is handled internally by SWMM).
Note that in each case buildup is continuously depleted as washoff proceeds,
and washoff ceases when there is no more buildup available.
Washoff loads for a given pollutant and land use category can be reduced by
a fixed percentage by specifying a BMP Removal Efficiency that reflects the
effectiveness of any BMP controls associated with the land use. It is also possible to use the Event Mean Concentration option by itself, without having to
model any pollutant buildup at all.
Street Sweeping
Street sweeping can be used on each land use category to periodically reduce the
accumulated buildup of specific pollutants. The parameters that describe street
sweeping include:
• days between sweeping;
• days since the last sweeping at the start of the simulation;
• the fraction of buildup of all pollutants that is available for removal
by sweeping; and
• the fraction of available buildup for each pollutant removed by
sweeping.
Note that these parameters can be different for each land use, and the last parameter can vary also with pollutant.
5.3.10 Treatment
Removal of pollutants from the flow streams entering any drainage system node
is modeled by assigning a set of treatment functions to the node. A treatment
function can be any well-formed mathematical expression involving:
• the pollutant concentration of the mixture of all flow streams entering the node (use the pollutant name to represent a concentration);
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Conceptual Model
•
the removals of other pollutants (use R_ prefixed to the pollutant
name to represent removal); and
• any of the following process variables:
- FLOW for flow rate into node (in user-defined flow units);
- DEPTH for water depth above node invert (ft or m);
- AREA for node surface area (ft2 or m2);
- DT for routing time step (sec); and
- HRT for hydraulic residence time (h).
The result of the treatment function can be either a concentration (denoted by
the letter C) or a fractional removal (denoted by R). For example, a first-order
decay expression for BOD exiting from a storage node might be expressed as:
C = BOD * exp(-0.05*HRT)
or the removal of some trace pollutant that is proportional to the removal of total
suspended solids (TSS) could be expressed as:
R = 0.75 * R_TSS
5.3.11 Curves
Curve objects are used to describe a functional relationship between two quantities. The following types of curves are available in SWMM:
• Storage - describes how the surface area of a Storage Unit node
varies with water depth;
• Shape - describes how the width of a customized cross-sectional
shape varies with height for a Conduit link;
• Diversion - relates diverted outflow to total inflow for a Flow Divider node;
• Tidal - describes how the stage at an Outfall node changes by hour
of the day;
• Pump - relates flow through a Pump link to the depth or volume at
the upstream node or to the head delivered by the pump;
• Rating - relates flow through an Outlet link to the head difference
across the outlet; and
• Control - determines how the control setting of a pump or flow regulator varies as a function of some control variable (such as water
level at a particular node) as specified in a Modulated Control rule.
Each curve must be given a unique name and can be assigned any number of
data pairs.
5.3.12 Time Series
Time Series objects are used to describe how certain object properties vary with
time. Time series can be used to describe:
• temperature data;
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73
• evaporation data;
• rainfall data;
• water stage at outfall nodes;
• external inflow hydrographs at drainage system nodes;
• external inflow pollutographs at drainage system nodes; and
• control settings for pumps and flow regulators.
Each time series must be given a unique name and can be assigned any
number of time-value data pairs. Time can be specified either as hours from the
start of a simulation or as an absolute date and time-of-day. Time series data can
either be entered directly into the program or be accessed from a user-supplied
time series data file.
For rainfall time series, it is only necessary to enter periods with nonzero rainfall amounts. SWMM interprets the rainfall value as a constant value
lasting over the recording interval specified for the rain gage that utilizes the
time series. For all other types of time series, SWMM uses interpolation to estimate values at times that fall in between the recorded values.
For times that fall outside the range of the time series, SWMM will use
a value of 0 for rainfall and external inflow time series, and either the first or last
series value for temperature, evaporation, and water stage time series.
5.3.13 Time Patterns
Time Patterns allow external Dry Weather Flow (DWF) to vary in a periodic
fashion. They consist of a set of adjustment factors applied as multipliers to a
baseline DWF flow rate or pollutant concentration. The different types of time
patterns include:
• Monthly - one multiplier for each month of the year;
• Daily - one multiplier for each day of the week;
• Hourly - one multiplier for each hour from 12 AM to 11 PM; and
• Weekend - hourly multipliers for weekend days.
Each Time Pattern must have a unique name and there is no limit on the
number of patterns that can be created. Each dry weather inflow (either flow or
quality) can have up to four patterns associated with it, one for each type listed
above.
5.3.14 LID Controls
LID Controls are low impact development practices designed to capture surface runoff and provide some combination of detention, infiltration, and
evapotranspiration to it. They are considered as properties of a given subcatchment, similar to how Aquifers and Snow Packs are treated. SWMM can
explicitly model five different generic types of LID controls:
• Bio-retention Cells are depressions that contain vegetation grown in
an engineered soil mixture placed above a gravel drainage bed.
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Conceptual Model
They provide storage, infiltration and evaporation of both direct
rainfall and runoff captured from surrounding areas. Rain gardens,
street planters, and green roofs are all variations of bio-retention
cells.
• Infiltration Trenches are narrow ditches filled with gravel that intercept runoff from upslope impervious areas. They provide storage
volume and additional time for captured runoff to infiltrate the native soil below.
• Continuous Porous Pavement systems are excavated areas filled
with gravel and paved over with a porous concrete or asphalt mix.
Normally all rainfall will immediately pass through the pavement
into the gravel storage layer below it where it can infiltrate at natural rates into the site's native soil. Block Paver systems consist of
impervious paver blocks placed on a sand or pea gravel bed with a
gravel storage layer below. Rainfall is captured in the open spaces
between the blocks and conveyed to the storage zone and native soil
below.
• Rain Barrels (or Cisterns) are containers that collect roof runoff during storm events and can either release or re-use the rainwater
during dry periods.
• Vegetative Swales are channels or depressed areas with sloping
sides covered with grass and other vegetation. They slow down the
conveyance of collected runoff and allow it more time to infiltrate
the native soil beneath it.
Bio-retention cells, infiltration trenches, and porous pavement systems can
all contain optional underdrain systems in their gravel storage beds to convey
captured runoff off of the site rather than letting it all infiltrate. They can also
have an impermeable floor or liner that prevents any infiltration into the native
soil from occurring. Infiltration trenches and porous pavement systems can also
be subjected to a decrease in hydraulic conductivity over time due to clogging.
Although some LID practices can also provide significant pollutant reduction
benefits, at this time SWMM only models their hydrologic performance.
There are two different approaches for placing LID controls within a subcatchment:
• place one or more controls in an existing subcatchment that will
displace an equal amount of non-LID area from the subcatchment;
and
• create a new subcatchment devoted entirely to just a single LID
practice.
The first approach allows a mix of LIDs to be placed into a subcatchment,
each treating a different portion of the runoff generated from the non-LID fraction of the subcatchment. Note that under this option the subcatchment's LIDs
act in parallel -- it is not possible to make them act in series (i.e., have the outflow from one LID control become the inflow to another LID). Also, after LID
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75
placement the subcatchment's Percent Impervious and Width properties may
require adjustment to compensate for the amount of original subcatchment area
that has now been replaced by LIDs (see Figure 5-5 below). For example, suppose that a subcatchment which is 40% impervious has 75% of that area
converted to a porous pavement LID. After the LID is added the subcatchment's
percent imperviousness should be changed to the percent of impervious area
remaining divided by the percent of non-LID area remaining. This works out to
(1 - 0.75)*40 / (100 - 0.75*40) or 14.3 %.
Figure 5-5 Adjustment of subcatchment parameters after LID placement.
5.4 Computational Methods
SWMM is a physically based, discrete-time simulation model. It employs principles of conservation of mass, energy, and momentum wherever appropriate.
This section briefly describes the methods SWMM uses to model stormwater
runoff quantity and quality through the following physical processes:
Surface Runoff
Flow Routing
Infiltration
Surface Ponding
Groundwater
Water Quality Routing
Snow Melt
5.4.1 Surface Runoff
The conceptual view of surface runoff used by SWMM is illustrated in Figure 56 below. Each subcatchment surface is treated as a nonlinear reservoir. Inflow
comes from precipitation and any designated upstream subcatchments. There are
several outflows, including infiltration, evaporation, and surface runoff. The
capacity of this reservoir is the maximum depression storage, which is the max-
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Conceptual Model
imum surface storage provided by ponding, surface wetting, and interception.
Surface runoff per unit area, Q, occurs only when the depth of water in the reservoir exceeds the maximum depression storage, dp, in which case the outflow
is given by Manning's equation. Depth of water over the subcatchment (d in
feet) is continuously updated with time (t in seconds) by solving numerically a
water balance equation over the subcatchment.
Figure 5-6 Conceptual view of surface runoff.
5.4.2 Infiltration
Infiltration is the process of rainfall penetrating the ground surface into the unsaturated soil zone of pervious subcatchments areas. SWMM offers three
choices for modeling infiltration.
Horton’s Equation
This method is based on empirical observations showing that infiltration decreases exponentially from an initial maximum rate to some minimum rate over
the course of a long rainfall event. Input parameters required by this method
include the maximum and minimum infiltration rates, a decay coefficient that
describes how fast the rate decreases over time, and a time it takes a fully saturated soil to completely dry.
Green-Ampt Method
This method for modeling infiltration assumes that a sharp wetting front exists
in the soil column, separating soil with some initial moisture content below from
saturated soil above. The input parameters required are the initial moisture deficit of the soil, the soil's hydraulic conductivity, and the suction head at the
wetting front.
Curve Number Method
This approach is adopted from the NRCS (SCS) Curve Number method for estimating runoff. It assumes that the total infiltration capacity of a soil can be
found from the soil's tabulated Curve Number. During a rain event this capacity
is depleted as a function of cumulative rainfall and remaining capacity. The input parameters for this method are the curve number, the soil's hydraulic
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Conceptual Model
conductivity (used to estimate a minimum separation time for distinct rain
events), and a time it takes a fully saturated soil to completely dry.
SWMM also allows the infiltration recovery rate to be adjusted by a fixed
amount on a monthly basis to account for seasonal variation in such factors as
evaporation rates and groundwater levels. This optional monthly soil recovery
pattern is specified as part of a project's Evaporation data.
5.4.3 Groundwater
Figure 5-7 is a definitional sketch of the two-zone groundwater model that is
used in SWMM. The upper zone is unsaturated with a variable moisture content
of θ. The lower zone is fully saturated and therefore its moisture content is fixed
at the soil porosity φ. The fluxes shown in the figure, expressed as volume per
unit area per unit time, are shown in Table 5-3.
Table 5-3 Fluxes shown in Figure 5-7.
Flux
fI
fEU
fU
fEL
fL
fG
Interpretation
infiltration from the surface
evapotranspiration from the upper zone which is a fixed fraction of the unused surface evaporation
percolation from the upper to lower zone which depends on the upper zone moisture
content q and depth dU
evapotranspiration from the lower zone, which is a function of the depth of the upper
zone dU
percolation from the lower zone to deep groundwater which depends on the lower
zone depth dL
lateral groundwater interflow to the drainage system, which depends on the lower
zone depth dL as well as the depth in the receiving channel or node.
Figure 5-7 Two-zone groundwater model.
After computing the water fluxes that exist during a given time step, a mass balance is written for the change in water volume stored in each zone so that a new
78
Conceptual Model
water table depth and unsaturated zone moisture content can be computed for
the next time step.
5.4.4 Snowmelt
The snowmelt routine in SWMM is a part of the runoff modeling process. It updates the state of the snow packs associated with each subcatchment by
accounting for snow accumulation, snow redistribution by areal depletion and
removal operations, and snow melt via heat budget accounting. Any snowmelt
coming off the pack is treated as an additional rainfall input onto the subcatchment.
At each runoff time step the following computations are made:
1. Air temperature and melt coefficients are updated according to the
calendar date;
2. Any precipitation that falls as snow is added to the snow pack;
3. Any excess snow depth on the plowable area of the pack is redistributed according to the removal parameters established for the
pack;
4. Areal coverages of snow on the impervious and pervious areas of
the pack are reduced according to the Areal Depletion Curves defined for the study area;
5. The amount of snow in the pack that melts to liquid water is found
using:
• a heat budget equation for periods with rainfall, where melt
rate increases with increasing air temperature, wind speed, and
rainfall intensity; and
• a degree-day equation for periods with no rainfall, where melt
rate equals the product of a melt coefficient and the difference
between the air temperature and the pack's base melt temperature;
6. If no melting occurs, the pack temperature is adjusted up or down
based on the product of the difference between current and past air
temperatures and an adjusted melt coefficient. If melting occurs, the
temperature of the pack is increased by the equivalent heat content
of the melted snow, up to the base melt temperature. Any remaining
melt liquid beyond this is available to runoff from the pack; and
7. The available snowmelt is then reduced by the amount of free water
holding capacity remaining in the pack. The remaining melt is treated the same as an additional rainfall input onto the subcatchment.
5.4.5 Flow Routing
Flow routing within a conduit link in SWMM is governed by the conservation of
mass and momentum equations for gradually varied, unsteady flow (i.e., the
Conceptual Model
79
Saint-Venant flow equations). The SWMM user has a choice on the level of sophistication used to solve these equations:
• Steady Flow Routing;
• Kinematic Wave Routing; and
• Dynamic Wave Routing.
Steady Flow Routing
Steady Flow routing represents the simplest type of routing possible (actually no
routing) by assuming that within each computational time step flow is uniform
and steady. Thus it simply translates inflow hydrographs at the upstream end of
the conduit to the downstream end, with no delay or change in shape. The normal flow equation is used to relate flow rate to flow area (or depth).
This type of routing cannot account for channel storage, backwater effects,
entrance/exit losses, flow reversal or pressurized flow. It can only be used with
dendritic conveyance networks, where each node has only a single outflow link
(unless the node is a divider in which case two outflow links are required). This
form of routing is insensitive to the time step employed and is really only appropriate for preliminary analysis using long-term continuous simulations.
Kinematic Wave Routing
This routing method solves the continuity equation along with a simplified form
of the momentum equation in each conduit. The latter requires that the slope of
the water surface equal the slope of the conduit.
The maximum flow that can be conveyed through a conduit is the full normal
flow value. Any flow in excess of this entering the inlet node is either lost from
the system or can pond atop the inlet node and be re-introduced into the conduit
as capacity becomes available.
Kinematic wave routing allows flow and area to vary both spatially and temporally within a conduit. This can result in attenuated and delayed outflow
hydrographs as inflow is routed through the channel. However this form of routing cannot account for backwater effects, entrance/exit losses, flow reversal, or
pressurized flow, and is also restricted to dendritic network layouts. It can usually maintain numerical stability with moderately large time steps, on the order of
5 to 15 minutes. If the aforementioned effects are not expected to be significant
then this alternative can be an accurate and efficient routing method, especially
for long-term simulations.
Dynamic Wave Routing
Dynamic Wave routing solves the complete one-dimensional Saint-Venant flow
equations and therefore produces the most theoretically accurate results. These
equations consist of the continuity and momentum equations for conduits and a
volume continuity equation at nodes.
With this form of routing it is possible to represent pressurized flow when a
closed conduit becomes full, such that flows can exceed the full normal flow
80
Conceptual Model
value. Flooding occurs when the water depth at a node exceeds the maximum
available depth, and the excess flow is either lost from the system or can pond
atop the node and re-enter the drainage system.
Dynamic wave routing can account for channel storage, backwater, entrance/exit losses, flow reversal, and pressurized flow. Because it couples
together the solution for both water levels at nodes and flow in conduits it can be
applied to any general network layout, even those containing multiple downstream diversions and loops. It is the method of choice for systems subjected to
significant backwater effects due to downstream flow restrictions and with flow
regulation via weirs and orifices. This generality comes at a price of having to
use much smaller time steps, on the order of a minute or less (SWMM will automatically reduce the user-defined maximum time step as needed to maintain
numerical stability).
Each of these routing methods employs the Manning equation to relate flow
rate to flow depth and bed (or friction) slope. The one exception is for circular
Force Main shapes, where the Hazen-Williams equation is used instead.
Contrasting SWMM 4 and SWMM 5 Dynamic Wave Routing Procedure
SWMM 4.4 (hereafter referred to as simply SWMM 4) actually contained three
different procedures that could be used for dynamic wave flow routing. The
choice was determined by the value of the ISOL parameter provided by the user
in SWMM 4’s input data file. The Explicit Method (ISOL = 0) is the default and
will be the method referred to below. Chapter 19 Dynamic Wave Routing Quality Assurance discusses this decision in more detail.
Governing Equations
Both the previous SWMM 4 and the current SWMM 5 solve the same form
of the conservation of mass and momentum equations that govern the unsteady
flow of water through a drainage network of channels and pipes. These equations, known as the Saint-Venant equations, can be expressed in the following
form for flow along an individual conduit:
∂A ∂Q
+
=0
∂t ∂x
∂Q ∂ (Q 2 / A)
∂H
+
+ gA
+ gAS f + gAhL = 0
∂t
∂x
∂x
Continuity (5-1)
Momentum (5-2)
where x is distance along the conduit, t is time, A is cross-sectional area, Q is
flow rate, H is the hydraulic head of water in the conduit (elevation head plus
any possible pressure head), Sf is the friction slope (head loss per unit length), hL
is the local energy loss per unit length of conduit, and g is the acceleration of
gravity. Note that for a known cross-sectional geometry, the area A is a known
function of flow depth y which in turn can be obtained from the head H. Thus
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Conceptual Model
the dependent variables in these equations are flow rate Q and head H, which are
functions of distance x and time t.
The friction slope Sf can be expressed in terms of the Manning equation as:
Sf =
n 2V V
k 2R4/3
where n is the Manning roughness coefficient, V is the flow velocity (equal to
the flow rate Q divided by the cross-sectional area A), R is the hydraulic radius
of the flow’s cross-section, and k = 1.49 for US units or 1.0 for metric units. The
local loss term hL can be expressed as:
KV 2
2 gL
where K is a local loss coefficient at location x and L is the conduit length.
To solve equations 5-1 and 5-2 over a single conduit, one needs a set of initial conditions for H and Q at time 0 as well as boundary conditions at x = 0 and
x = L for all times t.
When analyzing a network of conduits, an additional continuity relationship
is needed for the junction nodes that connect two or more conduits together (see
Figure 5-8). In SWMM a continuous water surface is assumed to exist between
the water elevation at the node and in the conduits that enter and leave the node
(with the exception of free fall drops should they occur). The change in hydraulic head H at the node with respect to time can be expressed as:
∂H
∑Q
=
∂t
Astore + ∑ As
(5-3)
where Astore is the surface area of the node itself, ∑As is the surface area contributed by the conduits connected to the node, and ∑Q is the net flow into the
node (inflow – outflow) contributed by all conduits connected to the node as
well as any externally imposed inflows.
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Conceptual Model
Figure 5-8 Node-link representation of a drainage system in SWMM
(Roesner et al, 1992).
Note that the flow depth at the end of a conduit connected to a node can be
computed as the difference between the head at the node and the invert elevation
of the conduit.
General Solution for Conduits
Equations 5-1, 5-2, and 5-3 are solved in SWMM by converting them into an
explicit set of finite difference formulas that compute the flow in each conduit
and head at each node for time t + ∆t as functions of known values at time t. The
equation solved for the flow in each conduit is:
Qt + Δt =
Qt + ΔQgravity + ΔQinertial
1 + ΔQ friction + ΔQlosses
(5-4)
The individual ∆Q terms have been named for the type of force they represent and are given by the following expressions:
ΔQgravity = gA (H 1 − H 2 )Δt / L
ΔQinertial = 2V (A − At ) + V 2 ( A2 − A1 )Δt / L
ΔQ friction =
ΔQlosses =
gn 2 V Δt
k 2R 4/3
∑ K V Δt
i
i
2L
i
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Conceptual Model
where:
A = average cross-sectional flow area in the conduit,
R = average hydraulic radius in the conduit,
V = average flow velocity in the conduit,
Vi
Ki
H1
H2
A1
A2
=
=
=
=
=
=
local flow velocity at location i along the conduit,
local loss coefficient at location i along the conduit,
head at upstream node of conduit,
head at downstream node of conduit,
cross-sectional area at the upstream end of the conduit,
cross-sectional area at the downstream end of the conduit.
The equation solved for the head at each node is:
H t + Δt = H t +
ΔVol
(Astore + ∑ As )t +Δt
(5-5)
where ∆Vol is the net volume flowing through the node over the time step as
given by:
[
]
ΔVol = 0.5 (∑ Q )t + (∑ Q )t + Δt Δt
SWMM 4 solves equations 5-4 and 5-5 using the modified Euler method
(equivalent to a 2nd order Runge-Kutta method). First equation 5-4 is solved for
new flows in each conduit over a half time step ∆t/2 using the heads, areas, and
velocities last computed for time t. The resulting flows are substituted into equation 5-5 to compute heads, using a time step of ∆t/2. Then full-step flows are
found by evaluating equation 5-4 again, this time using the full time step ∆t and
using the heads, areas, and velocities found for the half-step solution. Finally,
new heads for the full time step ∆t are found by solving equation 5-5 once more
with the full-step flows.
SWMM 5 solves equations 5-4 and 5-5 using a method of successive approximations with under relaxation. The procedure goes as follows:
1. A first estimate of flow in each conduit at time t + ∆t is made by
solving equation 5-4 using the heads, areas, and velocities found at
the current time t. Then the same is done for heads by evaluating
equation 5-5 using the flows just computed. These solutions are denoted as Qlast and Hlast.
2. Equation 5-4 is solved once again, using the heads, areas, and velocities that belong to the Qlast and Hlast values just computed. A
relaxation factor Ω is used to combine the new flow estimate Qnew,
with the previous estimate Qlast according to the equation
Q new = (1 − Ω)Q last + ΩQ new
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Conceptual Model
to produce an updated value of Qnew.
3. Equation 5-5 is solved once again for heads, using the flows Qnew.
As with flow, this new solution for head, Hnew, is weighted with Hlast
to produce an updated estimate for heads,
H new = (1 − Ω) H last + ΩH new
4. If Hnew is close enough to Hlast then the process stops with Qnew and
Hnew as the solution for time t + ∆t. Otherwise, Hlast and Qlast are replaced with Hnew and Qnew, respectively, and the process returns to
step 2.
In implementing this procedure, SWMM 5 uses a constant relaxation factor Ω of
0.5, a convergence tolerance of 0.005 feet on nodal heads, and limits the number
of trials to four.
Computation of Average Conduit Conditions
Evaluation of the flow updating equation 5-4 requires values for the average
area ( A ), hydraulic radius ( R ), and velocity ( V ) throughout the conduit in
question. Both SWMM 4 and 5 compute these values using the heads H1 and H2
at either end of the conduit from which corresponding flow depth values y1 and
y2 can be derived. An average depth y is then computed by averaging these
values and is used with the conduit’s cross-section geometry to compute the average area A and hydraulic radius R . The average velocity V is found by
dividing the most current flow value by the average area. SWMM 5 follows
SWMM 4’s practice of limiting this velocity to be no higher than 50 ft/sec in
absolute value, so as not to allow the frictional flow adjustment term in equation
5-4 to become unbounded.
When the conduit has a free-fall discharge into either of its end nodes (meaning that the water elevation in the node is below the invert elevation of the
conduit), the depth at that end of the conduit is set equal to the smaller of the
critical depth and the normal flow depth for the current flow through the conduit.
Computation of Surface Area
The surface area As that conduits contribute to their end nodes is computed the
same way in both SWMM 4 and SWMM 5 and depends on the flow condition
within the conduit. Under normal conditions it equals half the conduit’s length
times the average of the top width at the end- and mid-points of the conduit.
These widths are evaluated before the next updated flow solution is found, using
the flow depths y1, y2, and y discussed previously. If the conduit’s inflow to a
node is in free-fall (i.e., the conduit invert is above the node’s water surface),
then the conduit contributes nothing to the node’s surface area.
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Conceptual Model
For conduits with closed cross-sectional shapes (such as circular pipes) that
are greater than 96 percent full, SWMM 4 utilizes a constant top width equal to
the width when 96 percent full. This prevents the head adjustment term in equation 5-5 from blowing up as the actual top width and corresponding surface area
go to 0 as the conduit approaches being full. This same practice is followed in
SWMM 5Both programs assign a minimum surface area Astoremin to all nodes, including junctions that normally have no storage volume, to prevent equation 5-5
from becoming unbounded. The default value for this minimum area is 12.57 ft2
(i.e. the area of a 4-foot diameter manhole) but can be overridden by a usersupplied value.
Surcharge Conditions
SWMM defines a node to be in a surcharged condition when its water level exceeds the crown of the highest conduit connected to it. Under this condition the
surface area contributed by any closed conduits would be zero and equation 5-3
would no longer be applicable. To accommodate this situation, SWMM uses an
alternative nodal continuity condition, namely that the total rate of outflow from
a surcharged node must equal the total rate of inflow, ΣQ = 0. By itself, this
equation is insufficient to update nodal heads at the new time step since it only
contains flows. In addition, because the flow and head updating equations for
the system are not solved simultaneously, there is no guarantee that the condition will hold at the surcharged nodes after a flow solution has been reached.
To enforce the flow continuity condition, it can be expressed in the form of a
perturbation equation:
∂Q
⎡
⎤
∑ ⎢⎣Q + ∂H ΔH ⎥⎦ = 0
where ∆H is the adjustment to the node’s head that must be made to achieve
flow continuity. Solving for ∆H yields:
ΔH =
− ∑Q
∑ ∂Q / ∂H
(5-6)
where from equation 5-4,
∂Q
− g AΔt / L
=
∂H 1 + ΔQ friction + ΔQlosses
( ∂Q ∂H has a negative sign in front of it because when evaluating ΣQ, flow
directed out of a node is considered negative while flow into the node is positive.)
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Conceptual Model
Every time that equation 5-6 is applied to update the head at a surcharged
node, equation 5-4 is re-evaluated to provide flow updates for the conduits that
connect to the node. This process continues until some convergence criterion is
met. SWMM 4 enters this iterative mode for surcharged nodes at both the halfstep and full-step portions of its solution method. The user sets a convergence
tolerance on the maximum fractional difference for flows found between iterations as well as the maximum number of iterations allowed. For SWMM 5, these
surcharge iterations are folded into its normal set of iterations outlined previously. That is, whenever heads need to be computed in the successive
approximation scheme, equation 5-6 is used in place of equation 5-5 if a node is
surcharged, and no under-relaxation of the resulting head value is performed.
Normal Flow Condition
Both SWMM 4 and SWMM 5 limit the flow in non-surcharged conduits to be
no greater than the normal Manning’s flow for the current flow depth at the upstream end of the conduit whenever one of the following conditions occur:
1. The water surface slope is less than the conduit slope; or
2. The Froude number, based on the water depth at either end of the
conduit, is greater than 1.0.
Each condition indicates a flow regime that is supercritical. The user specifies which of these two criteria should apply.
Pumps, Orifices, and Weirs
Both programs model pumps, orifices, and weirs as links that connect a pair of
nodes together. The flow through these links is computed as a function of the
heads at their end nodes. These flows are computed during the flow evaluation
step of both the SWMM 4 and 5 procedures after the flows through all of the
conduits are computed.
SWMM 4 and 5 model pumps in a similar fashion, requiring the user to specify a pump curve along which the pump must operate. The pump curve can
specify flow as a function of inlet node volume, inlet node depth, or the head
difference between the inlet and outlet nodes. Both programs also limit the
pump’s flow to the inflow to the inlet node during a given time step should the
pump curve flow be high enough to completely drain the inlet node during the
time step.
SWMM 4 models an orifice (i.e., an enclosed opening oriented either vertically or horizontally to the flow direction) as an equivalent pipe. The length L of
the equivalent pipe is computed as
2Δt gD
where D is the height of the orifice opening. Its roughness coefficient is set
equal to
R 2 / 3 C d 2 Lg
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Conceptual Model
where R is the hydraulic radius of the full orifice opening and Cd is the discharge
coefficient of the orifice. Flow through the orifice is then computed in the same
fashion as for any conduit. SWMM 5 takes a more direct approach. It uses the
classical orifice equation
C d A 2 gh
to compute flow when the orifice is fully submerged and a modified weir equation
C d A 2 gD f 1.5
when the orifice is submerged a fraction f. In these formulas, A is the area and D
is the height of the full orifice opening, while h is the head across the orifice.
Both programs compute a surface area contribution of the orifice to its end
nodes, based on the equivalent pipe length L and the depth of water in the orifice.
SWMM 5 models weirs (i.e. an unrestricted opening oriented either transversely or parallel to the flow direction) in the same fashion as SWMM 4. An
equation of the general form
C w Lw h n
is used to compute flow as a function of head h across the weir when the weir is
not fully submerged. Cw is the weir’s discharge coefficient, Lw is the length of its
opening, and n is an exponent that depends on the type of weir being modeled
(e.g. transverse, side-flow, V-notch, or trapezoidal). When the weir becomes
completely submerged, both programs switch to using the orifice equation to
predict flow as a function of the head across it. Weirs do not contribute any surface area to their end nodes.
5.4.6 Surface Ponding
Normally in flow routing, when the flow into a junction exceeds the capacity of
the system to transport it further downstream, the excess volume overflows the
system and is lost. An option exists to have instead the excess volume be stored
atop the junction, in a ponded fashion, and be reintroduced into the system as
capacity permits. Under Steady and Kinematic Wave flow routing, the ponded
water is stored simply as an excess volume. For Dynamic Wave routing, which
is influenced by the water depths maintained at nodes, the excess volume is assumed to pond over the node with a constant surface area. This amount of
surface area is an input parameter supplied for the junction.
Alternatively, the user may wish to represent the surface overflow system
explicitly. In open channel systems this can include road overflows at bridges or
culvert crossings as well as additional floodplain storage areas. In closed conduit
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Conceptual Model
systems, surface overflows may be conveyed down streets, alleys, or other surface routes to the next available stormwater inlet or open channel. Overflows
may also be impounded in surface depressions such as parking lots, back yards,
or other areas.
5.4.7 Water Quality Routing
Water quality routing within conduit links assumes that the conduit behaves as a
continuously stirred tank reactor (CSTR). Although a plug flow reactor assumption might be more realistic, the differences will be small if the travel time
through the conduit is on the same order as the routing time step. The concentration of a constituent exiting the conduit at the end of a time step is found by
integrating the conservation of mass equation, using average values for quantities that might change over the time step such as flow rate and conduit volume.
Water quality modeling within storage unit nodes follows the same approach
used for conduits. For other types of nodes that have no volume, the quality of
water exiting the node is simply the mixture concentration of all water entering
the node.
5.4.8 LID Representation
LID controls are represented by a combination of vertical layers whose properties are defined on a per-unit-area basis. This allows LIDs of the same design
but differing areal coverage to easily be placed within different subcatchments
of a study area. During a simulation SWMM performs a moisture balance that
keeps track of how much water moves between and is stored within each LID
layer. As an example, the layers used to model a bio-retention cell and the flow
pathways between them are shown in Figure 3-8. The various possible layers
consist of the following:
• the Surface Layer corresponds to the ground (or pavement) surface
that receives direct rainfall and runon from upstream land areas,
stores excess inflow in depression storage, and generates surface
outflow that either enters the drainage system or flows onto downstream land areas;
• the Pavement Layer is the layer of porous concrete or asphalt used
in continuous porous pavement systems, or is the paver blocks and
filler material used in modular systems;
• the Soil Layer is the engineered soil mixture used in bio-retention
cells to support vegetative growth;
• the Storage Layer is a bed of crushed rock or gravel that provides
storage in bio-retention cells, porous pavement, and intfiltration
trench systems. For a rain barrel it is simply the barrel itself; and
• the Underdrain System conveys water out of the gravel storage layer
of bio-retention cells, porous pavement systems, and infiltration
trenches (typically with slotted pipes) into a common outlet pipe or
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Conceptual Model
chamber. For rain barrels it is simply the drain valve at the bottom
of the barrel.
Table 5-4 indicates which combination of layers applies to each type of LID
(x means required, o means optional).
Table 5-4 Layers used to model different types of LID units.
LID Type
Bio-Retention Cell
Porous Pavement
Infiltration Trench
Rain Barrel
Vegetative Swale
Surface
x
x
x
Pavement
x
Soil
x
Storage
x
x
x
x
Underdrain
o
o
o
x
x
All of the LID controls provide some amount of rainfall/runoff storage and
evaporation of stored water (except for rain barrels). Infiltration into native soil
occurs in vegetative swales and can also occur in bio-retention cells, porous
pavement systems, and infiltration trenches if those systems do not employ an
optional impermeable bottom liner. Infiltration trenches and porous pavement
systems can also be subjected to clogging. This reduces their hydraulic conductivity over time proportional to the cumulative hydraulic loading on the trench or
pavement.
The performance of the LID controls placed in a subcatchment is reflected in
the overall runoff, infiltration, and evaporation rates computed for the subcatchment as normally reported by SWMM. SWMM’s Status Report also
contains a section entitled LID Performance Summary that provides an overall
water balance for each LID control placed in each subcatchment. The components of this water balance include total inflow, infiltration, evpaoration, surface
runoff, underdrain flow and initial and final stored volumes, all expressed as
inches (or mm) over the LID’s area. Optionally, the entire time series of flux
rates and moisture levels for a selected LID control in a given subcatchment can
be written to a tab delimited text file for easy viewing and graphing in a spreadsheet program (such as Microsoft Excel).
90
Conceptual Model
Chapter 6
Main Window
This chapter discusses the essential features of SWMM’s workspace. It describes
the main menu bar, the tool and status bars, and the three windows used most
often – the Study Area Map, the Browser, and the Property Editor. It also shows
how to set program preferences.
6.1 Overview
The EPA SWMM main window is pictured below. It consists of the following
user interface elements: a Main Menu, several Toolbars, a Status Bar, the Study
Area Map window, a Browser panel, and a Property Editor window. A description of each of these elements is provided in the sections that follow.
91
92
Main Window
6.2 Main Menu
The Main Menu located across the top of the EPA SWMM main window contains a collection of menus used to control the program. These include:
• File Menu
• Edit Menu
• View Menu
• Project Menu
• Report Menu
• Tools Menu
• Window Menu
• Help Menu
File Menu
The File Menu contains commands for opening and saving data files and for
printing:
Command
Description
New
Creates a new SWMM project
Open
Opens an existing project
Reopen
Reopens a recently used project
Save
Saves the current project
Save As
Saves the current project under a different name
Export
Exports study area map to a file in a variety of formats;
Exports current results to a Hot Start file
Combine
Combines two Routing Interface files together
Page
Setup
Sets page margins and orientation for printing
Print
Preview
Previews a printout of the currently active view (map, report, graph, or
table)
Print
Prints the current view
Exit
Exits EPA SWMM
93
Main Window
Edit Menu
The Edit Menu contains commands for editing and copying:
Command
Description
Copy To
Copies the currently active view (map, report, graph or table) to
the clipboard or to a file
Select Object
Enables the user to select an object on the map
Select Vertex
Enables the user to select the vertex of a subcatchment or link
Select Region
Enables the user to delineate a region on the map for selecting
multiple objects
Select All
Selects all objects when the map is the active window or all cells
of a table when a tabular report is the active window
Find Object
Locates a specific object by name on the map
Find Text
Locates specific text in a Status Report
Group Edit
Edits a property for the group of objects that fall within the outlined region of the map
Group Delete
Deletes a group of objects that fall within the outlined region of
the map
View Menu
The View Menu contains commands for viewing the Study Area Map:
Command
Description
Dimensions
Sets reference coordinates and distance units for the study area
map
Backdrop
Allows a backdrop image to be added, positioned, and viewed
Pan
Pans across the map
Zoom In
Zooms in on the map
Zoom Out
Zooms out on the map
Full Extent
Redraws the map at full extent
Query
Highlights objects on the map that meet specific criteria
Overview
Toggles the display of the Overview Map
Objects
Toggles display of classes of objects on the map
Legends
Controls display of the map legends
Toolbars
Toggles display of tool bars
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Main Window
Project Menu
The Project menu contains commands related to the current project being analyzed:
Command
Description
Summary
Lists the number of each type of object in the project
Details
Shows a detailed listing of all project data
Defaults
Edits a project’s default properties
Calibration Data
Registers files containing calibration data with the project
Run Simulation
Runs a simulation
Report Menu
The Report menu contains commands used to report analysis results in different
formats:
Command
Description
Status
Displays a status report for the most recent simulation run
Graph
Displays simulation results in graphical form
Table
Displays simulation results in tabular form
Statistics
Displays a statistical analysis of simulation results
Customize
Customizes the display style of the currently active graph
Tools Menu
The Tools menu contains commands used to configure program preferences,
study area map display options, and external add-in tools:
Command
Description
Program Preferences
Sets program preferences, such as font size, confirm deletions,
number of decimal places displayed, etc.
Map Display Options
Sets appearance options for the Map, such as object size,
annotation, flow direction arrows, and back-ground color
Configure Tools
Adds, deletes, or modifies add-in tools
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Main Window
Window Menu
The Window Menu contains commands for arranging and selecting windows
within the SWMM workspace:
Command
Description
Cascade
Arranges windows in cascaded style, with the study area map
filling the entire display area
Tile
Minimizes the study area map and tiles the remaining windows vertically in the display area
Close All
Closes all open windows except for the study area map
Window List
Lists all open windows; the currently selected window has the
focus and is denoted with a check mark
Help Menu
The Help Menu contains commands for getting help in using EPA SWMM:
Command
Description
Help Topics
Displays the Help system's Table of Contents
How Do I
Displays a list of topics covering the most common operations
Measurement Units
Shows measurement units for all of SWMM’s parameters
Error Messages
Lists the meaning of all error messages
Tutorial
Presents a short tutorial introducing the user to EPA SWMM
About
Lists information about the version of EPA SWMM being
used
6.3 Toolbars
Toolbars provide shortcuts to commonly used operations. There are three such
toolbars:
• Standard Toolbar
• Map Toolbar
• Object Toolbar
All toolbars can be docked underneath the Main Menu bar, docked on the
right side of the Browser Panel or dragged to any location on the EPA SWMM
workspace. When undocked, they can also be re-sized.
Toolbars can be made visible or invisible by selecting View >> Toolbars from
the Main Menu.
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Main Window
Standard Toolbar
The Standard Toolbar contains buttons for the following commonly used commands:
Creates a new project (File >> New)
Opens an existing project (File >> Open)
Saves the current project (File >> Save)
Prints the currently active window (File >> Print)
Copies selection to the clipboard or to a file (Edit >> Copy To)
Finds a specific object on the Study Area Map (Edit >> Find Object) or specific text in the Status Report (Edit >> Find Text)
Runs a simulation (Project >> Run Simulation)
Makes a visual query of the study area map (View >> Query)
Creates a new profile plot of simulation results (Report >> Graph >> Profile)
Creates a new time series plot of simulation results (Report >> Graph >> Time
Series)
Creates a new scatter plot of simulation results (Report >> Graph >> Scatter)
Creates a new table of simulation results (Report >> Table)
Performs a statistical analysis of simulation results (Report >> Statistics)
Modifies display options for the currently active view (Tools >> Map Display
Options or Report >> Customize)
Arranges windows in cascaded style, with the study area map filling the entire
display area (Window >> Cascade)
Main Window
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Map Toolbar
The Map Toolbar contains the following buttons for viewing the study area map:
Selects an object on the map (Edit >> Select Object)
Selects link or subcatchment vertex points (Edit >> Select Vertex)
Selects a region on the map (Edit >> Select Region)
Pans across the map (View >> Pan)
Zooms in on the map (View >> Zoom In)
Zooms out on the map (View >> Zoom Out)
Draws map at full extent (View >> Full Extent)
Measures a length or area on the map
Object Toolbar
The Object Toolbar contains buttons for adding objects to the study area map:
Adds a rain gage to the map
Adds a subcatchment to the map
Adds a junction node to the map
Adds an outfall node to the map
Adds a flow divider node to the map
Adds a storage unit node to the map
Adds a conduit link to the map
Adds a pump link to the map
Adds an orifice link to the map
Adds a weir link to the map
Adds an outlet link to the map
Adds a label to the map
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Main Window
6.4 Status Bar
The Status Bar appears at the bottom of SWMM's Main Window and is divided
into six sections:
Auto-Length
Indicates whether the automatic computation of conduit lengths and subcatchment areas is turned on or off. The setting can be changed by clicking the drop
down arrow.
Offsets
Indicates whether the positions of links above the invert of their connecting
nodes are expressed as a Depth above the node invert or as the Elevation of the
offset. Click the drop down arrow to change this option. If changed, a dialog box
will appear asking if all existing offsets in the current project should be changed
or not (i.e., convert Depth offsets to Elevation offsets or Elevation offsets to
Depth offsets, depending on the option selected)
Flow Units
Displays the current flow units that are in effect. Click the drop down arrow to
change the choice of flow units. Selecting a US flow unit means that all other
quantities will be expressed in US units, while choosing a metric flow unit will
force all quantities to be expressed in metric units. The units of previously entered data are not automatically adjusted if the unit system is changed.
Run Status
A faucet icon shows:
• no running water if simulation results are not available,
• running water when simulation results are available,
• a broken faucet when simulation results are available but may be
invalid because project data have been modified.
Zoom Level
Displays the current zoom level for the map (100% is full-scale).
XY Location
Displays the map coordinates of the current position of the mouse pointer.
Main Window
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6.5 Study Area Map
The Study Area Map (shown below) provides a planar schematic diagram of the
objects comprising a drainage system. Its pertinent features are as follows:
•
•
•
•
•
•
•
The location of objects and the distances between them do not necessarily have to conform to their actual physical scale.
Selected properties of these objects, such as water quality at nodes
or flow velocity in links, can be displayed by using different colors.
The color-coding is described in a Legend, which can be edited.
New objects can be directly added to the map and existing objects
can be selected for editing, deleting, and repositioning.
A backdrop drawing (such as a street or topographic map) can be
placed behind the network map for reference.
The map can be zoomed to any scale and panned from one position
to another.
Nodes and links can be drawn at different sizes, flow direction arrows added, and object symbols, ID labels and numerical property
values displayed.
The map can be printed, copied onto the Windows clipboard, or exported as a DXF file or Windows metafile.
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Main Window
6.6 Data Browser
The Data Browser panel (shown below) appears when the Data tab on the left
panel of the SWMM workspace is selected. It provides access to all of the data
objects in a project. The vertical sizes of the list boxes in the browser can be
adjusted by using the splitter bar located just below the upper list box. The width
of the Data Browser panel can be adjusted by using the splitter bar located along
its right edge.
The upper list box displays the various categories of
data objects available to a SWMM project. The
lower list box lists the name of each individual object of the currently selected data category.
The buttons between the two list boxes of the Data
Browser are used as follows:
adds a new object
deletes the selected object
edits the selected object
moves the selected object up one position
moves the selected object down one position
sorts the objects in ascending order
Selections made in the Data Browser are coordinated with objects highlighted on the Study Area Map,
and vice versa. For example, selecting a conduit in
the Data Browser will cause that conduit to be highlighted on the map, while selecting it on the map
will cause it to become the selected object in the
Data Browser.
6.7 Map Browser
The Map Browser panel (shown below) appears when the Map tab on the left
panel of the SWMM workspace is selected. It controls the mapping themes and
time periods viewed on the Study Area Map. The width of the Map Browser
panel can be adjusted by using the splitter bar located along its right edge.
Main Window
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The Map Browser consists of the following three panels
that control what results are displayed on the map:
The Themes panel selects a set of variables to view in color-coded fashion on the Map.
The Time Period panel selects which time period of the
simulation results are viewed on the Map.
The Animator panel controls the animated display of the
Study Area Map and all Profile Plots over time.
The width of the Map Browser panel can be adjusted by
using the splitter bar located along its right edge.
The Themes panel of the Map Browser is used to select a thematic variable to
view in color-coded fashion on the Study Area Map.
Subcatchments - selects the theme to display for the subcatchment areas shown on the Map.
Nodes - selects the theme to display for the drainage system nodes shown on the Map.
Links - selects the theme to display for the drainage system
links shown on the Map.
The Time Period panel of the Map Browser allows is used to select a time period in which to view computed results in thematic fashion on the Study Area
Map.
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Main Window
Date - selects the day for which simulation results will
be viewed.
Time of Day - selects the hour of the current day for
which simulation results will be viewed.
Elapsed Time - selects the elapsed time from the start of
the simulation for which results will be viewed.
The Animator panel of the Map Browser contains controls for animating the
Study Area Map and all Profile Plots through time i.e., updating map colorcoding and hydraulic grade line profile depths as the simulation time clock is
automatically moved forward or back. The meaning of the control buttons are as
follows:
Returns to the starting period.
Starts animating backwards in time
Stops the animation
Starts animating forwards in time
The slider bar is used to adjust the animation speed.
Main Window
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6.8 Property Editor
The Property Editor is used to edit the properties of data objects that can appear
on the Study Area Map. It is invoked when one of these objects is selected (either on the Study Area Map or in the Data Browser) and double-clicked or when
the Data Browser's Edit button is clicked.
Key features of the Property Editor include:
• The Editor is a grid with two columns - one for the property's name
and the other for its value.
• The columns can be re-sized by re-sizing the header at the top of the
Editor with the mouse.
• A hint area is displayed at the bottom of the Editor with an expanded description of the property being edited. The size of this area can
be adjusted by dragging the splitter bar located just above it.
• The Editor window can be moved and re-sized via the normal Windows operations.
• Depending on the property, the value field can be one of the following:
• a text box in which you enter a value
• a dropdown combo box from which you select a value from a list of
choices
• a dropdown combo box in which you can enter a value or select
from a list of choices
• an ellipsis button which you click to bring up a specialized editor.
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•
•
•
•
•
Main Window
The property field in the Editor that currently has the focus will be
highlighted with a white background.
Both the mouse and the Up and Down arrow keys on the keyboard
can be used to move between property fields.
To begin editing the property with the focus, either begin typing a
value or hit the Enter key.
To have the program accept edits made in a property field, either
press the Enter key or move to another property. To cancel the edits,
press the Esc key.
The Property Editor can be hidden by clicking the button in the upper right corner of its title bar.
6.9 Setting Program Preferences
Program preferences allow one to customize certain program features. To set
program preferences, select Program Preferences from the Tools menu. A Preferences dialog form will appear containing two tabbed pages – one for General
Preferences and one for Number Formats.
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Main Window
General Preferences
The following preferences can be set on the General Preferences page of the
Preferences dialog:
Preference
Description
Bold Fonts
Check to use bold fonts in all windows
Large Fonts
Check to use large size fonts in all windows
Blinking Map Highlighter
Check to make the selected object on the study area map
blink on and off
Flyover Map Labeling
Check to display the ID label and current theme value in
a hint-style box whenever the mouse is placed over an
object on the study area map
Confirm Deletions
Check to display a confirmation dialog box before deleting any object
Automatic Backup File
Check to save a backup copy of a newly opened project
to disk named with a .bak extension
Report Elapsed Time by
Default
Check to use elapsed time (rather than date/time) as the
default for time series graphs and tables.
Prompt to Save Results
If left unchecked then simulation results are automatically saved to disk when the current project is closed.
Otherwise the user will be asked if results should be
saved.
Clear File List
Check to clear the list of most recently used files that
appears when File >> Reopen is selected from the Main
Menu
Temporary Directory
Name of the directory (folder) where EPA SWMM
writes its temporary files
The Temporary Directory must be a file directory (folder) where the
user has write privileges and must have sufficient space to temporarily
store files which can easily grow to several tens of megabytes for larger
study areas and simulation runs. The original default is the folder where
Windows writes its temporary files.
Number Format Preferences
The Number Formats page of the Preferences dialog controls the number of decimal places displayed when simulation results are reported. Use the dropdown
list boxes to select a specific Subcatchment, Node or Link parameter, and then
use the edit boxes next to them to select the number of decimal places to use
when displaying computed results for the parameter. Note that the number of
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Main Window
decimal places displayed for any particular input design parameter, such as
slope, diameter, length, etc. is whatever the user enters.
Chapter 7
Property Editors
7.1 Aquifer Editor
The Aquifer Editor is invoked whenever a new aquifer object is created or an
existing aquifer object is selected for editing. It contains the following data
fields.
Name
User-assigned aquifer name.
Porosity
Volume of voids / total soil volume (volumetric fraction).
Wilting Point
Soil moisture content at which plants cannot survive (volumetric fraction).
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Property Editors
Field Capacity
Soil moisture content after all free water has drained off (volumetric fraction).
Conductivity
Soil's saturated hydraulic conductivity (in/hr or mm/hr).
Conductivity Slope
Average slope of log (conductivity) versus soil moisture deficit (porosity minus
moisture content) curve (unitless).
Tension Slope
Average slope of soil tension versus soil moisture content curve (inches or mm).
Upper Evaporation Fraction
Fraction of total evaporation available for evapotranspiration in the upper unsaturated zone.
Lower Evaporation Depth
Maximum depth into the lower saturated zone over which evapotranspiration
can occur (ft or m).
Lower Groundwater Loss Rate
Rate of percolation from saturated zone to deep groundwater (in/hr or mm/hr).
Bottom Elevation
Elevation of the bottom of the aquifer (ft or m).
Water Table Elevation
Elevation of the water table in the aquifer at the start of the simulation (ft or m).
Unsaturated Zone Moisture
Moisture content of the unsaturated upper zone of the aquifer at the start of the
simulation (volumetric fraction) (cannot exceed soil porosity).
7.2 Climatology Editor
The Climatology Editor is used to enter values for various climate-related variables required by certain SWMM simulations. The dialog is divided into five
tabbed pages, where each page provides a separate editor for a specific category
of climate data.
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Temperature Page
The Temperature page of the Climatology Editor dialog is used to specify the
source of temperature data used for snowmelt computations. It is also used to
select a climate file as a possible source for evaporation rates. There are three
choices available.
No Data
Select this choice if snowmelt is not being simulated and evaporation
rates are not based on data in a climate file.
Time Series
Select this choice if the variation in temperature over the simulation period will
be described by one of the project's time series. Also enter (or select) the name
of the time series. Click the button to make the Time Series Editor appear for
the selected time series.
External Climate File
Select this choice if min/max daily temperatures will be read from an external
climate file. Also enter the name of the file (or click the button to search for
the file). If you want to start reading the climate file at a particular date in time
that is different than the start date of the simulation (as specified in the Simulation Options), check off the “Start Reading File at” box and enter a starting date
(month/day/year) in the date entry field next to it. Use this choice if you want
daily evaporation rates to be estimated from daily temperatures or be read directly from the file.
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Property Editors
Evaporation Page
The Evaporation page of the Climatology Editor dialog is used to supply evaporation rates, in inches/day (or mm/day), for a study area. There are five choices
for specifying these rates:
Constant
Use this choice if evaporation remains constant over time. Enter the value in the
edit box provided.
Time Series
Select this choice if evaporation rates will be specified in a time series. Enter or
select the name of the time series in the dropdown combo box provided. Click
the button to bring up the Time Series editor for the selected series. Note that
for each date specified in the time series, the evaporation rate remains constant
at the value supplied for that date until the next date in the series is reached (i.e.,
interpolation is not used on the series).
Directly From Climate File
This choice indicates that daily evaporation rates will be read from the same
climate file that was specified for temperature. Enter values for monthly pan
coefficients in the data grid provided.
Computed from Temperatures
Hargreaves’ method will be used to compute daily evaporation rates from the
daily air temperature record contained in the external climate file specified on
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the Temperature page of the dialog. This method also uses the site’s latitude,
which can be entered on the Snowmelt page of the dialog even if snow melt is
not being simulated.
Monthly Averages
Use this choice to supply an average rate for each month of the year. Enter the
value for each month in the data grid provided. Note that rates remain constant
within each month.
Evaporate Only During Dry Periods
Select this option if evaporation can only occur during periods with no precipitation.
In addition this page allows the user to specify an optional Monthly Soil Recovery Pattern. This is a time pattern whose factors adjust the rate at which
infiltration capacity is recovered during periods with no precipitation. It applies
to all subcatchments for any choice of infiltration method. For example, if the
normal infiltration recovery rate was 1% during a specific time period and a pattern factor of 0.8 applied to this period, then the actual recovery rate would be
0.8%. The Soil Recovery Pattern allows one to account for seasonal soil drying
rates. In principle, the variation in pattern factors should mirror the variation in
evaporation rates but might be influenced by other factors such as seasonal
groundwater levels. The button is used to launch the Time Pattern Editor for
the selected pattern.
Wind Speed Page
The Wind Speed page of the Climatology Editor dialog is used to provide average monthly wind speeds. These are used when computing snowmelt rates under
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Property Editors
rainfall conditions. Melt rates increase with increasing wind speed. Units of
wind speed are miles/hour for US units and km/hour for metric units. There are
two choices for specifying wind speeds:
From Climate File
Wind speeds will be read from the same climate file that was specified for temperature.
Monthly Averages
Wind speed is specified as an average value that remains constant in each month
of the year. Enter a value for each month in the data grid provided. The default
values are all zero.
Snowmelt Page
The Snowmelt page of the Climatology Editor dialog is used to supply values
for the following parameters related to snow melt calculations:
Dividing Temperature Between Snow and Rain
Enter the temperature below which precipitation falls as snow instead of rain.
Use degrees F for US units or degrees C for metric units.
ATI (Antecedent Temperature Index) Weight
This parameter reflects the degree to which heat transfer within a snow pack
during non-melt periods is affected by prior air temperatures. Smaller values
reflect a thicker surface layer of snow which results in reduced rates of heat
transfer. Values must be between 0 and 1, and the default is 0.5.
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Negative Melt Ratio
This is the ratio of the heat transfer coefficient of a snow pack during non-melt
conditions to the coefficient during melt conditions. It must be a number between 0 and 1. The default value is 0.6.
Elevation Above MSL
Enter the average elevation above mean sea level for the study area, in feet or
meters. This value is used to provide a more accurate estimate of atmospheric
pressure. The default is 0.0, which results in a pressure of 29.9 inches Hg. The
effect of wind on snow melt rates during rainfall periods is greater at higher
pressures, which occur at lower elevations.
Latitude
Enter the latitude of the study area in degrees North. This number is used when
computing the hours of sunrise and sunset, which in turn are used to extend
min/max daily temperatures into continuous values. It is also used to compute
daily evaporation rates from daily temperatures. The default is 50o North.
Longitude Correction
This is a correction, in minutes of time, between true solar time and the standard
clock time. It depends on a location's longitude (?) and the standard meridian of
its time zone (SM) through the expression 4(?-SM). This correction is used to
adjust the hours of sunrise and sunset when extending daily min/max temperatures into continuous values. The default value is 0.
Areal Depletion Page
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Property Editors
The Areal Depletion page of the Climatology Editor Dialog is used to specify
points on the Areal Depletion Curves for both impervious and pervious surfaces
within a project's study area. These curves define the relation between the area
that remains snow covered and snow pack depth. Each curve is defined by 10
equal increments of relative depth ratio between 0 and 0.9. (Relative depth ratio
is the ratio of an area's current snow depth to the depth at which there is 100%
areal coverage).
Enter values in the data grid provided for the fraction of each area that remains snow covered at each specified relative depth ratio. Valid numbers must
be between 0 and 1, and be increasing with increasing depth ratio.
Clicking the Natural Area button fills the grid with values that are typical of
natural areas. Clicking the No Depletion button will fill the grid with all 1's,
indicating that no areal depletion occurs. This is the default for new projects.
7.3 Control Rules Editor
The Control Rules Editor is invoked whenever a new control rule is created or
an existing rule is selected for editing. The editor contains a memo field where
the entire collection of control rules is displayed and can be edited.
Control Rule Format
Each control rule is a series of statements of the form:
RULE
ruleID
IF
AND
OR
AND
Etc.
condition_1
condition_2
condition_3
condition_4
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THEN action_1
AND
action_2
Etc.
ELSE action_3
AND
action_4
Etc.
PRIORITY value
where keywords are shown in boldface and ruleID is an ID label assigned to
the rule, condition_n is a Condition Clause, action_n is an Action
Clause, and value is a priority value (e.g., a number from 1 to 5). The formats
used for Condition and Action clauses are discussed below.
Only the RULE, IF and THEN portions of a rule are required; the ELSE
and PRIORITY portions are optional.
Blank lines between clauses are permitted and any text to the right of a semicolon is considered a comment.
When mixing AND and OR clauses, the OR operator has higher precedence
than AND:
IF A or B and C
is equivalent to
IF (A or B) and C.
If the interpretation was meant to be
IF A or (B and C)
then this can be expressed using two rules as in
IF A THEN ...
IF B and C THEN ...
The PRIORITY value is used to determine which rule applies when two or
more rules require that conflicting actions be taken on a link. A rule without a
priority value always has a lower priority than one with a value. For two rules
with the same priority value, the rule that appears first is given the higher priority.
Condition Clauses
A Condition Clause of a control rule has the following format:
object id attribute relation value
where
object
=
a category of object
id
=
the object's ID label
attribute
=
an attribute or property of the object
relation
=
a relational operator (=, <>, <, <=, >, >=)
value
=
an attribute value
Some examples of condition clauses are:
NODE N23 DEPTH > 10
PUMP P45 STATUS = OFF
SIMULATION CLOCKTIME = 22:45:00
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Property Editors
The objects and attributes that can appear in a condition clause are as follows.
Object
NODE
Attributes
DEPTH
HEAD
INFLOW
Value
LINK
FLOW
DEPTH
numerical value
numerical value
PUMP
STATUS
FLOW
ON or OFF
numerical value
ORIFICE
WEIR
SETTING
fraction open
SIMULATION
TIME
DATE
CLOCKTIME
elapsed time in decimal hours or hr:min:sec
month/day/year
time of day in hr:min:sec
numerical value
numerical value
numerical value
Action Clauses
An Action Clause of a control rule can have one of the following formats:
PUMP
id STATUS
= ON/OFF
PUMP/ORIFICE/WEIR/OUTLET id SETTING
=
value
where the meaning of SETTING depends on the object being controlled:
• for Pumps it is a multiplier applied to the flow computed from the
pump curve,
• for Orifices it is the fractional amount that the orifice is fully open,
• for Weirs it is the fractional amount of the original freeboard that
exists (i.e., weir control is accomplished by moving the crest height
up or down),
• for Outlets it is a multiplier applied to the flow computed from the
outlet's rating curve.
Some examples of action clauses are:
PUMP P67 STATUS = OFF
ORIFICE O212 SETTING = 0.5
Modulated Controls
Modulated controls are control rules that provide for a continuous degree of control applied to a pump or flow regulator as determined by the value of some
controller variable, such as water depth at a node, or by time. The functional
relation between the control setting and the controller variable can be specified
by using a Control Curve, a Time Series, or a PID Controller. Some examples of
modulated control rules are:
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Property Editors
RULE MC1
IF NODE N2 DEPTH >= 0
THEN WEIR W25 SETTING = CURVE C25
RULE MC2
IF SIMULATION TIME > 0
THEN PUMP P12 SETTING = TIMESERIES TS101
RULE MC3
IF LINK L33 FLOW <> 1.6
THEN ORIFICE O12 SETTING = PID 0.1 0.0 0.0
Note how a modified form of the action clause is used to specify the name of
the control curve, time series or PID parameter set that defines the degree of
control. A PID parameter set contains three values -- a proportional gain coefficient, an integral time (in minutes), and a derivative time (in minutes). Also, by
convention the controller variable used in a Control Curve or PID Controller
will always be the object and attribute named in the last condition clause of the
rule. As an example, in rule MC1 above Curve C25 would define how the fractional setting at Weir W25 varied with the water depth at Node N2. In rule MC3,
the PID controller adjusts the opening of Orifice O12 to maintain a flow of 1.6
in Link L33.
PID Controllers
A PID (Proportional-Integral-Derivative) Controller is a generic closed-loop
control scheme that tries to maintain a desired set-point on some process variable by computing and applying a corrective action that adjusts the process
accordingly. In the context of a hydraulic conveyance system a PID controller
might be used to adjust the opening on a gated orifice to maintain a target flow
rate in a specific conduit or to adjust a variable speed pump to maintain a desired depth in a storage unit. The classical PID controller has the form:
⎡
1
de( t ) ⎤
m( t ) = K p ⎢e( t ) + ∫ e( τ )dτ + Td
⎥
Ti
dt ⎦
⎣
where m(t) = controller output, Kp = proportional coefficient (gain), Ti = integral
time, Td = derivative time, e(t) = error (difference between setpoint and observed
variable value), and t = time. The performance of a PID controller is determined
by the values assigned to the coefficients Kp, Ti, and Td.
The controller output m(t) has the same meaning as a link setting used in a
rule's Action Clause while dt is the current flow routing time step in minutes.
Because link settings are relative values (with respect to either a pump's standard
operating curve or to the full opening height of an orifice or weir) the error e(t)
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Property Editors
used by the controller is also a relative value. It is defined as the difference between the control variable setpoint x* and its value at time t, x(t), normalized to
the setpoint value: e(t) = (x* - x(t)) / x*.
Note that for direct action control, where an increase in the link setting causes an increase in the controlled variable, the sign of Kp must be positive. For
reverse action control, where the controlled variable decreases as the link setting
increases, the sign of Kp must be negative. The user must recognize whether the
control is direct or reverse action and use the proper sign on Kd accordingly. For
example, adjusting an orifice opening to maintain a desired downstream flow is
direct action. Adjusting it to maintain a downstream water level is reverse action
while adjusting it to maintain an upstream water level is direct action. Controlling a pump to maintain a fixed wet well water level would be reverse action
while using it to maintain a fixed downstream flow is direct action.
7.4 Cross-Section Editor
The Cross-Section Editor dialog is used to specify the shape and dimensions of a
conduit's cross-section. When a shape is selected from the dropdown combo box
an appropriate set of edit fields appears for describing the dimensions of that
shape. Length dimensions are in units of feet for US units and meters for SI
units. Slope values represent ratios of horizontal to vertical distance. The Barrels
field specifies how many identical parallel conduits exist between its end nodes.
If an Irregular shaped section is chosen, a drop-down edit box will appear
where you can enter or select the name of a Transect object that describes the
cross-section's geometry. Clicking the Edit button next to the edit box will bring
up the Transect Editor from which you can edit the transect data.
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7.5 Curve Editor
The Curve Editor dialog is invoked whenever a new curve object is created or an
existing curve object is selected for editing. The editor adapts itself to the category of curve being edited (Storage, Tidal, Diversion, Pump, or Rating). To use
the Curve Editor:
• Enter values for the following data entry fields:
Name Name of the curve.
Type (Pump Curves Only). Choice of pump curve type as described in the Chapter 5, section 5.2 .8
Description Optional comment or description of what the
curve represents. Click the button to launch a multi-line
comment editor if more than one line is needed.
Data Grid The curve's X,Y data.
• Click the View button to see a graphical plot of the curve drawn in a
separate window.
• If additional rows are needed in the Data Grid, simply press the Enter key when in the last row.
• Right-clicking over the Data Grid will make a popup Edit menu appear. It contains commands to cut, copy, insert, and paste selected
cells in the grid as well as options to insert or delete a row.
You can also click the Load button to load in a curve that was previously saved
to file or click the Save button to save the current curve's data to a file.
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7.6 Groundwater Flow Editor
The Groundwater Flow Editor dialog is invoked when the Groundwater property
of a subcatchment is being edited. It is used to link a subcatchment to both an
aquifer and to a node of the drainage system that exchanges groundwater with
the aquifer. It also specifies coefficients that determine the rate of groundwater
flow between the aquifer and the node. These coefficients (A1, A2, B1, B2, and
A3) appear in the following equation that computes groundwater flow as a function of groundwater and surface water levels:
Qgw = A1( H gw ! H *) ! A2 ( H sw ! H *) + A3H gw H sw
B1
B2
where:
Qgw = groundwater flow (cfs per acre or cms per hectare)
Hgw = height of saturated zone above aquifer (ft or m)
Hsw = height of surface water at receiving node above aquifer bottom (ft or m)
H* = threshold groundwater height (ft or m).
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The properties listed in the editor are as follows.
Aquifer Name
Name of aquifer object that supplies groundwater. Leave this field blank if you
want the subcatchment not to generate any groundwater flow.
Receiving Node
Name of node that receives groundwater from the aquifer.
Surface Elevation
Elevation of ground surface for the subcatchment lying above the aquifer (ft or
m).
Groundwater Flow Coefficient
Value of A1 in the groundwater flow formula.
Groundwater Flow Exponent
Value of B1 in the groundwater flow formula.
Surface Water Flow Coefficient
Value of A2 in the groundwater flow formula.
Surface Water Flow Exponent
Value of B2 in the groundwater flow formula.
Surface-GW Interaction Coefficient
Value of A3 in the groundwater flow formula.
Fixed Surface Water Depth
Fixed depth of surface water at the receiving node (ft or m); set to 0 if surface
water depth will vary as computed by flow routing. This is used to compute HSW.
Threshold Groundwater Elevation
Groundwater elevation that must be reached before any flow occurs (feet or meters). Leave blank to use the receiving node's invert elevation.
The values of the flow coefficients must be in units that are consistent with
the groundwater flow units of cfs/acre for US units or cms/ha for metric units.
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If groundwater flow is simply proportional to the difference in groundwater and surface water heads, then set the Groundwater and Surface Water
Flow Exponents (B1 and B2) to 1.0, set the Groundwater Flow Coefficient (A1)
to the proportionality factor, set the Surface Water Flow Coefficient (A2) to the
same value as A1, and set the Interaction Coefficient (A3) to zero.
Note that when conditions warrant, the groundwater flux can be negative, simulating flow into the aquifer from the channel, in the manner of bank
storage. An exception occurs when A3 ≠ 0, since the surface water - groundwater interaction term is usually derived from groundwater flow models that
assume unidirectional flow. Otherwise, to ensure that negative fluxes will not
occur, one can make A1 greater than or equal to A2, B1 greater than or equal to
B2, and A3 equal to zero.
7.7 Infiltration Editor
The Infiltration Editor dialog is used to specify values for the parameters that
describe the rate at which rainfall infiltrates into the upper soil zone in a subcatchment's pervious area. It is invoked when editing the Infiltration property of
a subcatchment. The infiltration parameters depend on which infiltration model
was selected for the project: Horton, Green-Ampt, or Curve Number. The choice
of infiltration model can be made either by editing the project's Simulation Op-
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tions (see Chapter 11 Running a Simulation, section 11.1) or by changing the
project's Default Properties (see Chapter 8 Working with Projects, section 8.4).
Horton Infiltration Parameters
The following data fields appear in the Infiltration Editor for Horton infiltration.
Max. Infil. Rate
Maximum infiltration rate on the Horton curve (in/hr or mm/hr). Representative
values are as follows:
1. DRY soils (with little or no vegetation):
• Sandy soils: 5 in/hr
• Loam soils: 3 in/hr
• Clay soils: 1 in/hr
2. DRY soils (with dense vegetation):
• Multiply values in A. by 2
3. MOIST soils:
• Soils which have drained but not dried out (i.e., field capacity):
• Divide values from A and B by 3.
• Soils close to saturation:
• Choose value close to min. infiltration rate.
• Soils which have partially dried out:
• Divide values from A and B by 1.5 - 2.5.
Min. Infil. Rate
Minimum infiltration rate on the Horton curve (in/hr or mm/hr). Equivalent to
the soil’s saturated hydraulic conductivity. See the Soil Characteristics Table in
Chapter 24 Useful Tables, section 24.2 for typical values.
Decay Const.
Infiltration rate decay constant for the Horton curve (1/hours). Typical values
range between 2 and 7.
Drying Time
Time in days for a fully saturated soil to dry completely. Typical values range
from 2 to 14 days.
Max. Infil. Vol.
Maximum infiltration volume possible (inches or mm, 0 if not applicable). It can
be estimated as the difference between a soil's porosity and its wilting point
times the depth of the infiltration zone.
Green-Ampt Infiltration Parameters
The following data fields appear in the Infiltration Editor for Green-Ampt infiltration.
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Suction Head
Average value of soil capillary suction along the wetting front (inches or mm).
Conductivity
This property has been deprecated (sic) and is no longer used.
Initial Deficit
Fraction of soil volume that is initially dry (i.e. difference between soil porosity
and initial moisture content). For a completely drained soil, it is the difference
between the soil's porosity and its field capacity.
Typical values for all of these parameters can be found in the Soil Characteristics Table in Chapter 24 Useful Tables, section 24.2.
Curve Number Infiltration Parameters
The following data fields appear in the Infiltration Editor for Curve Number
infiltration.
Curve Number
This is the SCS curve number which is tabulated in the publication SCS Urban
Hydrology for Small Watersheds, 2nd Ed., (TR-55), June 1986. Consult the
Curve Number Table (Chapter 24 Useful Tables, section 24.4) for a listing of
values by soil group, and the accompanying Soil Group Table (section 24.3) for
the definitions of the various groups.
Conductivity
The soil's saturated hydraulic conductivity (in/hr or mm/hr). Typical ranges are
shown in both the Soil Group Table (Chapter 24, section 24.3) and in the Soil
Characteristics Table (section 24.2). This is used to estimate the minimum number of dry hours that must occur before a new storm is considered to begin using
the equation: dry hours = 4.5 / (conductivity, in/hr)1/2.
Drying Time
The number of days it takes a fully saturated soil to dry. Typical values range
between 2 and 14 days.
7.8 Inflows Editor
The Inflows Editor dialog is used to assign Direct, Dry Weather, and RDII inflow into a node of the drainage system. It is invoked whenever the Inflows
property of a Node object is selected in the Property Editor. The dialog consists
of three tabbed pages that provide a special editor for each type of inflow.
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Direct Inflows Page
The Direct page on the Inflows Editor dialog is used to specify the time history
of direct external flow and water quality entering a node of the drainage system.
These inflows are represented by both a constant and time varying component as
follows:
Inflow at time t = (baseline value) + (scale factor)* (time series value at time t)
The dialog consists of the following input fields.
Constituent
Selects the constituent (FLOW or one of the project's specified pollutants)
whose direct inflow will be described.
Baseline
Specifies the value of the constant baseline component of the constituent's inflow. For FLOW, the units are the project's flow units. For pollutants, the units
are the pollutant's concentration units if inflow is a concentration, or can be any
mass flow units if the inflow is a mass flow (see Conversion Factor below). If
left blank then no baseline inflow is assumed.
Baseline Pattern
An optional Time Pattern whose factors adjust the baseline inflow on either an
hourly, daily, or monthly basis (depending on the type of time pattern specified).
Clicking the
button will bring up the Time Pattern Editor dialog for the selected time pattern. If left blank, then no adjustment is made to the baseline
inflow.
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Time Series
Specifies the name of the time series that contains inflow data for the selected
constituent. If left blank then no direct inflow will occur for the selected constituent at the node in question. You can click the button to bring up the Time
Series Editor dialog for the selected time series.
Scale Factor
A multiplier used to adjust the values of the constituent's inflow time series. The
baseline value is not adjusted by this factor. The scale factor can have several
uses, such as allowing one to easily change the magnitude of an inflow hydrograph while keeping its shape the same, without having to re-edit the entries in
the hydrograph's time series. Or it can allow a group of nodes sharing the same
time series to have their inflows behave in a time-synchronized fashion while
letting their individual magnitudes be different. If left blank the scale factor defaults to 1.0.
Inflow Type
For pollutants, selects the type of inflow data contained in the time series as being either a concentration (mass/volume) or mass flow rate (mass/time). This
field does not appear for FLOW inflow.
Conversion Factor
A numerical factor used to convert the units of pollutant mass flow rate in the
time series data into concentration mass units per second. For example, if the
time series data were in pounds per day and the pollutant concentration defined
in the project was mg/L, then the conversion factor value would be (453,590
mg/lb) / (86400 sec/day) = 5.25 (mg/sec) per (lb/day).
More than one constituent can be edited while the dialog is active by simply
selecting another choice for the Constituent property. However, if the Cancel
button is clicked then any changes made to all constituents will be ignored.
If a pollutant is assigned a direct inflow in terms of concentration, then
one must also assign a direct inflow to flow, otherwise no pollutant inflow will
occur. An exception is at submerged outfalls where pollutant intrusion can occur
during periods of reverse flow. If pollutant inflow is defined in terms of mass,
then a flow inflow time series is not required.
Dry Weather Inflows Page
The Dry Weather page of the Inflows Editor dialog is used to specify a continuous source of dry weather flow entering a node of the drainage system. The
dialog consists of the following input fields.
Constituent
Selects the constituent (FLOW or one of the project's specified pollutants)
whose dry weather inflow will be specified.
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Average Value
Specifies the average (or baseline) value of the dry weather inflow of the constituent in the relevant units (flow units for flow, concentration units for
pollutants). Leave blank if there is no dry weather flow for the selected constituent.
Time Patterns
Specifies the names of the time patterns to be used to allow the dry weather flow
to vary in a periodic fashion by month of the year, by day of the week, and by
time of day (for both weekdays and weekends). One can either type in a name or
select a previously defined pattern from the dropdown list of each combo box.
Up to four different types of patterns can be assigned. You can click the button next to each Time Pattern field to edit the respective pattern.
More than one constituent can be edited while the dialog is active by simply
selecting another choice for the Constituent property. However, if the Cancel
button is clicked then any changes made to all constituents will be ignored.
RDII Inflow Page
The RDII page of the Inflows Editor dialog is used to specify RDII (rainfalldependent infiltration/inflow) for the node in question. The editor contains the
following two input fields:
Unit Hydrograph Group
Enter (or select from the dropdown list) the name of the Unit Hydrograph group
that applies to the node in question. The unit hydrographs in the group are used
in combination with the group's assigned rain gage to develop a time series of
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RDII inflows per unit area over the period of the simulation. Leave this field
blank to indicate that the node receives no RDII inflow. Clicking the button
will launch the Unit Hydrograph Editor for the UH group specified.
Sewershed Area
Enter the area (in acres or hectares) of the sewershed that contributes RDII to the
node in question. Note this area will typically be only a small, localized portion
of the subcatchment area that contributes surface runoff to the node.
7.9 Initial Buildup Editor
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The Initial Buildup Editor is invoked from the Property Editor when editing the
Initial Buildup property of a subcatchment. It specifies the amount of pollutant
buildup existing over the subcatchment at the start of the simulation. The editor
consists of a data entry grid with two columns. The first column lists the name
of each pollutant in the project and the second column contains edit boxes for
entering the initial buildup values. If no buildup value is supplied for a pollutant,
it is assumed to be 0. The units for buildup are either pounds per acre when US
units are in use or kilograms per hectare when SI metric units are in use.
If a non-zero value is specified for the initial buildup of a pollutant, it will
override any initial buildup computed from the Antecedent Dry Days parameter
specified on the Dates page of the Simulation Options dialog.
7.10 Land Use Editor
The Land Use Editor dialog is used to define a category of land use for the study
area and to define its pollutant buildup and washoff characteristics. The dialog
contains three tabbed pages of land use properties:
• General Page (provides land use name and street sweeping parameters)
• Buildup Page (defines rate at which pollutant buildup occurs)
• Washoff Page (defines rate at which pollutant washoff occurs)
General Page
The General page of the Land Use Editor dialog describes the following properties of a particular land use category:
Land Use Name
The name assigned to the land use.
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Description
An optional comment or description of the land use (click the ellipsis button or
press Enter to edit).
Street Sweeping Interval
Days between street sweeping within the land use.
Street Sweeping Availability
Fraction of the buildup of all pollutants that is available for removal by sweeping.
Last Swept
Number of days since last swept at the start of the simulation.
If street sweeping does not apply to the land use, then the last three properties can be left blank.
Buildup Page
The Buildup page of the Land Use Editor dialog describes the properties associated with pollutant buildup over the land during dry weather periods. These are:
Pollutant
Select the pollutant whose buildup properties are being edited.
Function
The type of buildup function to use for the pollutant. The choices are NONE for
no buildup, POW for power function buildup, EXP for exponential function
buildup and SAT for saturation function buildup. See the discussion of Pollutant
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Buildup in Chapter 5, section 5.3.9 for explanations of these different functions.
Select NONE if no buildup occurs.
Max. Buildup
The maximum buildup that can occur, expressed as lbs (or kg) of the pollutant
per unit of the normalizer variable (see below). This is the same as the C1 coefficient used in the buildup formulas discussed in Chapter 5, section 5.3.9.
The following two properties apply to the POW, EXP, and SAT buildup
functions.
Rate Constant
The time constant that governs the rate of pollutant buildup. This is the C2 coefficient in the Power and Exponential buildup formulas discussed in Chapter 5,
section 5.3.9. For Power buildup its units are mass / days raised to a power,
while for Exponential buildup its units are 1/days.
Power/Sat. Constant
The exponent C3 used in the Power buildup formula, or the half-saturation constant C2 used in the Saturation buildup formula discussed in Chapter 5, section
5.3.9. For the latter case, its units are days.
The following two properties apply to the EXT (External Time Series) option.
Scaling Factor
A multiplier used to adjust the buildup rates listed in the time series.
Time Series
The name of the Time Series that contains buildup rates (as mass per normalizer
per day).
Normalizer
The variable to which buildup is normalized on a per unit basis. The choices are
either land area (in acres or hectares) or curb length. Any units of measure can
be used for curb length, as long as they remain the same for all subcatchments in
the project.
When there are multiple pollutants, the user must select each pollutant separately from the Pollutant dropdown list and specify its pertinent buildup
properties.
Washoff Page
The Washoff page of the Land Use Editor dialog describes the properties associated with pollutant washoff over the land use during wet weather events. These
consist of the following.
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Pollutant
The name of the pollutant whose washoff properties are being edited.
Function
The choice of washoff function to use for the pollutant. The choices are:
* NONE
no washoff
* EXP
exponential washoff
* RC
rating curve washoff
* EMC
event-mean concentration washoff.
The formula for each of these functions is discussed in Chapter 5, section
5.3.9 under the Pollutant Washoff topic.
Coefficient
This is the value of C1 in the exponential and rating curve formulas, or the
event-mean concentration.
Exponent
The exponent used in the exponential and rating curve washoff formulas.
Cleaning Efficiency
The street cleaning removal efficiency (percent) for the pollutant. It represents
the fraction of the amount that is available for removal on the land use as a
whole (set on the General page of the editor) which is actually removed.
BMP Efficiency
Removal efficiency (percent) associated with any Best Management Practice
that might have been implemented. The washoff load computed at each time
step is simply reduced by this amount.
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As with the Buildup page, each pollutant must be selected in turn from the
Pollutant dropdown list and have its pertinent washoff properties defined.
7.11 Land Use Assignment Editor
The Land Use Assignment editor is invoked from the Property Editor when editing the Land Uses property of a subcatchment. Its purpose is to assign land uses
to the subcatchment for water quality simulations. The percent of land area in
the subcatchment covered by each land use is entered next to its respective land
use category. If the land use is not present its field can be left blank. The percentages entered do not necessarily have to add up to 100.
7.12 LID Control Editor
The LID Control Editor is used to define a low impact development control that
can be deployed throughout a study area to store, infiltrate, and evaporate subcatchment runoff. The design of the control is made on a per-unit-area basis so
that it can be placed in any number of subcatchments at different sizes or number of replicates. The editor contains the following data entry fields.
Control Name
A name used to identify the particular LID control.
LID Type
The generic type of LID being defined (bio-retention cell, porous pavement,
infiltration trench, rain barrel, or vegetative swale).
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The Process Layers are a tabbed set of pages containing data entry fields for
the vertical layers and underdrain that comprise an LID control. They include
some combination of the following, depending on the type of LID selected:
• Surface Layer
• Pavement Layer
• Soil Layer
• Storage Layer
• Underdrain System.
Surface Layer Page
The Surface Layer page of the LID Control Editor is used to describe the surface properties of bio-retention cells, porous pavement, infiltration trenches,
and vegetative swales. These properties are as follows.
Storage Depth
When confining walls or berms are present this is the maximum depth to which
water can pond above the surface of the unit before overflow occurs (in inches
or mm). For LIDs that experience overland flow it is the height of any surface
depression storage. For swales, it is the height of its trapezoidal cross section.
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Vegetative Cover Fraction
The fraction of the storage area above the surface that is filled with vegetation.
Surface Roughness
Manning's n for overland flow over the surface of porous pavement or a vegetative swale. Use 0 for other types of LIDs.
Surface Slope
Slope of porous pavement surface or vegetative swale (percent). Use 0 for other
types of LIDs.
Swale Side Slope
Slope (run over rise) of the side walls of a vegetative swale's cross section. This
value is ignored for other types of LIDs.
If either Surface Roughness or Surface Slope values are 0 then any
ponded water that exceeds the storage depth is assumed to completely overflow
the LID control within a single time step.
Pavement Layer
The Pavement Layer page of the LID Control Editor supplies values for the
following properties of a porous pavement LID.
Thickness
The thickness of the pavement layer (inches or mm). Typical values are 4 to 6
inches (100 to 150 mm).
Void Ratio
The volume of void space relative to the volume of solids in the pavement for
continuous systems or for the fill material used in modular systems. Typical values for pavements are 0.12 to 0.21. Note that porosity = void ratio / (1 + void
ratio).
Impervious Surface Fraction
Ratio of impervious paver material to total area for modular systems; 0 for continuous porous pavement systems.
Permeability
Permeability of the concrete or asphalt used in continuous systems or hydraulic
conductivity of the fill material (gravel or sand) used in modular systems (in/hr
or mm/hr). The permeability of new porous concrete or asphalt is very high
(e.g., hundreds of in/hr) but can drop off over time due to clogging by fine particulates in the runoff (see below).
Clogging Factor
Number of pavement layer void volumes of runoff treated it takes to completely
clog the pavement. Use a value of 0 to ignore clogging. Clogging progressively
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reduces the pavement's permeability in direct proportion to the cumulative volume of runoff treated.
If one has an estimate of the number of years it takes to fully clog the system
(Yclog), the Clogging Factor can be computed as: Yclog * Pa * CR * (1 + VR) *
(1 - ISF) / (T * VR) where Pa is the annual rainfall amount over the site, CR is
the pavement's capture ratio (area that contributes runoff to the pavement divided by area of the pavement itself), VR is the system's Void Ratio, ISF is the
Impervious Surface Fraction, and T is the pavement layer Thickness.
As an example, suppose it takes 5 years to clog a continuous porous pavement system that serves an area where the annual rainfall is 36 inches/year. If
the pavement is 6 inches thick, has a void ratio of 0.2 and captures runoff only
from its own surface, then the Clogging Factor is 5 x 36 x (1 + 0.2) / 6 / 0.2 =
180.
Soil Layer Page
The Soil Layer page of the LID Control Editor describes the properties of the
engineered soil mixture used in bio-retention types of LIDs. These properties
are the following.
Thickness
The thickness of the soil layer (inches or mm). Typical values range from 18 to
36 inches (450 to 900 mm) for rain gardens, street planters and other types of
land-based bio-retention units, but only 3 to 6 inches (75 to 150 mm) for green
roofs.
Porosity
The volume of pore space relative to total volume of soil (as a fraction).
Field Capacity
Volume of pore water relative to total volume after the soil has been allowed to
drain fully (as a fraction). Below this level, vertical drainage of water through
the soil layer does not occur.
Wilting Point
Volume of pore water relative to total volume for a well dried soil where only
bound water remains (as a fraction). The moisture content of the soil cannot fall
below this limit.
Conductivity
Hydraulic conductivity for the fully saturated soil (in/hr or mm/hr).
Conductivity Slope
Slope of the curve of log(conductivity) versus soil moisture content (dimensionless). Typical values range from 5 for sands to 15 for silty clay.
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Suction Head
The average value of soil capillary suction along the wetting front (inches or
mm). This is the same parameter as used in the Green-Ampt infiltration model.
Porosity, field capacity, conductivity and conductivity slope are the
same soil properties used for Aquifer objects when modeling groundwater,
while suction head is the same parameter used for Green-Ampt infiltration. Except here they apply to the special soil mixture used in a LID unit rather than the
site's naturally occuring soil.
Storage Layer Page
The Storage Layer page of the LID Control Editor describes the properties of
the crushed stone or gravel layer used in bio-retention cells, porous pavement
systems, and infiltration trenches as a bottom storage/drainage layer. It is also
used to specify the height of a rain barrel (or cistern). The following data fields
are displayed.
Height
This is the height of a rain barrel or thickness of a gravel layer (inches or mm).
Crushed stone and gravel layers are typically 6 to 18 inches (150 to 450 mm)
thick while single family home rain barrels range in height from 24 to 36 inches
(600 to 900 mm).
The following data fields do not apply to Rain Barrels.
Void Ratio
The volume of void space relative to the volume of solids in the layer. Typical
values range from 0.5 to 0.75 for gravel beds. Note that porosity = void ratio / (1
+ void ratio).
Filtration Rate
The maximum rate at which water can flow out the bottom of the layer after it is
first constructed (in/hr or mm/hr). Typical values for gravels are 10 to 30 in/hr
(250 to 750 mm/hr). If the layer contains a sand bed beneath it then the conductivity of the sand should be used. If there is an impermeable floor or liner below
the layer then use a value of 0. The actual exfiltration rate through the bottom
will be the smaller of this limiting rate and the normal infiltration rate into the
soil below the layer.
Clogging Factor
Total volume of treated runoff it takes to completely clog the bottom of the layer
divided by the void volume of the layer. Use a value of 0 to ignore clogging.
Clogging progressively reduces the Filtration Rate in direct proportion to the
cumulative volume of runoff treated and may only be of concern for infiltration
trenches with permeable bottoms and no under drains.
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Underdrain Page
LID storage layers can contain an optional underdrain system that collects
stored water from the bottom of the layer and conveys it to a conventional storm
drain. The Underdrain page of the LID Control Editor describes the properties of
this system. It contains the following data entry fields.
Drain Coefficient and Drain Exponent
Coefficient C and exponent n that determines the rate of flow through the underdrain as a function of height of stored water above the drain height. The
following equation is used to compute this flow rate (per unit area of the LID
unit):
q = C(h ! H d )n
where q is outflow (in/h or mm/h), h is the height of stored water (inches or
mm), and Hd is the drain height. If the layer does not have an underdrain then set
C to 0. A typical value for n would be 0.5 (making the drain act like an orifice).
A rough estimate for C can be based on the time T required to drain a depth D
of stored water. For n = 0.5, C = 2D½/T.
Drain Offset Height
Height Hd of any underdrain piping above the bottom of a storage layer or rain
barrel (inches or mm).
Drain Delay (for Rain Barrels only)
The number of dry weather hours that must elapse before the drain line in a rain
barrel is opened (the line is assumed to be closed once rainfall begins). This parameter is ignored for other types of LIDs.
7.13 LID Group Editor
The LID Group Editor is invoked when the LID Controls property of a Subcatchment is selected for editing. It is used to identify a group of previously
defined LID controls that will be placed within the subcatchment, the sizing of
each control, and what percent of runoff from the non-LID portion of the subcatchment each should treat.
The editor displays the current group of LIDs placed in the subcatchment
along with buttons for adding an LID unit, editing a selected unit, and deleting a
selected unit. These actions can also be chosen by hitting the Insert key, the
Enter key, and the Delete key, respectively. Selecting Add or Edit will bring up
an LID Usage Editor where one can enter values for the data fields shown in the
Group Editor.
Note that the total % Of Area for all of the LID units within a subcatchment
must not exceed 100%. The same applies to % From Impervious. Refer to the
LID Usage Editor for the meaning of these parameters.
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7.14 LID Usage Editor
The LID Usage Editor is invoked from a subcatchment's LID Group Editor to
specify how a particular LID control will be deployed within the subcatchment.
It contains the following data entry fields.
Control Name
The name of a previously defined LID control to be used in the subcatchment.
(LID controls are added to a project by using the Data Browser.)
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Number of Replicate Units
The number of equal size units of the LID practice (e.g., the number of rain barrels) deployed within the subcatchment.
Area of Each Unit
The surface area devoted to each replicate LID unit (sq. ft or sq. m). If the LID
Occupies Full Subcatchment box is checked, then this field becomes disabled
and will display the total subcatchment area divided by the number of replicate
units. (See Section 5.3.14 for options on placing LIDs within subcatchments.)
The label below this field indicates how much of the total subcatchment area is
devoted to the particular LID being deployed.
Top Width of Overland Flow Surface
The width of the outflow face of each identical LID unit (ft or m). This parameter only applies to LID processes that use overland flow (e.g. Porous Pavement,
Vegetative Swales) to convey surface runoff off of the unit. The other LID processes (e.g. Bio-Retention Cells and Infiltration Trenches) simply spill any
excess captured runoff over their berms.
% Initially Saturated
For Bio-Retention Cells this is the degree to which the unit’s soil is initially
filled with water (0% saturation corresponds to the wilting point moisture content, 100% has the moisture content equal to the porosity). The storage zone
beneath the soil zone of the cell is assumed to be completely dry. For other types
of LID it corresponds to the degree to which their storage zone is initially filled
with water.
% of Impervious Area Treated
The percent of the impervious portion of the subcatchment's non-LID area
whose runoff is treated by the LID practice. (E.g. if rain barrels are used to capture roof runoff and roofs represent 60% of the impervious area, then the
impervious area treated is 60%). If the LID unit treats only direct rainfall, such
as with a green roof, then this value should be 0. If the LID takes up the entire
subcatchment then this field is ignored.
Send Outflow to Pervious Area
Select this option if the outflow from the LID is returned onto the subcatchment's pervious area rather than going to the subcatchment's outlet. An example
of where this might apply is a rain barrel whose contents are used to irrigate a
lawn area. This field is ignored if the LID takes up the entire subcatchment.
Detailed Report File
The name of an optional file where detailed time series results for the LID will
be written. Click the browse button to select a file using the standard Windows File Save dialog or click the delete button to remove any detailed
reporting. The detailed report file will be a tab delimited text file that can be
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easily opened and viewed with any text editor or spreadsheet program (such as
Microsoft Excel) outside of SWMM.
7.15 Pollutant Editor
The Pollutant Editor is invoked when a new pollutant object is created or an existing pollutant is selected for editing. It contains the following fields.
Name
The name assigned to the pollutant.
Units
The concentration units (mg/L, µg/L or #/L (counts/L)) in which the pollutant
concentration is expressed.
Rain Concentration
Concentration of the pollutant in rain water (concentration units).
GW Concentration
Concentration of the pollutant in ground water (concentration units).
I&I Concentration
Concentration of the pollutant in any Infiltration/Inflow (concentration units)
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DWF Concentration
Concentration of the pollutant in any dry weather sanitary flow (concentration
units). This value can be overriden for any specific node of the conveyance system by editing the node's Inflows property
Decay Coefficient
First-order decay coefficient of the pollutant (1/days).
Snow Only
YES if pollutant buildup occurs only when snowfall occurs, NO otherwise (default is NO).
Co-Pollutant
Name of another pollutant whose runoff concentration contributes to the runoff
concentration of the current pollutant.
Co-Fraction
Fraction of the co-pollutant's runoff concentration that contributes to the runoff
concentration of the current pollutant.
An example of a co-pollutant relationship would be where the runoff concentration of a particular heavy metal is some fixed fraction of the runoff
concentration of suspended solids. In this case suspended solids would be declared as the co-pollutant for the heavy metal.
7.16 Snow Pack Editor
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The Snow Pack Editor is invoked when a new snow pack object is created or an
existing snow pack is selected for editing. The editor contains a data entry field
for the snow pack’s name and two tabbed pages, one for snow pack parameters
and one for snow removal parameters.
Snow Pack Parameters Page
The Parameters page of the Snow Pack Editor dialog provides snow melt parameters and initial conditions for snow that accumulates over three different
types of areas: the impervious area that is plowable (i.e., subject to snow removal), the remaining impervious area, and the entire pervious area. The page
contains a data entry grid which has a column for each type of area and a row
for each of the following parameters:
Min. Melt Coefficient
The degree-day snow melt coefficient that occurs on December 21. Units are
either in/hr-deg F or mm/hr-deg C.
Max. Melt Coefficient
The degree-day snow melt coefficient that occurs on June 21. Units are either
in/hr-deg F or mm/hr-deg C. For a short term simulation of less than a week or
so it is acceptable to use a single value for both the minimum and maximum
melt coefficients.
The minimum and maximum snow melt coefficients are used to estimate a
melt coefficient that varies by day of the year. The latter is used in the following
degree-day equation to compute the melt rate for any particular day:
Melt Rate = (Melt Coefficient) * (Air Temperature – Base Temperature).
Base Temperature
Temperature at which snow begins to melt (˚F or ˚C).
Fraction Free Water Capacity
The volume of a snow pack's pore space which must fill with melted snow before liquid runoff from the pack begins, as a fraction of snow pack depth.
Initial Snow Depth
Depth of snow at the start of the simulation (water equivalent depth in inches or
millimeters).
Initial Free Water
Depth of melted water held within the pack at the start of the simulation (inches
or mm). This number should be at or below the product of the initial snow depth
and the fraction free water capacity.
Depth at 100% Cover
The depth of snow beyond which the entire area remains completely covered
and is not subject to any areal depletion effect (inches or mm).
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Fraction of Impervious Area That is Plowable
The fraction of impervious area that is plowable and therefore is not subject to
areal depletion.
Snow Removal Parameters Page
The Snow Removal page of the Snow Pack Editor describes how snow removal
occurs within the Plowable area of a snow pack. The following parameters govern this process.
Depth at which snow removal begins (in or mm)
No removal occurs at depths below this and the fractions specified below are
applied to the snow depths in excess of this number.
Fraction transferred out of the watershed
The fraction of excess snow depth that is removed from the system (and does
not become runoff).
Fraction transferred to the impervious area
The fraction of excess snow depth that is added to snow accumulation on the
pack's impervious area.
Fraction transferred to the pervious area
The fraction of excess snow depth that is added to snow accumulation on the
pack's pervious area.
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Fraction converted to immediate melt
The fraction of excess snow depth that becomes liquid water which runs onto
any subcatchment associated with the snow pack.
Fraction moved to another subcatchment
The fraction of excess snow depth which is added to the snow accumulation on
some other subcatchment. The name of the subcatchment must also be provided.
The various removal fractions must add up to 1.0 or less. If less than 1.0,
then some remaining fraction of snow depth will be left on the surface after all
of the redistribution options are satisfied.
7.17 Time Pattern Editor
The Time Pattern Editor is invoked when a new time pattern object is created or
an existing time pattern is selected for editing. The editor contains the following
data entry fields.
Name
Enter the name assigned to the time pattern.
Type
Select the type of time pattern being specified.
Description
You can enter an optional comment/description for the time pattern; if you need
more than one line, click the button to launch a multi-line comment editor.
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Multipliers
Enter a value for each multiplier. The number and meaning of the multipliers
changes with the type of time pattern selected:
MONTHLY One multiplier for each month of the year.
DAILY
One multiplier for each day of the week.
HOURLY One multiplier for each hour from 12 midnight to 11 p.m.
WEEKEND Same as for HOURLY except applied to weekend days.
In order to maintain an average dry weather flow or pollutant concentration at its specified value (as entered on the Inflows Editor), the multipliers for a
pattern should average to 1.0.
7.18 Time Series Editor
The Time Series Editor is invoked whenever a new time series object is created
or an existing time series is selected for editing. To use the Time Series Editor,
perform the following steps.
1. Enter values for the following standard items:
Name
Name of the time series.
Description
Optional comment or description of what the time series represents. Click the button to launch a multi-line comment editor if
more than one line is needed.
2. Select whether to use an external file as the source of the data or to enter the data directly into the form's data entry grid.
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3. If the external file option is selected, click the button to locate the
file's name. The file's contents must be formatted in the same manner as
the direct data entry option discussed below. See the description of
Time Series Files in Section 14.6 for details.
4. For direct data entry, enter values in the data entry grid as follows:
Date Column Optional date (in month/day/year format) of the time
series values (only needed at points in time where a new date
occurs).
Time Column If dates are used, enter the military time of day for
each time series value (as hours:minutes or decimal hours). If
dates are not used, enter time as hours since the start of the
simulation.
Value Column The time series’s numerical values. A graphical plot
of the data in the grid can be viewed in a separate window by
clicking the View button. Right clicking over the grid will make
a popup Edit menu appear. It contains commands to cut, copy,
insert, and paste selected cells in the grid as well as options to
insert or delete a row.
5. Press OK to accept the time series or Cancel to cancel your edits.
Note that there are two methods for describing the occurrence time of time
series data:
• as calendar date/time of day (which requires that at least one date, at the
start of the series, be entered in the Date column); and
• as elapsed hours since the start of the simulation (where the Date column remains empty).
7.19 Title/Notes Editor
The Title/Notes editor is invoked when a project’s Title/Notes data category is
selected for editing. As shown below, the editor contains a multi-line edit field
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for entering a description of a project. It also contains a check box used to indicate whether or not the first line of notes should be used as a header for printing.
7.20 Transect Editor
The Transect Editor is invoked when a new transect object is created or an existing transect selected for editing. It contains the following data entry fields.
Name
The name assigned to the transect.
Description
An optional comment or description of the transect.
Station/Elevation Data Grid
Values of distance from the left side of the channel along with the corresponding
elevation of the channel bottom as one moves across the channel from left to
right, looking in the downstream direction. Up to 1500 data values can be entered.
Roughness
Values of Manning's roughness for the left and right overbanks, and main channel portion of the transect. The values can be 0 if no overbank exists.
Bank Stations
The distance values appearing in the Station/Elevation grid that mark the end of
the left overbank and the start of the right overbank. Use 0 to denote the absence
of an overbank.
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Modifiers
The Stations modifier is a factor by which the distance between each station will
be multiplied when the transect data is processed by SWMM. Use a value of 0 if
no such factor is needed.
The Elevations modifier is a constant value that will be added to each elevation value.
The Meander modifier is the ratio of the length of a meandering main channel to the length of the overbank area that surrounds it. This modifier is applied
to all conduits that use this particular transect for their cross section. It assumes
that the length supplied for these conduits is that of the longer main channel.
SWMM will use the shorter overbank length in its calculations while increasing
the main channel roughness to account for its longer length. The modifier is ignored if it is left blank or set to 0.
Right-clicking over the Data Grid will make a popup Edit menu appear. It
contains commands to cut, copy, insert, and paste selected cells in the grid as
well as options to insert or delete a row.
Clicking the View button will bring up a window that illustrates the shape of
the transect cross section.
7.21 Treatment Editor
The Treatment Editor is invoked whenever the Treatment property of a node is
selected from the Property Editor. It displays a list of the project's pollutants
with an edit box next to each. Enter a valid treatment expression in the box next
to each pollutant which receives treatment. Refer to the Treatment topic in
Chapter 5, section 5.3.10 to see what constitutes a valid treatment expression.
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7.22 Unit Hydrograph Editor
The Unit Hydrograph Editor is invoked whenever a new unit hydrograph object
is created or an existing one is selected for editing. It is used to specify the shape
parameters and rain gage for a group of triangular unit hydrographs. These hydrographs are used to compute rainfall-derived infiltration/inflow (RDII) flow at
selected nodes of the drainage system. A UH group can contain up to 12 sets of
unit hydrographs (one for each month of the year), and each set can consist of up
to 3 individual hydrographs (for short-term, intermediate-term, and long-term
responses, respectively) as well as parameters that describe any initial abstraction losses. The editor contains the following data entry fields.
Name of UH Group
Enter the name assigned to the UH Group.
Rain Gage
Type in (or select from the dropdown list) the name of the rain gage that supplies rainfall data to the unit hydrographs in the group.
Hydrographs For
Select a month from the dropdown list box for which hydrograph parameters
will be defined. Select All Months to specify a default set of hydrographs that
apply to all months of the year. Then select specific months that need to have
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special hydrographs defined. Months listed with a (*) next to them have had
hydrographs assigned to them.
Unit Hydrographs
Select this tab to provide the R-T-K shape parameters for each set of unit hydrographs in selected months of the year. The first row is used to specify
parameters for a short-term response hydrograph (i.e., small value of T), the second for a medium-term response hydrograph, and the third for a long-term
response hydrograph (largest value of T). It is not required that all three hydrographs be defined and the sum of the three R-values do not have to equal 1.
The shape parameters for each UH consist of:
R: the fraction of rainfall volume that enters the sewer system
T: the time from the onset of rainfall to the peak of the UH in hours
K: the ratio of time to recession of the UH to the time to peak
Initial Abstraction Depth
Select this tab to provide parameters that describe how rainfall will be reduced
by any initial abstraction depth available (i.e. interception and depression storage) before it is processed through the unit hydrographs defined for a specific
month of the year. Different initial abstraction parameters can be assigned to
each of the three unit hydrograph responses. These parameters are:
Dmax: the maximum depth of initial abstraction available (in rain depth
units)
Drec: the rate at which any utilized initial abstraction is made available
again (in rain depth units per day)
Do: the amount of initial abstraction that has already been utilized at the
start of the simulation (in rain depth units).
If a grid cell is left empty its corresponding parameter value is assumed to be
zero. Right-clicking over a data entry grid will make a popup Edit menu appear.
It contains commands to cut, copy, and paste text to or from selected cells in the
grid.
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Chapter 8
Working with Projects
Project files contain all of the information used to model a study area. They
are usually named with an INP extension. This section describes how to create, open, and save EPA SWMM projects as well as setting their default
properties.
8.1 Creating a New Project
To create a new project:
1. Select File >> New from the Main Menu or click on the Standard
Toolbar.
2. You will be prompted to save the existing project (if changes were
made to it) before the new project is created.
3. A new, unnamed project is created with all options set to their default values.
A new project is automatically created whenever EPA SWMM first begins.
If you are going to use a backdrop image with automatic area and length
calculation, then it is recommended that you set the map dimensions immediately after creating the new project (see Setting the Map's Dimensions).
8.2 Opening an Existing Project
To open an existing project stored on disk:
1. Either select File >> Open from the Main Menu or click on the
Standard Toolbar.
2. You will be prompted to save the current project (if changes were
made to it).
3. Select the file to open from the Open File dialog form that will appear.
4. Click Open to open the selected file.
To open a project that was worked on recently:
1. Select File >> Reopen from the Main Menu.
2. Select a file from the list of recently used files to open.
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8.3 Saving a Project
To save a project under its current name either select File >> Save from the
Main Menu or click on the Standard Toolbar.
To save a project using a different name:
1. Select File >> Save As from the Main Menu.
2. A standard File Save dialog form will appear from which you can
select the folder and name that the project should be saved under.
8.4 Setting Project Defaults
Each project has a set of default values that are used unless overridden by the
SWMM user. These values fall into three categories:
• Default ID labels (labels used to identify nodes and links when they
are first created)
• Default subcatchment properties (e.g., area, width, slope, etc.)
• Default node/link properties (e.g., node invert, conduit length, routing method).
To set default values for a project:
1. Select Project >> Defaults from the Main Menu.
2. A Project Defaults dialog will appear with three pages, one for each
category listed above.
3. Check the box in the lower left of the dialog form if you want to
save your choices for use in all new future projects as well.
4. Click OK to accept your choice of defaults.
The specific items for each category of defaults will be discussed next.
Default ID Labels
The ID Labels page of the Project Defaults dialog form is used to determine how
SWMM will assign default ID labels for the visual project components when
they are first created. For each type of object you can enter a label prefix in the
corresponding entry field or leave the field blank if an object's default name will
simply be a number. In the last field you can enter an increment to be used when
adding a numerical suffix to the default label. As an example, if C were used as
a prefix for Conduits along with an increment of 5, then as conduits are created
they receive default names of C5, C10, C15 and so on. An object’s default name
can be changed by using the Property Editor for visual objects or the objectspecific editor for non-visual objects.
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Default Subcatchment Properties
The Subcatchment page of the Project Defaults dialog sets default property values for newly created subcatchments. These properties include:
• Subcatchment Area
• Characteristic Width
• Slope
• % Impervious
• Impervious Area Roughness
• Pervious Area Roughness
• Impervious Area Depression Storage
• Pervious Area Depression Storage
• % of Impervious Area with No Depression Storage
• Infiltration Method
The default properties of a subcatchment can be modified later by using the
Property Editor.
Default Node/Link Properties
The Nodes/Links page of the Project Defaults dialog sets default property values
for newly created nodes and links. These properties include:
• Node Invert Elevation
• Node Maximum Depth
• Node Ponded Area
• Conduit Length
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• Conduit Shape and Size
• Conduit Roughness
• Flow Units
• Link Offsets Convention
• Routing Method
• Force Main Equation
The defaults automatically assigned to individual objects can be changed by
using the object’s Property Editor. The choice of Flow Units and Link Offsets
Convention can be changed directly on the main window’s Status Bar.
8.5 Measurement Units
SWMM can use either U.S. units or SI metric units. The choice of flow units
determines what unit system is used for all other quantities:
• selecting CFS (cubic feet per second), GPM (gallons per minutes),
or MGD (million gallons per day) for flow units implies that US
unitswill be used throughout
• selecting CMS (cubic meters per second), LPS (liters per second),
or MLD (million liters per day) as flow units implies that SI
unitswill be used throughout.
Flow units can be selected directly on the main window's Status Bar or by
setting a project's default values. In the latter case the selection can be saved so
that all new future projects will automatically use those units.
The units of previously entered data are not automatically adjusted if
the unit system is changed.
8.6 Link Offset Conventions
Conduits and flow regulators (orifices, weirs, and outlets) can be offset some
distance above the invert of their connecting end nodes as depicted below:
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There are two different conventions available for specifying the location of
these offsets. The Depth convention uses the offset distance from the node's invert (distance between ① and ② in the figure above). The Elevation convention
uses the absolute elevation of the offset location (the elevation of point ① in the
figure). The choice of convention can be made on the Status Bar of SWMM's
main window or on the Node/Link Properties page of the Project Defaults dialog. When this convention is changed, a dialog will appear giving one the option
to automatically re-calculate all existing link offsets in the current project using
the newly selected convention.
8.7 Calibration Data
SWMM can compare the results of a simulation with measured field data in its
Time Series Plots, which are discussed in Chapter 12, section 12.4. Before
SWMM can use such calibration data they must be entered into a specially formatted text file and registered with the project.
Calibration Files
Calibration Files contain measurements of a single parameter at one or more
locations that can be compared with simulated values in Time Series Plots. Separate files can be used for each of the following parameters:
• Subcatchment Runoff
• Subcatchment Pollutant Washoff
• Groundwater Flow
• Groundwater Elevation
• Snow Pack Depth
• Node Depth
• Node Lateral Inflow
• Node Flooding
• Node Water Quality
• Link Flow Rate
The format of the file is described in Chapter 14, section 14.5.
Registering Calibration Data
To register calibration data residing in a Calibration File:
1. Select Project >> Calibration Data from the Main Menu.
2. In the Calibration Data dialog form shown below, click in the box
next to the parameter (e.g. node depth, link flow, etc.) whose calibration data will be registered.
3. Either type in the name of a Calibration File for this parameter or
click the Browse button to search for it.
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4. Click the Edit button if you want to open the Calibration File in
Windows NotePad for editing.
5. Repeat steps 2 - 4 for any other parameters that have calibration data.
6. Click OK to accept your selections.
8.8 Viewing all Project Data
A listing of all project data (with the exception of map coordinates) can be
viewed in a non-editable window, formatted for input to SWMM's computational engine. This can be useful for checking data consistency and to make sure that
no key components are missing. To view such a listing, select Project >> Details from the Main Menu. The format of the data in this listing is the same as
that used when the file is saved to disk. It is described in detail in Chapter 17,
section 17.2.
Chapter 9
Working with Objects
SWMM uses various types of objects to model a drainage area and its conveyance system. This section describes how these objects can be created,
selected, edited, deleted, and repositioned.
9.1 Types of Objects
SWMM contains both physical objects that can appear on its Study Area Map,
and non-physical objects that encompass design, loading, and operational information. These objects, which are listed in the Data Browser and were described
in Chapter 5, consist of the following:
Project Title/Notes
Simulation Options
Climatology
Rain Gages
Subcatchments
Aquifers
Snow Packs
Unit Hydrographs
LID Controls
Nodes
Links
Transects
Controls
Pollutants
Land Uses
Curves
Time Series
Time Patterns
Map Labels
9.2 Adding Objects
Visual objects are those that can appear on the Study Area Map and include
Rain Gages, Subcatchments, Nodes, Links, and Map Labels. With the exception
of Map Labels, there are two ways to add these objects into a project:
• selecting the object’s icon from the Object Toolbar and then clicking
on the map,
• selecting the object’s category in the Data Browser and clicking the
Browser’s button.
The first method makes the object appear on the map and is therefore recommended. With the second method, the object will not appear on the map until
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X,Y coordinates are entered manually by editing the object’s properties. What
follows are more specific instructions for adding each type of object to a project.
Adding a Rain Gage
To add a Rain Gage using the Object Toolbar:
1. Click on the toolbar.
2. Move the mouse to the desired location on the map and click.
To add a Rain Gage using the Data Browser:
1. Select Rain Gages from the list of categories.
2. Click the button.
3. Enter the rain gage's X and Y coordinates in the Property Editor if
you want it to appear on the study area map. Adding a Subcatchment
To add a Subcatchment using the Object Toolbar:
1. Click
on the toolbar.
2. Use the mouse to draw a polygon outline of the subcatchment on the
map:
3. left-click at each vertex
4. right-click or press <Enter> to close the polygon
5. press the <Esc> key if you wish to cancel the action.
To add a Subcatchment using the Data Browser:
1. Select Subcatchments from the list of object categories.
2. Click the button.
3. Enter the X and Y coordinates of the subcatchment's centroid in the
Property Editor if you want it to appear on the study area map.
Adding a Node
To add a Node using the Object Toolbar:
1. Click the button for the type of node to add (if its not already depressed):
for a junction
for an outfall
for a flow divider
for a storage unit.
2. Move the mouse to the desired location on the map and click.
To add a Node using the Data Browser:
1. Select the type of node (Junction, Outfall, Flow Divider, or Storage
Unit from the categories list of the Data Browser.
2. Click the button.
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3. Enter the node's X and Y coordinates in the Property Editor if you
want it to appear on the study area map.
Adding a Link
To add a Link using the Object Toolbar:
1. Click the button corresponding to the type of link to add (if its not
already depressed):
for a Conduit
for a Pump
for an Orifice
for a Weir
for an Outlet.
2. On the study area map, click the mouse on the link's inlet (upstream)
node.
3. Move the mouse in the direction of the link's outlet (downstream)
node, clicking at all intermediate points needed to define the link
alignment.
4. Click the mouse a final time over the link's outlet (downstream) node.
Pressing the right mouse button or the <Esc> key while drawing a link will
cancel the operation.
To add a Link using the Data Browser:
1. Select the type of link to add from the categories listed in the Data
Browser.
2. Click the button.
3. Enter the names of the inlet and outlet nodes of the link in the Property Editor.
Adding a Map Label
To add a text label to the Study Area Map:
1. Click the Text button on the Object Toolbar.
2. Click the mouse on the map where the top left corner of the label
should appear.
3. Enter the text for the label.
4. Press <Enter> to accept the label or <Esc> to cancel.
Adding a Non-visual Object
To add an object belonging to a class that is not displayable on the Study Area
Map (which includes Climatology, Aquifers, Snow Packs, LID controls, Unit
Hydrographs, Transects, Control Rules, Pollutants, Land Uses, Curves, Time
Series, and Time Patterns):
1. Select the object's category from the list in the Data Browser.
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2. Click the button.
3. Edit the object's properties in the special editor dialog form that appears (see Chapter 7 for descriptions of these editors).
9.3 Selecting and Moving Objects
To select an object on the map:
1. Make sure that the map is in Selection mode (the mouse cursor has
the shape of an arrow pointing up to the left). To switch to this
mode, either click the Select Object button on the Map Toolbar
or choose Edit >> Select Object from the Main Menu.
2. Click the mouse over the desired object on the map.
To select an object using the Data Browser:
1. Select the object’s category from the upper list in the Browser.
2. Select the object from the lower list in the Browser.
Rain gages, subcatchments, and nodes can be moved to another location on the
Study Area Map. To move an object to another location:
1. Select the object on the map.
2. With the left mouse button held down over the object, drag it to its
new location.
3. Release the mouse button.
The following alternative method can also be used:
1. Select the object to be moved from the Data Browser (it must either
be a rain gage, subcatchment, node, or map label).
2. With the left mouse button held down, drag the item from the Items
list box of the Data Browser to its new location on the map.
3. Release the mouse button.
Note that the second method can be used to place objects on the map that were
imported from a project file that had no coordinate information included in it.
9.4 Editing Objects
To edit an object appearing on the Study Area Map:
1. Select the object on the map.
2. If the Property Editor is not visible either:
double click on the object
or right-click on the object and select Properties from the popup menu that appears
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or click on in the Data Browser.
3. Edit the object’s properties in the Property Editor.
Chapter 16 lists the properties associated with each of SWMM’s visual objects.
To edit an object listed in the Data Browser:
1. Select the object in the Data Browser.
2. Either:
• click on in the Data Browser,
• or double-click the item in the Objects list,
• or press the <Enter> key.
Depending on the class of object selected, a special property editor will appear
in which the object’s properties can be modified. Chapter 7 describes all of the
special property editors used with SWMM’s non-visual objects.
The unit system in which object properties are expressed depends on
the choice of units for flow rate. Using a flow rate expressed in cubic
feet, gallons or acre-feet implies that US units will be used for all quantities. Using a flow rate expressed in liters or cubic meters means that
SI metric units will be used. Flow units are selected either from the project’s default Node/Link properties (see Section 9.4) or directly from
the main window’s Status Bar (see Section 6.4). The units used for all
properties are listed in Chapter 24 Useful Tables, Section 24.1.
9.5 Converting an Object
It is possible to convert a node or link from one type to another without having
to first delete the object and add a new one in its place. An example would be
converting a Junction node into an Outfall node, or converting an Orifice link
into a Weir link. To convert a node or link to another type:
1. Right-click the object on the map.
2. Select Convert To from the popup menu that appears.
3. Select the new type of node or link to convert to from the sub-menu
that appears.
4. Edit the object to provide any data that was not included with the
previous type of object.
Only data that is common to both types of objects will be preserved after an
object is converted to a different type. For nodes this includes its name, position,
description, tag, external inflows, treatment functions, and invert elevation. For
links it includes just its name, end nodes, description, and tag.
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9.6 Copying and Pasting Objects
The properties of an object displayed on the Study Area Map can be copied and
pasted into another object from the same category.
To copy the properties of an object to SWMM's internal clipboard:
1. Right-click the object on the map.
2. Select Copy from the pop-up menu that appears.
To paste copied properties into an object:
1. Right-click the object on the map.
2. Select Paste from the pop-up menu that appears.
Only data that can be shared between objects of the same type can be copied
and pasted. Properties not copied include the object's name, coordinates, end
nodes (for links), tag property and any descriptive comment associated with the
object. For Map Labels, only font properties are copied and pasted.
9.7 Shaping and Reversing Links
Links can be drawn as polylines containing any number of straight-line segments that define the alignment or curvature of the link. Once a link has been
drawn on the map, interior points that define these line segments can be added,
deleted, and moved. To edit the interior points of a link:
1. Select the link to edit on the map and put the map in Vertex Selection mode either by clicking on the Map Toolbar, selecting Edit
>> Select Vertex from the Main Menu, or right clicking on the link
and selecting Vertices from the popup menu.
2. The mouse pointer will change shape to an arrow tip, and any existing vertex points on the link will be displayed as small open
squares. The currently selected vertex will be displayed as a filled
square. To select a particular vertex, click the mouse over it.
3. To add a new vertex to the link, right-click the mouse and select
Add Vertex from the popup menu (or simply press the <Insert>
key on the keyboard).
4. To delete the currently selected vertex, right-click the mouse and select Delete Vertex from the popup menu (or simply press the
<Delete> key on the keyboard).
5. To move a vertex to another location, drag it to its new position
with the left mouse button held down.
While in Vertex Selection mode you can begin editing the vertices for another link by simply clicking on the link. To leave Vertex Selection mode, right-
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click on the map and select Quit Editing from the popup menu, or simply select
one of the other buttons on the Map Toolbar.
A link can also have its direction reversed (i.e. its end nodes switched) by
right clicking on it and selecting Reverse from the pop-up menu that appears.
Normally, links should be oriented so that the upstream end is at a higher elevation than the downstream end.
9.8 Shaping a Subcatchment
Subcatchments are drawn on the Study Area Map as closed polygons. To edit or
add vertices to the polygon, follow the same procedures used for links. If the
subcatchment is originally drawn or is edited to have two or less vertices, then
only its centroid symbol will be displayed on the Study Area Map.
9.9 Deleting an Object
To delete an object:
1. Select the object on the map or from the Data Browser.
2. Either click the
button on the Data Browser or press the <Delete> key on the keyboard, or right-click the object on the map and
select Delete from the pop-up menu that appears.
You can require that all deletions be confirmed before they take effect.
See the General Preferences page of the Program Preferences dialog
box described in Chapter 6, section 6.9.
9.10 Editing or Deleting a Group of Objects
A group of objects located within an irregular region of the Study Area Map can
have a common property edited or be deleted all together. To select such a group
of objects:
1. Choose Edit >> Select Region from the Main Menu or click on
the Map Toolbar.
2. Draw a polygon around the region of interest on the map by clicking the left mouse button at each successive vertex of the polygon.
3. Close the polygon by clicking the right button or by pressing the
<Enter> key; cancel the selection by pressing the <Esc> key.
To select all objects in the project, whether in view or not, select Edit >> Select All from the Main Menu.
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Once a group of objects has been selected, you can edit a common property
shared among them:
1. Select Edit >> Group Edit from the Main Menu.
2. Use the Group Editor dialog that appears to select a property and
specify its new value.
The Group Editor dialog, shown below, is used to modify a property for a selected group of objects. To use the dialog:
1. Select a class of object (Subcatchments, Infiltration, Junctions,
Storage Units, or Conduits) to edit.
2. Check the “with Tag equal to” box if you want to add a filter that
will limit the objects selected for editing to those with a specific
Tag value. (For Infiltration, the Tag will be that of the subcatchment
to which the infiltration parameters belong.)
3. Enter a Tag value to filter on if you have selected that option.
4. Select the property to edit.
5. Select whether to replace, multiply, or add to the existing value of
the property. Note that for some non-numerical properties the only
available choice is to replace the value.
6. In the lower-right edit box, enter the value that should replace, multiply, or be added to the existing value for all selected objects. Some
properties will have an ellipsis button displayed in the edit box
which should be clicked to bring up a specialized editor for the
property.
7. Click OK to execute the group edit.
To delete the objects located within a selected area of the map, select Edit
>> Group Delete from the Main Menu. Then select the categories of objects
you wish to delete from the dialog box that appears. As an option, you can specify that only objects within the selected area that have a specific Tag property
should be deleted. Keep in mind that deleting a node will also delete any links
connected to the node.
Chapter 10
Working with the Map
USEPA SWMM can display a map of the study area being modeled. This section
describes how you can manipulate this map to enhance your visualization of the
system.
10.1 Selecting a Map Theme
A map theme displays object properties in color-coded fashion on the Study Area Map. The dropdown list boxes on the Map Browser are used for selecting a
theme to display for Subcatchments, Nodes and Links.
Methods for changing the color-coding associated with a theme are discussed
in section 10.9 below.
10.2 Setting the Map’s Dimensions
The physical dimensions of the map can be defined so that map coordinates can
be properly scaled to the computer’s video display. To set the map's dimensions:
1. Select View >> Dimensions from the Main Menu.
2. Enter coordinates for the lower-left and upper-right corners of the
map into the Map Dimensions dialog (see below) that appears or
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click the Auto-Size button to automatically set the dimensions based
on the coordinates of the objects currently included in the map.
3. Select the distance units to use for these coordinates.
4. If the Auto-Length option is in effect, check the “Re-compute all
lengths and areas” box if you would like SWMM to re-calculate all
conduit lengths and subcatchment areas under the new set of map
dimensions.
5. Click the OK button to resize the map.
If you are going to use a backdrop image with the automatic distance
and area calculation feature, then it is recommended that you set the
map dimensions immediately after creating a new project. Map distance
units can be different from conduit length units. The latter (feet or meters) depend on whether flow rates are expressed in US or metric units.
SWMM will automatically convert units if necessary.
10.3 Utilizing a Backdrop Image
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SWMM can display a backdrop image behind the Study Area Map. The backdrop image might be a street map, utility map, topographic map, site
development plan, or any other relevant picture or drawing. For example, using
a street map would simplify the process of adding sewer lines to the project
since one could essentially digitize the drainage system's nodes and links directly on top of it.
The backdrop image must be a Windows metafile, bitmap, or JPEG image
created outside of SWMM. Once imported, its features cannot be edited, although its scale and viewing area will change as the map window is zoomed and
panned. For this reason metafiles work better than bitmaps or JPEGs since they
will not loose resolution when re-scaled. Most CAD and GIS programs have the
ability to save their drawings and maps as metafiles.
Selecting View >> Backdrop from the Main Menu will display a sub-menu
with the following commands:
• Load (loads a backdrop image file into the project)
• Unload (unloads the backdrop image from the project)
• Align (aligns the drainage system schematic with the backdrop)
• Resize (resizes the map dimensions of the backdrop)
• Watermark (toggles the backdrop image appearance between normal and lightened)
To load a backdrop image, select View >> Backdrop >> Load from the
Main Menu. A Backdrop Image Selector dialog form will be displayed. The entries on this form are as follows:
Backdrop Image File
Enter the name of the file that contains the image. You can click the
button
to bring up a standard Windows file selection dialog from which you can search
for the image file.
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World Coordinates File
If a “world” file exists for the image, enter its name here, or click the
button
to search for it. A world file contains geo-referencing information for the image
and can be created from the software that produced the image file or by using a
text editor. It contains six lines with the following information:
Line 1:
real world width of a pixel in the horizontal direction.
Line 2:
X rotation parameter (not used).
Line 3:
Y rotation parameter (not used).
Line 4:
negative of the real world height of a pixel in the vertical
direction.
Line 5:
real world X coordinate of the upper left corner of the image.
Line 6:
real world Y coordinate of the upper left corner of the image.
If no world file is specified, then the backdrop will be scaled to fit into the
center of the map display window.
Scale Map to Backdrop Image
This option is only available when a world file has been specified. Selecting it
forces the dimensions of the Study Area Map to coincide with those of the backdrop image. In addition, all existing objects on the map will have their
coordinates adjusted so that they appear within the new map dimensions yet
maintain their relative positions to one another. Selecting this option may then
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require that the backdrop be re-aligned so that its position relative to the drainage area objects is correct. How to do this is described below.
The backdrop image can be re-positioned relative to the drainage system by
selecting View >> Backdrop >> Align. This allows the backdrop image to be
moved across the drainage system (by moving the mouse with the left button
held down) until one decides that it lines up properly.
The backdrop image can also be resized by selecting View >> Backdrop >>
Resize. In this case the following Backdrop Dimensions dialog will appear.
The dialog lets you manually enter the X,Y coordinates of the backdrop’s
lower left and upper right corners. The Study Area Map’s dimensions are also
displayed for reference. While the dialog is visible you can view map coordinates by moving the mouse over the map window and noting the X,Y values
displayed in SWMM’s Status Panel (at the bottom of the main window).
Selecting the Resize Backdrop Image Only button will resize only the
backdrop, and not the Study Area Map, according to the coordinates specified.
Selecting the Scale Backdrop Image to Map button will position the backdrop
image in the center of the Study Area Map and have it resized to fill the display
window without changing its aspect ratio. The map's lower left and upper right
coordinates will be placed in the data entry fields for the backdrop coordinates,
and these fields will become disabled. Selecting Scale Map to Backdrop Image
makes the dimensions of the map coincide with the dimensions being set for the
backdrop image. Note that this option will change the coordinates of all objects
currently on the map so that their positions relative to one another remain unchanged. Selecting this option may then require that the backdrop be re-aligned
so that its position relative to the drainage area objects is correct.
Exercise caution when selecting the Scale Map to Backdrop Image
option in either the Backdrop Image Selector dialog or the Backdrop
Dimensions dialog as it will modify the coordinates of all existing objects currently on the Study Area Map. You might want to save your
project before carrying out this step in case the results are not what you
expected.
The name of the backdrop image file and its map dimensions are saved along
with the rest of a project’s data whenever the project is saved to file.
For best results in using a backdrop image:
• Use a metafile, not a bitmap.
• If the image is loaded before any objects are added to the project then
scale the map to it.
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10.4 Measuring Distances
To measure a distance or area on the Study Area Map:
Click on the Map Toolbar.
1. Left-click on the map where you wish to begin measuring from.
2. Move the mouse over the distance being measured, left-clicking at
each intermediate location where the measured path changes direction.
3. Right-click the mouse or press <Enter> to complete the measurement.
4. The distance measured in project units (feet or meters) will be displayed in a dialog box. If the last point on the measured path
coincides with the first point then the area of the enclosed polygon
will also be displayed.
10.5 Zooming the Map
To Zoom In on the Study Area Map:
1. Select View >> Zoom In from the Main Menu or click
on the
Map Toolbar.
2. To zoom in 100% (i.e., 2X), move the mouse to the center of the
zoom area and click the left button.
3. To perform a custom zoom, move the mouse to the upper left corner
of the zoom area and with the left button pressed down, draw a rectangular outline around the zoom area. Then release the left button.
To Zoom Out on the Study Area Map:
1. Select View >> Zoom Out from the Main Menu or click on the
Map Toolbar.
2. The map will be returned to the view in effect at the previous zoom
level.
10.6 Panning the Map
To pan across the Study Area Map window:
1. Select View >> Pan from the Main Menu or click
on the Map
Toolbar.
2. With the left button held down over any point on the map, drag the
mouse in the direction you wish to pan in.
3. Release the mouse button to complete the pan.
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To pan using the Overview Map (which is described in Section 10.10 below):
1. If not already visible, bring up the Overview Map by selecting View
>> Overview Map from the Main Menu.
2. If the Study Area Map has been zoomed in, an outline of the current
viewing area will appear on the Overview Map. Position the mouse
within this outline on the Overview Map.
3. With the left button held down, drag the outline to a new position.
4. Release the mouse button and the Study Area Map will be panned
to an area corresponding to the outline on the Overview Map.
10.7 Viewing at Full Extent
To view the Study Area Map at full extent, either:
• select View >> Full Extent from the Main Menu, or
• press on the Map Toolbar.
10.8 Finding an Object
To find an object on the Study Area Map whose name is known:
1. Select View >> Find Object from the Main Menu or click
on
the Standard Toolbar.
2. In the Map Finder dialog that appears, select the type of object to
find and enter its name.
3. Click the Go button.
If the object exists, it will be highlighted on the map and in the Data Browser. If the map is currently zoomed in and the object falls outside the current
boundaries, the map will be panned so that the object comes into view.
User-assigned object names in SWMM are not case sensitive. E.g.,
NODE123 is equivalent to Node123.
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After an object is found, the Map Finder dialog will also list:
• the outlet connections for a subcatchment
• the connecting links for a node
• the connecting nodes for a link.
10.9 Submitting a Map Query
A Map Query identifies objects on the study area map that meet a specific criterion (e.g. nodes which flood, links with velocity below 2 ft/sec, etc.). It can also
identify which subcatchments have LID controls and which nodes have external
inflows. To submit a map query:
1. Select a time period in which to query the map from the Map
Browser.
2. Select View >> Query or click on the Map Toolbar.
3. Fill in the following information in the Query dialog that appears:
Select whether to search for Subcatchments, Nodes, Links,
LID Subcatchments or Inflow Nodes.
Select a parameter to query or the type of LID or inflow to
locate.
Select the appropriate operator: Above, Below, or Equals.
Enter a value to compare against.
4. Click the Go button. The number of objects that meet the criterion
will be displayed in the Query dialog and each such object will be
highlighted on the Study Area Map.
5. As a new time period is selected in the Browser, the query results
are automatically updated.
6. You can submit another query using the dialog box or close it by
clicking the button in the upper right corner.
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After the Query box is closed the map will revert to its original display.
10.10 Using the Map Legends
Map Legends associate a color with a range of values
for the current theme being viewed. Separate legends
exist for Subcatchments, Nodes, and Links. A
Date/Time Legend is also available for displaying the
date and clock time of the simulation period being
viewed on the map.
To display or hide a map legend:
1. Select View >> Legends from the Main Menu or right-click on the
map and select Legends from the pop-up menu that appears
2. Click on the type of legend whose display should be toggled on or
off.
A visible legend can also be hidden by double clicking on it.
To move a legend to another location press the left mouse button over the
legend, drag the legend to its new location with the button held down, and then
release the button.
To edit a legend, either select View >> Legends >> Modify from the Main
Menu or right-click on the legend if it is visible. Then use the Legend Editor
dialog that appears to modify the legend's colors and intervals.
The Legend Editor is used to set numerical ranges to which different colors
are assigned for viewing a particular parameter on the network map. It works as
follows:
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Numerical values, in increasing order, are entered in the edit boxes
to define the ranges. Not all four boxes need to have values.
To change a color, click on its color band in the Editor and then select a new color from the Color Dialog that will appear.
Click the Auto-Scale button to automatically assign ranges based
on the minimum and maximum values attained by the parameter in
question at the current time period.
The Color Ramp button is used to select from a list of built-in color
schemes.
The Reverse Colors button reverses the ordering of the current set
of colors (the color in the lowest range becomes that of the highest
range and so on).
Check Framed if you want a frame drawn around the legend.
10.11 Using the Overview Map
The Overview Map allows one to see where in terms of the overall system the
main Study Area Map is currently focused. This zoom area is depicted by the
rectangular outline displayed on the Overview Map. As you drag this rectangle
to another position the view within the main map will be redrawn accordingly.
The Overview Map can be toggled on and off by selecting View >> Overview
Map from the Main Menu. The Overview Map window can also be dragged to
any position as well as be re-sized.
10.12 Setting Map Display Options
The Map Options dialog (shown below) is used to change the appearance of the
Study Area Map. There are several ways to invoke it:
• select Tools >> Map Display Options from the Main Menu or,
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click the Options button
on the Standard Toolbar when the
Study Area Map window has the focus or,
right-click on any empty portion of the map and select Options
from the popup menu that appears.
The dialog contains a separate page, selected from the panel on the left side of
the form, for each of the following display option categories:
• Subcatchments (controls fill style, symbol size, and outline thickness of subcatchment areas)
• Nodes (controls size of nodes and making size be proportional to
value)
• Links (controls thickness of links and making thickness be proportional to value)
• Labels (turns display of map labels on/off)
• Annotation (displays or hides node/link ID labels and parameter
values)
• Symbols (turns display of storage unit, pump, and regulator symbols
on/off)
• Flow Arrows (selects visibility and style of flow direction arrows)
• Background (changes color of map's background).
Subcatchment Options
The Subcatchments page of the Map Options dialog controls how subcatchment
areas are displayed on the study area map.
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Option
Fill Style
Symbol Size
Outline Thickness
Display Link to Outlet
Description
Selects style used to fill interior of subcatchment area
Sets the size of the symbol (in pixels) placed at the centroid of a subcatchment area
Sets the thickness of the line used to draw a subcatchment's boundary; set
to zero if no boundary should be displayed
If checked then a dashed line is drawn between the subcatchment centroid
and the subcatchment's outlet node (or outlet subcatchment)
Node Options
The Nodes page of the Map Options dialog controls how nodes are displayed on
the study area map.
Option
Node Size
Proportional to
Value
Display Border
Description
Selects node diameter in pixels
Select if node size should increase as the viewed parameter increases in
value
Select if a border should be drawn around each node (recommended for
light-colored backgrounds)
Link Options
The Links page of the Map Options dialog controls how links are displayed on
the map.
Option
Link Size
Proportional to Value
Display Border
Description
Sets thickness of links displayed on map (in pixels)
Select if link thickness should increase as the viewed parameter increases in value
Check if a black border should be drawn around each link
Label Options
The Labels page of the Map Options dialog controls how user-created map labels are displayed on the study area map.
Option
Use Transparent Text
At Zoom Of
Description
Check to display label with a transparent background (otherwise an
opaque background is used)
Selects minimum zoom at which labels should be displayed; labels
will be hidden at zooms smaller than this
Annotation Options
The Annotation page of the Map Options dialog form determines what kind of
annotation is provided alongside of the objects on the study area map.
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Option
Rain Gage IDs
Subcatch IDs
Node IDs
Link IDs
Subcatch Values
Node Values
Link Values
Use Transparent Text
Description
Check to display rain gage ID names
Check to display subcatchment ID names
Check to display node ID names
Check to display link ID names
Check to display value of current subcatchment variable
Check to display value of current node variable
Check to display value of current link variable
Check to display text with a transparent background (otherwise
an opaque background is used)
Adjusts the size of the font used to display annotation
Selects minimum zoom at which annotation should be displayed; all annotation will be hidden at zooms smaller than this
Font Size
At Zoom Of
Symbol Options
The Symbols page of the Map Options dialog determines which types of objects
are represented with special symbols on the map.
Option
Display Node Symbols
Display Link Symbols
At Zoom Of
Description
If checked then special node symbols will be used
If checked then special link symbols will be used
Selects minimum zoom at which symbols should be displayed;
symbols will be hidden at zooms smaller than this
Flow Arrow Options
The Flow Arrows page of the Map Options dialog controls how flow-direction
arrows are displayed on the map.
Option
Arrow Style
Arrow Size
At Zoom Of
Description
Selects style (shape) of arrow to display (select None to hide arrows)
Sets arrow size
Selects minimum zoom at which arrows should be displayed; arrows will
be hidden at zooms smaller than this
Flow direction arrows will only be displayed after a successful simulation has been made and a computed parameter has been selected for
viewing. Otherwise the direction arrow will point from the userdesignated start node to end node.
Background Options
The Background page of the Map Options dialog offers a selection of colors
used to paint the map’s background with.
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10.13 Exporting the Map
The full extent view of the study area map can be saved to file using either:
• Autodesk's DXF (Drawing Exchange Format) format,
• the Windows enhanced metafile (EMF) format,
• EPA SWMM's own ASCII text (.map) format.
The DXF format is readable by many Computer Aided Design (CAD) programs. Metafiles can be inserted into word processing documents and loaded
into drawing programs for re-scaling and editing. Both formats are vector-based
and will not lose resolution when they are displayed at different scales.
To export the map to a DXF, metafile, or text file:
1. Select File >> Export >> Map.
2. In the Map Export dialog that appears select the format that you
want the map saved in.
If you select DXF format, you have a choice of how nodes will be represented in the DXF file. They can be drawn as filled circles, as open circles, or as
filled squares. Not all DXF readers can recognize the format used in the DXF
file to draw a filled circle. Also note that map annotation, such as node and link
ID labels will not be exported, but map label objects will be.
After choosing a format, click OK and enter a name for the file in the Save
As dialog that appears.
Chapter 11
Running a Simulation
After a study area has been suitably described, its runoff response, flow
routing and water quality behavior can be simulated. This section describes
how to specify options to be used in the analysis, how to run the simulation
and how to troubleshoot common problems that might occur.
11.1 Setting Simulation Options
SWMM has a number of options that control how the simulation of a stormwater drainage system is carried out. To set these options:
1. Select the Options category from the Data Browser.
2. Select one of the following categories of options to edit.
• General Options
• Date Options
• Time Step Options
• Dynamic Wave Routing Options
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• Interface File Options
and click the button to invoke the Simulation Options dialogue
The Simulations Options dialog contains a separate tabbed page for each of
these option categories which are described in more detail below.The following
sections discuss each category of options.
General Options
The General page of the Simulation Options dialog sets values for the following
options.
Process Models
This section allows you to select which of SWMM’s process models will be applied to the current project. For example, a model that contained Aquifer and
Groundwater elements could be run first with the groundwater computations
turned on and then again with them turned off to see what effect this process had
on the site’s hydrology. Note that if there are no elements in the project needed
to model a given process then that process option is disabled (e.g. if there were
no Aquifers defined for the project then the Groundwater check box will appear
disabled in an unchecked state).
Infiltration Model
This option controls how infiltration of rainfall into the upper soil zone of subcatchments is modeled. The choices are:
• Horton
• Green-Ampt
• Curve Number
Changing this option will require re-entering values for the infiltration parameters in each subcatchment. Each of these models is briefly described in
section 5.4.2.
Routing Method
This option determines which method is used to route flows through the conveyance system. The choices are:
• None
• Steady Flow
• Kinematic Wave
• Dynamic Wave
Review section 5.4.5 for a brief description of each of these alternatives.
Allow Ponding
Checking this option will allow excess water to collect atop nodes and be reintroduced into the system as conditions permit. In order for ponding to actually
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occur at a particular node, a non-zero value for its Ponded Area attribute must be
used.
Report Control Actions
Check this option if you want the simulation’s Status Report to list all discrete
control actions taken by the Control Rules associated with a project (continuous
modulated control actions are not listed). This option should only be used for
short-term simulation.
Report Input Summary
Check this option if you want the simulation's Status Report to list a summary of
the project's input data.
Skip Steady State Periods
Checking this option will make the simulation use the most recently computed
conveyance system flows during a steady state period instead of computing a
new flow routing solution. A time step is considered to be in steady state if the
change in external inflows at each node is below 0.5 cfs and the relative difference between total system inflow and outflow is below 5%.
Minimum Conduit Slope
The minimum value allowed for a conduit's slope (%). If blank or zero (the default) then no minimum is imposed (although SWMM uses a lower limit on
elevation drop of 0.001 ft (0.000 35 m) when computing a conduit slope).
Date Options
The Dates page of the Simulation Options dialog determines the starting and
ending dates/times of a simulation.
Start Analysis On
Enter the date (month/day/year) and time of day when the simulation begins.
Start Reporting On
Enter the date and time of day when reporting of simulation results is to begin.
This must be on or after the simulation starting date and time.
End Analysis On
Enter the date and time when the simulation is to end.
Start Sweeping On
Enter the day of the year (month/day) when street sweeping operations begin.
The default is January 1.
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End Sweeping On
Enter the day of the year (month/day) when street sweeping operations end. The
default is December 31.
Antecedent Dry Days
Enter the number of days with no rainfall prior to the start of the simulation.
This value is used to compute an initial buildup of pollutant load on the surface
of subcatchments.
If rainfall or climate data are read from external files, then the simulation dates should be set to coincide with the dates recorded in these files.
Time Step Options
The Time Steps page of the Simulation Options dialog establishes the length of
the time steps used for runoff computation, routing computation and results reporting. Time steps are specified in days and hours:minutes:seconds except for
flow routing which is entered as decimal seconds.
Reporting Time Step
Enter the time interval for reporting of computed results.
Runoff - Wet Weather Time Step
Enter the time step length used to compute runoff from subcatchments during
periods of rainfall or when ponded water still remains on the surface.
Runoff - Dry Weather Time Step
Enter the time step length used for runoff computations (consisting essentially of
pollutant buildup) during periods when there is no rainfall and no ponded water.
This must be greater or equal to the Wet Weather time step.
Routing Time Step
Enter the time step length in decimal seconds used for routing flows and water
quality constituents through the conveyance system. Note that Dynamic Wave
routing requires a much smaller time step than the other methods of flow routing.
Dynamic Wave Options
The Dynamic Wave page of the Simulation Options dialog sets several parameters that control how the dynamic wave flow routing computations are made.
These parameters have no effect for the other flow routing methods.
Inertial Terms
Indicates how the inertial terms in the Saint-Venant momentum equation will be
handled.
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KEEP maintains these terms at their full value under all conditions.
DAMPEN reduces the terms as flow comes closer to being critical
and ignores them when flow is supercritical.
IGNORE drops the terms altogether from the momentum equation,
producing what is essentially a Diffusion Wave solution.
Define Supercritical Flow By
Selects the basis used to determine when supercritical flow occurs in a conduit.
The choices are:
• water surface slope only (i.e., water surface slope > conduit slope)
• Froude number only (i.e., Froude number > 1.0)
• both water surface slope and Froude number.
The first two choices were used in earlier versions of SWMM while the third
choice, which checks for either condition, is now the recommended one.
Force Main Equation
Selects which equation will be used to compute friction losses during pressurized flow for conduits that have been assigned a Circular Force Main crosssection. The choices are either the Hazen-Williams equation or the DarcyWeisbach equation.
Use Variable Time Step
Check the box if an internally computed variable time step should be used at
each routing time period and select an adjustment (or safety) factor to apply to
this time step. The variable time step is computed so as to satisfy the Courant
condition within each conduit. A typical adjustment factor would be 75% to
provide some margin of conservatism. The computed variable time step will not
be less than 0.5 seconds nor be greater than the fixed time step specified on the
Time Steps page of the dialog. If the latter was set lower than 0.5 seconds then
the variable time step option is ignored.
Time Step for Conduit Lengthening
This is a time step, in seconds, used to artificially lengthen conduits so that they
meet the Courant stability criterion under full-flow conditions (i.e., the travel
time of a wave will not be smaller than the specified conduit lengthening time
step). As this value is decreased, fewer conduits will require lengthening. A value of 0 means that no conduits will be lengthened. The ratio of the artificial
length to the original length for each conduit is listed in the Flow Classification
table that appears in the simulation’s Status Report (see Chapter 12, section
12.1).
Minimum Surface Area
This is a minimum surface area used at nodes when computing changes in water
depth. If 0 is entered, then the default value of 12.566 ft2 (1.167 m2) is used.
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This is the area of a 4-ft diameter manhole. The value entered should be in
square feet for US units or square meters for SI units.
File Options
The Interface Files page of the Simulation Options dialog is used to specify
which interface files will be used or saved during the simulation. (Interface files
are described in Chapter 14 Files Used by SWMM.) The page contains a list box
with three buttons underneath it. The list box lists the currently selected files,
while the buttons are used as follows:
Add
adds a new interface file specification to the list.
Edit
edits the properties of the currently selected interface file.
Delete deletes the currently selected interface from the project (but not from
your hard drive).
When the Add or Edit buttons are clicked, an Interface File Selector dialog
appears where you can specify the type of interface file, whether it should be
used or saved, and its name. The entries on this dialog are as follows:
File Type
Select the type of interface file to be specified.
Use / Save Buttons
Select whether the named interface file will be used to supply input to a simulation run or whether simulation results will be saved to it.
File Name
Enter the name of the interface file or click the Browse button
a standard Windows file selection dialog box.
to select from
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187
11.2 Setting Reporting Options
The Reporting Options dialog is used to select individual subcatchments, nodes,
and links that will have detailed time series results saved for viewing after a
simulation has been run. The default for new projects is that all objects will have
detailed results saved for them. The dialog is invoked by selecting the Reporting
category of Options from the Data Browser and clicking the
button
The dialog contains three tabbed pages - one each for subcatchments, nodes,
and links. It is a stay-on-top form which means that you can select items directly
from the Study Area Map or Data Browser while the dialog remains visible.
To include an object in the set that is reported on:
1. Select the tab to which the object belongs (Subcatchments, Nodes
or Links).
2. Unselect the "All" check box if it is currently checked.
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Running a Simulation
3. Select the specific object either from the Study Area Map or from
the listing in the Data Browser.
4. Click the Add button on the dialog.
5. Repeat the above steps for any additional objects.
To remove an item from the set selected for reporting:
1. Select the desired item in the dialog's list box.
2. Click the Remove button to remove the item.
To remove all items from the reporting set of a given object category, select
the object category's page and click the Clear button.
To include all objects of a given category in the reporting set, check the "All"
box on the page for that category (i.e. subcatchments, nodes, or links). This
will override any individual items that may be currently listed on the page.
To dismiss the dialog click the Close button.
11.3 Starting a Simulation
To start a simulation either select Project >> Run Simulation from the Main
Menu or click
on the Standard Toolbar. A Run Status window will appear
which displays the progress of the simulation.
To stop a run before its normal termination, click the Stop button on the Run
Status window or press the <Esc> key. Simulation results up until the time when
the run was stopped will be available for viewing. To minimize the SWMM
program while a simulation is running, click the Minimize button on the Run
Status window.
If the analysis runs successfully the icon will appear in the Run Status section of the Status Bar at the bottom of SWMM’s main window. Any error or
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189
warning messages will appear in a Status Report window. If you modify the project after a successful run has been made, the faucet icon changes to a broken
faucet indicating that the current computed results no longer apply to the modified project.
11.4 Troubleshooting Results
When a run ends prematurely, the Run Status dialog will indicate the run was
unsuccessful and direct the user to the Status Report for details. The Status Report will include an error statement, code, and description of the problem (e.g.,
ERROR 138: Node TG040 has initial depth greater than maximum depth). Consult Chapter 18 for a description of SWMM’s error messages. Even if a run
completes successfully, one should check to insure that the results are reasonable. The following are the most common reasons for a run to end prematurely or
to contain questionable results.
Unknown ID Error Message
This message typically appears when an object references another object that
was never defined. An example would be a subcatchment whose outlet was designated as N29, but no such subcatchment or node with that name exists. Similar
situations can exist for incorrect references made to Curves, Time Series, Time
Patterns, Aquifers, Snow Packs, Transects, Pollutants, and Land Uses.
File Errors
File errors can occur when:
• a file cannot be located on the user's computer
• a file being used has the wrong format
• a file being written cannot be opened because the user does not have
write privileges for the directory (folder) where the file is to be
stored.
SWMM needs to have write privileges for a directory (folder) where temporary files are stored during a run. The original default is the directory where
Windows writes its temporary files. If this directory does not exist or the user
does not have write privileges to it, then a new directory must be assigned by
using the Program Preferences dialog (discussed in Chapter 6, section 6.9).
Drainage System Layout Errors
A valid drainage system layout must obey the following conditions:
• An outfall node can have only one conduit link connected to it.
• A flow divider node must have exactly two outflow links.
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Running a Simulation
•
Under Kinematic Wave routing, a junction node can only have one
outflow link and a regulator link cannot be the outflow link of a
non-storage node.
• Under Dynamic Wave routing there must be at least one outfall
node in the network.
An error message will be generated if any of these conditions are violated.
Excessive Continuity Errors
When a run completes successfully, the mass continuity errors for runoff, flow
routing, and pollutant routing will be displayed in the Run Status window. These
errors represent the percent difference between initial storage + total inflow and
final storage + total outflow for the entire drainage system. If they exceed some
reasonable level, such as 10 percent, then the validity of the analysis results
must be questioned. The most common reasons for an excessive continuity error
are computational time steps that are too long or conduits that are too short.
In addition to the system continuity error, the Status Report produced by a
run (see Chapter 12, section 12.1) will list those nodes of the drainage network
that have the largest flow continuity errors. If the error for a node is excessive,
then one should first consider if the node in question is of importance to the purpose of the simulation. If it is, then further study is warranted to determine how
the error might be reduced.
Unstable Flow Routing Results
Due to the explicit nature of the numerical methods used for Dynamic Wave
routing (and to a lesser extent, Kinematic Wave routing), the flows in some links
or water depths at some nodes may fluctuate or oscillate significantly at certain
periods of time as a result of numerical instabilities in the solution method.
SWMM does not automatically identify when such conditions exist, so it is up to
the user to verify the numerical stability of the model and to determine if the
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Running a Simulation
simulation results are valid for the modeling objectives. Time series plots at key
locations in the network can help identify such situations as can a scatter plot
between a link’s flow and the corresponding water depth at its upstream node
(see Chapter 12, section 12.4, Viewing Results with a Graph).
Numerical instabilities can occur over short durations and may not be apparent when time series are plotted with a long time interval. When detecting such
instabilities, it is recommended that a reporting time step of 1 minute or less be
used, at least for an initial screening of results.
The run’s Status Report lists the links having the five highest values of a
Flow Instability Index (FII). This index counts the number of times that the flow
value in a link is higher (or lower) than the flow in both the previous and subsequent time periods. The index is normalized with respect to the expected number
of such ‘turns’ that would occur for a purely random series of values and can
range from 0 to 150.
As an example of how the Flow Instability Index can be used, consider the
figure shown below. The solid line plots the flow hydrograph for the link identified as having the highest FII value (100) in a dynamic wave flow routing run
that used a fixed time step of 30 seconds. The dashed line shows the hydrograph
that results when a variable time step was used instead, which is now completely
stable.
Flow time series plots for the links having the highest FII’s should be inspected to insure that flow routing results are acceptably stable.
Numerical instabilities under Dynamic Wave flow routing can be reduced
by:
• reducing the routing time step
• utilizing the variable time step option with a smaller time step factor
• selecting to ignore the inertial terms of the momentum equation
• selecting the option to lengthen short conduits.
800
Fixed Time Step
(FII = 100)
Flow (cfs)
600
Variable Time Step
(FII = 0)
400
200
0
0
2
4
6
Time (hours)
8
10
12
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Chapter 12
Viewing Results
This chapter describes the different ways in which the results of a simulation
can be viewed. These include a status report, various map views, graphs, tables,
and a statistical frequency report.
12.1 Viewing a Status Report
A Status Report is available for viewing after each simulation. It contains:
• a summary of the main Simulation Options that are in effect
• a list of any error conditions encountered during the run
• a summary listing of the project’s input data (if requested in the
Simulation Options)
• a summary of the data read from each rainfall file used in the simulation
• a description of each control rule action taken during the simulation
(if requested in the Simulation Options)
• the system-wide mass continuity errors for:
• runoff quantity and quality
• groundwater flow
• conveyance system flow and water quality
• the names of the nodes with the highest individual flow continuity
errrors
• the names of the conduits that most often determined the size of the
time step used for flow routing (only when the Variable Time Step
option is used)
• the names of the links with the highest Flow Instability Index values
• information on the range of routing time steps taken and the percentage of these that were considered steady state.
In addition, the report contains several tables that display summary results
for the quantities of most interest for each subcatchment, node, and link. The
tables and the information they display are listed below.
193
194
Table
Subcatchment Runoff
LID Performanc
Subcatchment Washoff
Node Depths
Node Inflows
Node Surcharging
Node Flooding
Storage Volumes
Outfall Loading
Link Flows
Viewing Results
Columns
Total precipitation (in or mm);
Total run-on from other subcatchments (in or mm);
Total evaporation (in or mm);
Total infiltration (in or mm);
Total runoff depth (in or mm);
Total runoff volume (Mgal or Mliters);
Runoff coefficient (ratio of total runoff to total precipitation).
Total inflow volume
Total evaporation loss
Total infiltration loss
Total surface outflow
Total underdrain outflow
Initial storage volume
Final storage volume
Note: all quantities are expressed as depths (in or mm) over
the LID unit’s surface area.
Total mass of each pollutant washed off the subcatchment (lbs or
kg).
Average water depth (ft or m);
Maximum water depth (ft or m);
Maximum hydraulic head (HGL) elevation (ft or m);
Time of maximum depth.
Maximum lateral inflow (flow units);
Maximum total inflow (flow units);
Time of maximum total inflow;
Total lateral inflow volume (Mgal or Mliters);
Total inflow volume (Mgal or Mliters).
Note: Total inflow consists of lateral inflow plus inflow from connecting links.
Hours surcharged;
Maximum height of surcharge above node’s crown (ft or m);
Minimum depth of surcharge below node’s top rim (ft or m).
Note: surcharging occurs when water rises above the crown of the
highest conduit and only those conduits that surcharge are listed.
Hours flooded;
Maximum flooding rate (flow units);
Time of maximum flooding;
Total flood volume (Mgal or Mliter);
Maximum ponded volume (acre-in or ha-mm).
Note: flooding refers to all water that overflows a node, whether it
ponds or not, and only those nodes that flood are listed.
Average volume of water in the facility (1000 ft3 or 1000 m3);
Average percent of full storage capacity utilized;
Maximum volume of water in the facility (1000 ft3 or 1000 m3);
Maximum percent of full storage capacity utilized;
Time of maximum water stored;
Maximum outflow rate from the facility (flow units).
Percent of time that outfall discharges;
Average discharge flow (flow units);
Maximum discharge flow (flow units);
Total volume of flow discharged (Mgal or Mliters);
Total mass discharged of each pollutant (lbs or kg).
Maximum flow (flow units);
Time of maximum flow;
Viewing Results
Flow Classification
Conduit Surcharging
Pumping Summary
195
Maximum velocity (ft/sec or m/sec)
Ratio of maximum flow to full normal flow;
Ratio of maximum flow depth to full depth.
Ratio of adjusted conduit length to actual length;
Fraction of time spent in the following flow categories:
•
dry on both ends
•
dry on the upstream end
•
dry on the downstream end
•
subcritical flow
•
supercritical flow
•
critical flow at the upstream end
•
critical flow at the downstream end
Average Froude number;
Average change in flow between each time step (flow units).
Hours that conduit is full at:
•
both ends
•
upstream end
•
downstream end
Hours that conduit flows above full normal flow;
Hours that conduit is capacity limited
Note: only conduits with one or more non-zero entries are listed
and a conduit is considered capacity limited if its upstream end is
full and the HGL slope is greater than the conduit slope.
Percent of time that the pump is on line;
Maximum flow pumped (flow units);
Average flow pumped (flow units);
Total energy consumed assuming 100% efficiency (kwatt-hours);
Percent of time that the pump operates off of its pump curve.
The Status Report can be viewed by selecting Report >> Status from the
Main Menu. Its window includes a Bookmarks panel that makes it easy to navigate between the topics listed above.
To copy selected text from the Status Report to a file or to the Windows
Clipboard, first select the text to copy with the mouse and then choose Edit >>
Copy To from the Main Menu (or press the button on the Standard Toolbar).
If the entire report is to be copied then it is not necessary to first select text with
the mouse.
To locate an object that is listed in one of the Status Report's tables, first select the object's name with the mouse and choose Edit >> Find Object from the
Main Menu (or press the button on the Standard Toolbar and select Find Object from the dropdown menu). Then in the Map Finder dialog that appears,
select the type of object to look for (Subcatchment, Node or Link) and press the
Go button (the object's name will have already been entered in the form). The
object will appear highlighted in both the Data Browser and on the Study Area
Map.
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Viewing Results
12.2 Variables that can be Viewed
Computed results at each reporting time step for the following variables are
available for viewing on the map and can be plotted, tabulated, and statistically
analyzed:
Subcatchment Variables
▪
▪
▪
▪
▪
▪
▪
Link Variables
▪
▪
losses (infiltration + evaporation in in/h or ▪
mm/h)
▪
runoff flow (flow units)
▪
groundwater flow into the drainage network
▪
(flow units)
rainfall rate (in/h or mm/h)
flow rate (flow units)
snow depth (inches or millimeters)
average water depth (ft or m)
flow velocity (ft/s or m/s)
Froude number (dimensionless)
capacity (ratio of depth to full depth)
concentration of each pollutant (mass/liter)
groundwater elevation (ft or m)
washoff concentration of each pollutant
(mass/liter)
Node Variables
▪
▪
▪
▪
▪
▪
▪
System-Wide Variables
air temperature (ºF or ºC)
water depth (ft or m above the node invert ▪
▪
evaporation rate (in/d or mm/d)
elevation)
▪
total rainfall (in/h or mm/h)
hydraulic head (ft or m, absolute elevation
▪
total snow depth (inches or millimeters)
per vertical datum)
water volume held in storage (including
ponded water, ft3 or m3)
lateral inflow (runoff + all other external
inflows, in flow units)
total inflow (lateral inflow + upstream inflows, in flow units)
surface flooding (flow lost from the system
when the node’s inflow exceeds its available storage and outflow capacity, flow
units)
concentration of each pollutant after any
treatment applied at the node (mass/liter)
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
average losses (in/h or mm/h)
total runoff flow (flow units)
total dry weather inflow (flow units)
total groundwater inflow (flow units)
total I&I inflow (flow units)
total direct inflow (flow units)
total external inflow (flow units)
total external flooding (flow units)
total outflow from outfalls (flow units)
total nodal storage volume ( ft3 or m3)
12.3 Viewing Results on the Map
There are several ways to view the values of certain input parameters and simulation results directly on the Study Area Map:
• For the current settings on the Map Browser, the subcatchments,
nodes and links of the map will be colored according to their respective Map Legends. The map's color coding will be updated as a
new time period is selected in the Map Browser.
Viewing Results
•
•
•
•
•
197
When the Flyover Map Labeling program preference is selected
(see Chapter 6, section 6.9), moving the mouse over any map object
will display its ID name and the value of its current theme parameter in a hint-style box.
ID names and parameter values can be displayed next to all subcatchments, nodes and/or links by selecting the appropriate options
on the Annotation page of the Map Options dialog (see Chapter 10,
section 10.11).
Subcatchments, nodes or links meeting a specific criterion can be
identified by submitting a Map Query (see Chapter 10, section
10.8).
You can animate the display of results on the network map either
forward or backward in time by using the controls on the Animator
panel of the Map Browser (see Chapter 6, section 6.7).
The map can be printed, copied to the Windows clipboard, or saved
as a DXF file or Windows metafile (see Chapter 10, section 10.12).
12.4 Viewing Results with a Graph
Analysis results can be viewed using several different types of graphs. Graphs
can be printed, copied to the Windows clipboard, or saved to a text file or to a
Windows metafile. The following types of graphs can be created from available
simulation results:
▪
Time
Series
Plot:
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Viewing Results
Water Elevation Profile: Node 81009 - 16009
Profile
Plot:
81009
135
81309
130
Elevation (ft)
▪
140
15009
12516009
120
115
110
105
100
10,000
5,000
Distance (ft)
0
01/01/2002 01:30:00
▪
Scatter
Plot:
You can zoom in or out of any graph by holding down the <Shift> key while
drawing a zoom rectangle with the mouse's left button held down. Drawing the
rectangle from left to right zooms in, drawing it from right to left zooms out.
The plot can also be panned in any direction by holding down the <Ctrl> key
and moving the mouse across the plot with the left button held down
An opened graph will normally be redrawn when a new simulation is run. To
prevent the automatic updating of a graph once a new set of results is computed
you can lock the current graph by clicking the icon in the upper left corner of
the graph. To unlock the graph, click the icon again.
Time Series Plots
A Time Series Plot graphs the value of a particular variable at up to six locations
against time. When only a single location is plotted, and that location has calibration data registered for the plotted variable, then the calibration data will be
plotted along with the simulated results (see Chapter 8, section 8.7 for instructions on how to register calibration data with a project).
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199
To create a Time Series Plot:
1. Select Report >> Graph >> Time Series from the Main Menu or
click on the Standard Toolbar.
2. A Time Series Plot dialog will appear. Use it to describe what objects and quantities should be plotted.
The Time Series Plot dialog describes the objects and variable to be graphed
in a time series plot. Time series for certain system-wide variables, such as total
rainfall, total runoff, total flooding, etc., can also be plotted. Use the dialog as
follows:
1. Select a Start Date and End Date for the plot (the default is the entire simulation period).
2. Choose whether to show time as Elapsed Time or as Date/Time values.
3. Choose an Object Category (Subcatchment, Node, Link, or System)
for plotting.
4. If the object category is not System, identify the objects to plot by:
selecting the object either on the Study Area Map or in the Data Browser
clicking the button on the dialog to add it to the plot,
repeating these steps for any additional objects of the same
category.
5. Select a simulated variable to be plotted. The available choices depend on the category of object selected.
6. Click the OK button to create the plot.
A maximum of 6 objects can be selected for a single plot. Objects already selected can be deleted, moved up in the order or moved down in the order by
clicking the , , and buttons, respectively.
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Viewing Results
Profile Plots
A Profile Plot displays the variation in simulated water depth with distance over
a connected path of drainage system links and nodes at a particular point in time.
Once the plot has been created it will be automatically updated as a new time
period is selected using the Map Browser.
To create a Profile Plot:
1. Select Report >> Graph >> Profile from the main menu or press
on the Standard Toolbar
2. A Profile Plot dialog will appear (see below). Use it to identify the
path along which the profile plot is to be drawn.
The Profile Plot dialog is used to specify a path of connected conveyance
system links along which a water depth profile versus distance should be drawn.
To define a path using the dialog:
1. Enter the ID of the upstream node of the first link in the path in the
Start Node edit field (or click on the node on the Study Area Map
and then on the button next to the edit field).
2. Enter the ID of the downstream node of the last link in the path in
the End Node edit field (or click the node on the map and then click
the button next to the edit field).
3. Click the Find Path button to have the program automatically identify the path with the smallest number of links between the start and
end nodes. These will be listed in the Links in Profile box.
4. You can insert a new link into the Links in Profile list by selecting
the new link either on the Study Area Map or in the Data Browser
and then clicking the button underneath the Links in Profile list
box.
5. Entries in the Links in Profile list can be deleted or rearranged by
using the , , and buttons underneath the list box.
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201
6. Click the OK button to view the profile plot.
To save the current set of links listed in the dialog for future use:
1. Click the Save Current Profile button.
2. Supply a name for the profile when prompted.
To use a previously saved profile:
1. Click the Use Saved Profile button.
2. Select the profile to use from the Profile Selection dialog that appears.
Profile plots can also be created before any simulation results are available,
to help visualize and verify the vertical layout of a drainage system. Plots created in this manner will contain a refresh button
in the upper left corner that
can be used to redraw the plot after edits are made to any elevation data appearing in the plot.
Scatter Plots
A Scatter Plot displays the relationship between a pair of variables, such as flow
rate in a pipe versus water depth at a node. To create a Scatter Plot:
1. Select Report >> Graph >> Scatter from the main menu or press
on the Standard Toolbar
2. Specify what time interval and what pair of objects and their variables to plot using the Scatter Plot dialog that appears.
The Scatter Plot dialog is used to select the objects and variables to be
graphed against one another in a scatter plot. Use the dialog as follows:
1. Select a Start Date and End Date for the plot (the default is the entire simulation period).
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Viewing Results
2. Select the following choices for the X-variable (the quantity plotted
along the horizontal axis):
Object Category (Subcatchment, Node or Link)
Object ID (enter a value or click on the object either on the
Study Area Map or in the Data Browser and then click the
button on the dialog)
Variable to plot (choices depend on the category of object selected).
3. Do the same for the Y-variable (the quantity plotted along the vertical axis).
4. Click the OK button to create the plot.
12.5 Customizing a Graph’s Appearance
To customize the appearance of a graph:
1. Make the graph the active window (click on its title bar).
2. Select Report >> Customize from the Main Menu, or click on
the Standard Toolbar, or right-click on the graph.
3. Use the Graph Options dialog that appears to customize the appearance of a Time Series or Scatter Plot, or use the Profile Plot Options
dialog for a Profile Plot.
Graph Options Dialog
The Graph Options dialog is used to customize the appearance of a time series
plot or a scatter plot. To use the dialog:
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1. Select from among the five tabbed pages that cover the following
categories of options: General, Horizontal Axis, Vertical Axis, Legend, and Series.
2. Check the Default box if you wish to use the current settings as defaults for all new graphs as well.
3. Select OK to accept your selections.
Graph Options - General
The following options can be set on the General page of the Graph Options dialog box:
Panel Color
Background Color
View in 3D
3D Effect Percent
Main Title
Font
Color of the panel that contains the graph
Color of graph's plotting area
Check if graph should be drawn in 3D
Degree to which 3D effect is drawn
Text of graph's main title
Click to set the font used for the main title
Graph Options - Axes
The Horizontal Axis and Vertical Axis pages of the Graph Options dialog box
adjust the way that the axes are drawn on a graph.
Minimum
Maximum
Increment
Auto Scale
Gridlines
Axis Title
Font
Sets minimum axis value (minimum data value is shown in parentheses). Can be left blank.
Sets maximum axis value (maximum data value is shown in parentheses). Can be left blank.
Sets increment between axis labels. Can be left blank.
If checked then Minimum, Maximum, and Increment settings are
ignored.
Toggles the display of grid lines on and off.
Text of axis title.
Click to select a font for the axis title.
Graph Options - Legend
The Legend page of the Graph Options dialog box controls how the legend is
displayed on the graph.
Position
Color
Symbol Width
Framed
Visible
Selects where to place the legend.
Selects color to use for legend background.
Selects width to use (in pixels) to draw the symbol portion of the
legend.
Places a frame around the legend.
Makes the legend visible.
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Graph Options - Series
The Series page of the Graph Options dialog box controls how individual data
series (or curves) are displayed on a graph. To use this page:
1. Select a data series to work with from the Series combo box.
2. Edit the title used to identify this series in the legend.
3. Click the Font button to change the font used for the legend. (Other
legend properties are selected on the Legend page of the dialog.)
4. Select a property of the data series you would like to modify (not all
properties are available for some types of graphs). The choices are:
• Lines
• Markers
• Patterns
• Labels
Profile Plot Options Dialog
The Profile Plot Options dialog is used to customize the appearance of a Profile
Plot. The dialog contains three pages:
Colors:
• selects the color to use for the plot window panel, the plot background, a conduit’s interior, and the depth of filled water
• includes a "Display Conduits Only" check box that provides a
closer look at the water levels within conduits by removing all
other details from the plot.
Axes:
• edits the main and axis titles, including their fonts
• selects to display horizontal and vertical axis grid lines.
Node Labels:
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205
•
selects to display node ID labels either along the plot’s top axis,
directly on the plot above the node’s crown height, or both.
• selects the length of arrow to draw between the node label and
the node’s crown on the plot (use 0 for no arrows).
• selects the font size of the node ID labels.
Check the Default box if you want these options to apply to all new profile
plots when they are first created.
12.6 Viewing Results with a Table
Time series results for selected variables and objects can also be viewed in a
tabular format. There are two types of formats available:
• Table by Object - tabulates the time series of several variables for a
single object (e.g., flow and water depth for a conduit).
• Table by Variable - tabulates the time series of a single variable for
several objects of the same type (e.g., runoff for a group of subcatchments).
To create a tabular report:
1. Select Report >> Table from the Main Menu or click
on the
Standard Toolbar.
2. Choose the table format (either By Object or By Variable) from
the sub-menu that appears.
3. Fill in the Table by Object or Table by Variable dialogs to specify
what information the table should contain.
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Viewing Results
The Table by Object dialog is used when creating a time series table of several variables for a single object. Use the dialog as follows:
1. Select a Start Date and End Date for the table (the default is the entire simulation period).
2. Choose whether to show time as Elapsed Time or as Date/Time values.
3. Choose an Object Category (Subcatchment, Node, Link, or System).
4. Identify a specific object in the category by clicking the object either on the Study Area Map or in the Data Browser and then
clicking the button on the dialog. Only a single object can be selected for this type of table.
5. Check off the variables to be tabulated for the selected object. The
available choices depend on the category of object selected.
6. Click the OK button to create the table.
Viewing Results
207
The Table by Variable dialog is used when creating a time series table of a
single variable for one or more objects. Use the dialog as follows:
1. Select a Start Date and End Date for the table (the default is the entire simulation period).
2. Choose whether to show time as Elapsed Time or as Date/Time values.
3. Choose an Object Category (Subcatchment, Node or Link).
4. Select a simulated variable to be tabulated. The available choices
depend on the category of object selected.
5. Identify one or more objects in the category by successively clicking the object either on the Study Area Map or in the Data Browser
and then clicking the button on the dialog.
6. Click the OK button to create the table.
A maximum of 6 objects can be selected for a single table. Objects already
selected can be deleted, moved up in the order or moved down in the order by
clicking the , , and buttons, respectively.
12.7 Viewing a Statistics Report
A Statistics Report can be generated from the time series of simulation results.
For a given object and variable this report will do the following:
• segregate the simulation period into a sequence of non-overlapping
events, either by day, month, or by flow (or volume) above some
minimum threshold value,
• compute a statistical value that characterizes each event (e.g. the
mean, maximum or sum of the variable over the event’s time period),
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Viewing Results
•
compute summary statistics for the entire set of event values (mean,
standard deviation and skewness),
• perform a frequency analysis on the set of event values.
The frequency analysis of event values will determine the frequency at which
a particular event value has occurred and will also estimate a return period for
each event value. Statistical analyses of this nature are most suitable for longterm continuous simulation runs.
To generate a Statistics Report:
1. Select Report >> Statistics from the Main Menu or click on the
Standard Toolbar.
2. Fill in the Statistics Selection dialog that appears, specifying the object, variable, and event definition to be analyzed.
The Statistics Selection dialog is used to define the type of statistical analysis
to be made on a computed simulation result. It contains the following data
fields:
Object Category
Select the category of object to analyze (Subcatchment, Node, Link or System).
Object Name
Enter the ID name of the object to analyze. Instead of typing in an ID name, you
can select the object on the Study Area Map or in the Data Browser and then
click the button to select it into the Object Name field.
Viewing Results
209
Variable Analyzed
Enter the name of the variable to be analyzed. The available choices depend on
the object category selected (e.g. rainfall, losses or runoff for subcatchments;
depth, inflow or flooding for nodes; depth, flow, velocity or capacity for links;
water quality for all categories).
Event Time Period
Select the length of the time period that defines an event. The choices are daily,
monthly, or event-dependent. In the latter case, the event period depends on the
number of consecutive reporting periods where simulation results are above the
threshold values defined below.
Statistic
Choose an event statistic to be analyzed. The available choices depend on the
choice of variable to be analyzed and include such quantities as mean value,
peak value, event total, event duration, and inter-event time (i.e., the time interval between the midpoints of successive events). For water quality variables the
choices include mean concentration, peak concentration, mean loading, peak
loading, and event total load.
Event Thresholds
These define minimum values that must be exceeded for an event to occur:
• The Analysis Variable threshold specifies the minimum value of the
variable being analyzed that must be exceeded for a time period to
be included in an event.
• The Event Volume threshold specifies a minimum flow volume (or
rainfall volume) that must be exceeded for a result to be counted as
part of an event.
• Separation Time sets the minimum number of hours that must occur
between the end of one event and the start of the next event. Events
with fewer hours are combined together. This value applies only to
event-dependent time periods (not to daily or monthly event periods).
If a particular type of threshold does not apply, then leave the field blank.
After the choices made on the Statistics Selection dialog form are processed,
a Statistics Report is produced as shown below.
The report consists of four tabbed pages that contain:
• a table of event summary statistics
• a table of rank-ordered event periods, including their date, duration,
and magnitude
• a histogram plot of the chosen event statistic
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Viewing Results
• an exceedance frequency plot of the event values.
Note that the exceedance frequencies included in the report are computed
with respect to the number of events that occur, not the total number of reporting
periods.
Chapter 13
Printing and Copying
This chapter describes how to print, copy to the Windows clipboard, or copy to
a file, the contents of the currently active window in the SWMM workspace. This
can include the study area map, a graph, a table, or a report.
13.1 Selecting a Printer
To select a printer from among your installed Windows printers and set its properties:
1. Select File >> Page Setup from the Main Menu.
2. Click the Printer button on the Page Setup dialog that appears (see
Figure 13-1).
3. Select a printer from the choices available in the combo box in the
Print Setup dialog that appears.
4. Click the Properties button to select the appropriate printer properties (which vary with choice of printer).
5. Click OK on each dialog to accept your selections.
Figure 13-1 The Margins page of the Page Setup dialog.
211
212
Printing and Copying
13.2 Setting the Page Format
To format the printed page:
1. Select File >> Page Setup from the main menu.
2. Use the Margins page of the Page Setup dialog form that appears
(Figure 13-1) to:
Select a printer.
Select the paper orientation (Portrait or Landscape).
Set left, right, top, and bottom margins.
3. Use the Headers/Footers page of the dialog box (Figure 13-2) to:
Supply the text for a header that will appear on each page.
Indicate whether the header should be printed or not and how
its text should be aligned.
Supply the text for a footer that will appear on each page.
Indicate whether the footer should be printed or not and how
its text should be aligned.
Indicate whether pages should be numbered.
4. Click OK to accept your choices.
Figure 13-2 The Headers/Footers page of the Page Setup dialog.
13.3 Print Preview
To preview a printout, select File >> Print Preview from the Main Menu. A
Preview form will appear which shows how each page being printed will appear.
While in preview mode, the left mouse button will re-center and zoom in on the
image and the right mouse button will re-center and zoom out.
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Printing and Copying
13.4 Printing the Current View
To print the contents of the current window being viewed in the SWMM workspace, either select File >> Print from the Main Menu or click
on the
Standard Toolbar. The following views can be printed:
• Study Area Map (at the current zoom level)
• Status Report.
• Graphs (Time Series, Profile, and Scatter plots)
• Tabular Reports
• Statistical Reports.
13.5 Copying to the Clipboard or to a File
SWMM can copy the text and graphics of the current window being viewed to
the Windows clipboard or to a file. Views that can be copied in this fashion include the Study Area Map, graphs, tables, and reports. To copy the current view
to the clipboard or to file:
1. If the current view is a table, select the cells of the table to copy by
dragging the mouse over them or copy the entire table by selecting
Edit >> Select All from the Main Menu.
2. Select Edit >> Copy To from the Main Menu or click the
button
on the Standard Toolbar.
3. Select choices from the Copy dialog (see Figure 13-3) that appears
and click the OK button.
4. If copying to file, enter the name of the file in the Save As dialog
that appears and click OK.
Figure 13-3 Example of the Copy dialog.
Use the Copy dialog as follows to define how you want your data copied and
to where:
1. Select a destination for the material being copied (Clipboard or File)
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Printing and Copying
2. Select a format to copy in:
Bitmap (graphics only)
Metafile (graphics only)
Data (text, selected cells in a table, or data used to construct a
graph)
3. Click OK to accept your selections or Cancel to cancel the copy request.
Chapter 14
Files used by SWMM
This section describes the various files that SWMM can utilize. They include: the
project file, the report and output files, rainfall files, the climate file, calibration
data files, time series files, and interface files. The only file required to run
SWMM is the project file; the others are optional.
14.1 Project Files
A SWMM project file is a plain text file that contains all of the data used to describe a study area and the options used to analyze it. The file is organized into
sections, where each section generally corresponds to a particular category of
object used by SWMM. The contents of the file can be viewed from within
SWMM while it is open by selecting Project >> Details from the Main Menu.
An existing project file can be opened by selecting File >> Open from the Main
Menu and be saved by selecting File >> Save (or File >> Save As).
Normally a SWMM user would not edit the project file directly, since
SWMM's graphical user interface can add, delete, or modify a project's data and
control settings. However, for large projects where data currently reside in other
electronic formats, such as CAD or GIS files, it may be more expeditious to extract data from these sources and save it to a formatted project file before
running SWMM. The format of the project file is described in detail in Chapter 17 of this manual.
After a project file is saved to disk, a settings file will automatically be saved
with it. This file has the same name as the project file except that its extension is
.ini (e.g., if the project file were named project1.inp then its settings file would
have the name project1.ini). It contains various settings used by SWMM’s
graphical user interface, such as map display options, legend colors and intervals, object default values, and calibration file information. Users should not edit
this file. A SWMM project will still load and run even if the settings file is missing.
14.2 Report and Output Files
The report file is a plain text file created after every SWMM run that contains a
status report on the results of a run. It can be viewed by selecting Report >>
215
216
Files used by SWMM
Status from the main menu. If the run was unsuccessful it will contain a list of
error messages. For a successful run it will contain:
• the mass continuity errors for runoff quantity and quality as well as
for flow and water quality routing,
• summary results tables for all drainage system nodes and links, and
• information about the time step size and iterations required when
Dynamic Wave routing analyses are performed.
The output file is a binary file that contains the numerical results from a successful SWMM run. This file is used by SWMM’s user interface to interactively
create time series plots and tables, profile plots, and statistical analyses of a simulation's results.
Whenever a successfully run project is either saved or closed the report and
output files are saved with the same name as the project file, but with extensions
of .rpt and .out. This will happen automatically if the program preference
Prompt to Save Results is turned off (see Chapter 6, section 6.9). Otherwise the
user is asked if the current results should be saved or not. If results are saved
then the next time that the project is opened, the results from these files will automatically be available for viewing.
If a project's data were modified before a successful run was made, then
when the project is closed the user is asked if the updated project should be
saved or not. If the answer is no, then results of the most recent run will not be
saved either.
14.3 Rainfall Files
SWMM’s rain gage objects can utilize rainfall data stored in external rainfall
files. The program currently recognizes the following formats for storing such
data:
• DSI-3240 and related formats which record hourly rainfall at U.S.
National Weather Service (NWS) and Federal Aviation Agency stations, available online from the National Climatic Data Center
(NCDC) at www.ncdc.noaa.gov/oa/ncdc.html.
• DSI-3260 and related formats which record fifteen minute rainfall
at NWS stations, also available online from NCDC.
• HLY03 and HLY21 formats for hourly rainfall at Canadian stations, available online from Environment Canada at their website
www.climate.weatheroffice.ec.gc.ca.
• FIF21 format for fifteen minute rainfall at Canadian stations, also
available online from Environment Canada.
• a standard user-prepared format where each line of the file contains
the station ID, year, month, day, hour, minute, and non-zero precipitation reading, all separated by one or more spaces.
Files used by SWMM
217
An excerpt from a sample user-prepared Rainfall file is as follows:
STA01 2004 6 12 00 00 0.12
STA01 2004 6 12 01 00 0.04
STA01 2004 6 22 16 00 0.07
When a rain gage is designated as receiving its rainfall data from a file, the
user must supply the name of the file and the name of the recording station referenced in the file. For the standard user-prepared format, the rainfall type (e.g.,
intensity or volume), recording time interval, and depth units must also be supplied as rain gage properties. For the other file types these properties are defined
by their respective file format and are automatically recognized by SWMM.
14.4 Climate Files
SWMM can use an external climate file that contains daily air temperature,
evaporation and wind speed data. The program recognizes the following formats:
• A DSI-3200 or DSI-3210 file available from the National Climatic
Data Center at www.ncdc.noaa.gov/oa/ncdc.html.
• Canadian climate files available from Environment Canada at
www.climate.weatheroffice.ec.gc.ca.
• A user-prepared climate file where each line contains a recording
station name, the year, month, day, maximum temperature, minimum temperature, and, optionally, evaporation rate and wind speed.
If no data are available for any of these items on a given date, then
an asterisk should be entered as its value.
When a climate file has days with missing values, SWMM will use the value
from the most recent previous day with a recorded value.
For a user-prepared climate file, the data must be in the same units as
the project being analyzed. For US units, temperature is in degrees F, evaporation is in inches/day, and wind speed is in miles/hour. For metric units,
temperature is in degrees C, evaporation is in mm/day, and wind speed is in
km/hour.
14.5 Calibration Files
Calibration files contain measurements of variables at one or more locations that
can be compared with simulated values in Time Series Plots. Separate files can
be used for each of the following:
• Subcatchment Runoff
• Subcatchment Groundwater Flow
• Subcatchment Groundwater Elevation
• Subcatchment Snowpack Depth
218
Files used by SWMM
• Subcatchment Pollutant Washoff
• Node Depth
• Node Lateral Inflow
• Node Flooding
• Node Water Quality
• Link Flow
Calibration files are registered to a project by selecting Project >> Calibration
Data from the main menu (see Chapter 8, section 8.7).
The format of the file is as follows:
1. The name of the first object with calibration data is entered on a
single line.
2. Subsequent lines contain the following recorded measurements for
the object:
measurement date (month/day/year, e.g., 6/21/2004) or number
of whole days since the start of the simulation
measurement time (hours:minutes) on the measurement date or
relative to the number of elapsed days
measurement value (for pollutants, a value is required for each
pollutant).
3. Follow the same sequence for any additional objects.
An excerpt from an example calibration file is shown below. It contains flow
values for two conduits: 1030 and 1602. Note that a semicolon can be used to
begin a comment. In this example, elapsed time rather than the actual measurement date was used.
;Flows for Selected Conduits
;Conduit Days Time Flow
;----------------------------1030
0
0:15 0
0
0:30 0
0
0:45 23.88
0
1:00 94.58
0
1:15 115.37
1602
0
0:15 5.76
0
0:30 38.51
0
1:00 67.93
0
1:15 68.01
14.6 Time Series Files
Time series files are external text files that contain data for SWMM's time series
objects. Examples of time series data include rainfall, evaporation, inflows to
nodes of the drainage system, and water stage at outfall boundary nodes. The
Files used by SWMM
219
file must be created and edited outside of SWMM, using a text editor or spreadsheet program. A time series file can be linked to a specific time series object
using SWMM's Time Series Editor.
The format of a time series file consists of one time series value per line.
Comment lines can be inserted anywhere in the file as long as they begin with a
semicolon. Time series values can either be in date / time / value format or in
time / value format, where each entry is separated by one or more spaces or tab
characters. For the date / time / value format, dates are entered as
month/day/year (e.g., 7/21/2004) and times as 24-hour military time (e.g., 8:30
pm is 20:30). After the first date, additional dates need only be entered whenever a new day occurs. For the time / value format, time can either be decimal
hours or military time since the start of a simulation (e.g., 2 days, 4 hours and 20
minutes can be entered as either 52.333 or 52:20). An example of a time series
file is shown below:
; Rainfall Data for Gauge G1
07/01/2003 00:00 0.00000
00:15 0.03200
00:30 0.04800
00:45 0.02400
01:00 0.0100
07/06/2003 14:30 0.05100
14:45 0.04800
15:00 0.03000
18:15 0.01000
In earlier releases of SWMM 5, a time series file was required to have
two header lines of descriptive text at the start of the file that did not have to
begin with the semicolon comment character. These files can still be used as
long as they are modified by inserting a semicolon at the front of the first two
lines.
When preparing rainfall time series files, it is only necessary to enter
periods with non-zero rainfall amounts. SWMM interprets the rainfall value as a
constant value lasting over the recording interval specified for the rain gage
which utilizes the time series. For all other types of time series, SWMM uses
interpolation to estimate values at times that fall in between the recorded values.
14.7 Interface Files
SWMM can use several different kinds of interface files that contain either externally imposed inputs (e.g., rainfall or infiltration/inflow hydrographs) or the
results of previously run analyses (e.g., runoff or routing results). These files can
help speed up simulations, simplify comparisons of different loading scenarios,
220
Files used by SWMM
and allow large study areas to be broken up into smaller areas that can be analyzed individually. The different types of interface files that are currently
available include:
• rainfall interface file
• runoff interface file
• hot start file
• RDII interface file
• routing interface files
Consult Section 11.1, Setting Simulation Options, for instructions on how to
specify interface files for use as input and/or output in a simulation.
Rainfall and Runoff Files
The rainfall and runoff interface files are binary files created internally by
SWMM that can be saved and reused from one analysis to the next.
The rainfall interface file collates a series of separate rain gage files into a
single rainfall data file. Normally a temporary file of this type is created for every SWMM analysis that uses external rainfall data files and is then deleted after
the analysis is completed. However, if the same rainfall data are being used with
many different analyses, requesting SWMM to save the rainfall interface file
after the first run and then reusing this file in subsequent runs can save computation time.
The rainfall interface file should not be confused with a rainfall data
file. The latter is an external text file that provides rainfall time series data for a
single rain gage. The former is a binary file created internally by SWMM that
processes all of the rainfall data files used by a project.
The runoff interface file can be used to save the runoff results generated from
a simulation run. If runoff is not affected in future runs, the user can request that
SWMM use this interface file to supply runoff results without having to repeat
the runoff calculations again.
Hot Start Files
Hot start files are binary files created by SWMM that save the current state of
the study area’s groundwater and conveyance system at the end of a run. The
following information is saved to the file:
▪ the unsaturated zone moisture content and water table elevation for
each subcatchment that has a groundwater zone defined for it
▪ the water depth and concentration of each pollutant at each node of the
system
▪ the flow rate and concentration of each pollutant in each link of the system.
The hot start file saved after a run can be used to define the initial conditions
for a subsequent run.
Files used by SWMM
221
Hot start files can be used to avoid the initial numerical instabilities that
sometimes occur under Dynamic Wave routing. For this purpose they are typically generated by imposing a constant set of base flows (for a natural channel
network) or set of dry weather sanitary flows (for a sewer network) over some
startup period of time. The resulting hot start file from this run is then used to
initialize a subsequent run where the inflows of real interest are imposed.
It is also possible to both use and save a hot start file in a single run, starting
off the run with one file and saving the ending results either to the same or to
another file. The resulting file can then serve as the initial conditions for a subsequent run if need be. This technique can be used to divide up extremely long
continuous simulations into more manageable pieces.
Aside from using the project's Analysis Options to create a hot start file, one
can also use the File >> Export >> Hot Start File Main Menu command to
save the results of a current run at any particular time period to a hot start file.
However, in this case only the results for nodes and links will be saved and not
those for groundwater
RDII Files
The RDII interface file is a text file that contains a time series of rainfalldependent infiltration/inflow flows for a specified set of drainage system nodes.
This file can be generated from a previous SWMM run when Unit Hydrographs
and nodal RDII inflow data have been defined for the project, or it can be created outside of SWMM using some other source of RDII data (e.g., through
measurements or output from a different computer program). The format of the
file is the same as that of the routing interface file discussed below, where Flow
is the only variable contained in the file.
Routing Files
A routing interface file stores a time series of flows and pollutant concentrations
that are discharged from the outfall nodes of drainage system model. This file
can serve as the source of inflow to another drainage system model that is connected at the outfalls of the first system. A Combine utility is available on the
File menu that will combine pairs of routing interface files into a single interface
file. This allows very large systems to be broken into smaller sub-systems that
can be analyzed separately and linked together through the routing interface file.
Figure 14-1 illustrates this concept.
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Files used by SWMM
Figure 14-1 Example of using the Combine utility to merge Routing files.
A single SWMM run can utilize an outflows routing file to save results generated at a system's outfalls, an inflows routing file to supply hydrograph and
pollutograph inflows at selected nodes, or both.
RDII / Routing File Format
RDII interface files and routing interface files have the same text format:
1. the first line contains the keyword "SWMM5" (without the quotes)
2. a line of text that describes the file (can be blank)
3. the time step used for all inflow records (integer seconds)
4. the number of variables stored in the file, where the first variable
must always be flow rate
5. the name and units of each variable (one per line), where flow rate
is the first variable listed and is always named FLOW
6. the number of nodes with recorded inflow data
7. the name of each node (one per line)
8. a line of text that provides column headings for the data to follow
(can be blank)
9. for each node at each time step, a line with:
the name of the node
the date (year, month, and day separated by spaces)
the time of day (hours, minutes, and seconds separated by
spaces)
the flow rate followed by the concentration of each quality
constituent
Time periods with no values at any node can be skipped. An excerpt from an
RDII / routing interface file is shown below.
223
Files used by SWMM
SWMM5
Example File
300
1
FLOW CFS
2
N1
N2
Node Year Mon
N1
2002 04
N2
2002 04
N1
2002 04
N2
2002 04
Day
01
01
01
01
Hr
00
00
00
00
Min
20
20
25
25
Sec
00
00
00
00
Flow
0.000000
0.002549
0.000000
0.002549
224
Files used by SWMM
Chapter 15
Using Add-In Tools
SWMM 5 has the ability to launch external applications from its graphical
user interface that can extend its capabilities. This section describes how
such tools can be registered and share data with SWMM 5.
15.1 What are Add-In Tools?
Add-in tools are third party applications that users can add to the Tools menu of
the main SWMM menu bar and be launched while SWMM is still running.
SWMM can interact with these applications to a limited degree by exchanging
data through its pre-defined files (see Chapter 14) or through the Windows clipboard. Add-in tools can provide additional modeling capabilities to what
SWMM already offers. Some examples of useful add-ins might include:
• a tool that performs a statistical analysis of long-term rainfall data
prior to adding it to a SWMM rain gage,
• an external spreadsheet program that would facilitate the editing of
a SWMM data set,
• a unit hydrograph estimator program that would derive the R-T-K
parameters for a set of RDII unit hydrographs which could then be
copied and pasted directly into SWMM’s Unit Hydrograph Editor,
• a post-processor program that uses SWMM’s hydraulic results to
compute suspended solids removal through a storage unit,
• a third-party dynamic flow routing program used as a substitute for
SWMM’s own internal procedure.
Figure 15-1 SWMM’s Tools menu.
225
226
Using Add-In Tools
Figure 15-1 shows what the Tools menu might look like after several add-in
tools have been registered with it. The Configure Tools option is used to add,
delete, or modify add-in tools. The options below this are the individual tools
that have been made available (by this particular user) and can be launched by
selecting them from the menu.
15.2 Configuring Add-In Tools
To configure one’s personal collection of add-in tools, select Configure Tools
from the Tools menu. This will bring up the Tool Options dialog as shown in
Figure 15-2. The dialog lists the currently available tools and has command buttons for adding a new tool and for deleting or editing an existing tool. The up
and down arrow buttons are used to change the order in which the registered
tools are listed on the Tools menu.
Figure 15-2 The Tools Options dialog.
Figure 15-3 The Tool Properties dialog.
Using Add-In Tools
227
Whenever the Add or Edit button is clicked on this dialog a Tool Properties
dialog will appear as shown in Figure 15-3. This dialog is used to describe the
properties of the new tool being added or the existing tool being edited.
The data entry fields of the Tool Properties dialog consist of the following.
Tool Name
This is the name to be used for the tool when it is displayed in the Tools Menu.
Program
Enter the full path name to the program that will be launched when the tool is
selected. You can click the button to bring up a standard Windows file selection dialog from which you can search for the tool’s executable file name.
Working Directory
This field contains the name of the directory that will be used as the working
directory when the tool is launched. You can click the button to bring up a
standard directory selection dialog from which you can search for the desired
directory. You can also enter the macro symbol $PROJDIR to utilize the current
SWMM project’s directory or $SWMMDIR to use the directory where the
SWMM 5 executable resides. Either of these macros can also be inserted into
the Working Directory field by selecting its name in the list of macros provided
on the dialog and then clicking the button. This field can be left blank, in
which case the system’s current directory will be used.
Parameters
This field contains the list of command line arguments that the tool’s executable
program expects to see when it is launched. Multiple parameters can be entered
as long as they are separated by spaces. A number of special macro symbols
have been pre-defined, as listed in the Macros list box of the dialog, to simplify
the process of listing the command line parameters. When one of these macro
symbols is inserted into the list of parameters, it will be expanded to its true value when the tool is launched. A specific macro symbol can either be typed into
the Parameters field or be selected from the Macros list (by clicking on it) and
then added to the parameter list by clicking the button. The available macro
symbols and their meanings are defined in Table 15-1 below.
As an example of how the macro expansion works, consider the entries in the
Tool Properties dialog (shown in Figure 15-3). This Spreadsheet Editor tool
wants to launch Microsoft Excel and pass it the name of the SWMM input data
file to be opened by Excel. SWMM will issue the following command line to do
this:
c:\Program Files\Microsoft Office\Office10\EXCEL.EXE $INPFILE
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Using Add-In Tools
where the string $INPFILE is replaced by the name of a temporary file that
SWMM creates internally which will contain the current project’s data.
Table 15-1 Macros used as command line parameters for external tools.
Macro Symbol
$PROJDIR
$SWMMDIR
$INPFILE
$RPTFILE
$OUTFILE
$RIFFILE
Expands To
The directory where the current SWMM project file resides.
The directory where the SWMM 5 executable is installed.
The name of a temporary file containing the current project’s data that is
created just before the tool is launched.
The name of a temporary file that is created just before the tool is launched
and can be displayed after the tool closes by using the Report >> Status
command from the main SWMM menu.
The name of a temporary file to which the tool can write simulation results
in the same format used by SWMM 5, which can then be displayed after
the tool closes in the same fashion as if a SWMM run were made.
The name of the Runoff Interface File, as specified in the Interface Files
page of the Simulation Options dialog, to which runoff simulation results
were saved from a previous SWMM run (see Sections 8.1 and 11.7).
Disable SWMM while executing
Check this option if SWMM should be minimized and disabled while the tool is
executing. Normally you will need to employ this option if the tool produces a
modified input file or output file, such as when the $INPFILE or $OUTFILE
macros are used as command line parameters. When this option is enabled,
SWMM’s main window will be minimized and will not respond to user input
until the tool is terminated.
Update SWMM after closing
Check this option if SWMM should be updated after the tool finishes executing.
This option can only be selected if the option to disable SWMM while the tool is
executing was first selected. Updating can occur in two ways. If the $INPFILE
macro was used as a command line parameter for the tool and the corresponding
temporary input file produced by SWMM was updated by the tool, then the current project’s data will be replaced with the data contained in the updated
temporary input file. If the $OUTFILE macro was used as a command line parameter, and its corresponding file is found to contain a valid set of output
results after the tool closes, then the contents of this file will be used to display
simulation results within the SWMM workspace.
Generally speaking, the suppliers of third-party tools will provide instructions on what settings should be used in the Tool Properties dialog to properly
register their tool with SWMM.
Chapter 16
Visual Object Properties
16.1 Rain Gage Properties
Name
X-Coordinate
Y-Coordinate
Description
Tag
Rain Format
Rain Interval
Snow Catch Factor
Data Source
TIME SERIES
- Series Name
DATA FILE
- File Name
- Station No.
- Rain Units
User-assigned rain gage name.
Horizontal location of the rain gage on the Study Area Map. If left
blank then the rain gage will not appear on the map.
Vertical location of the rain gage on the Study Area Map. If left
blank then the rain gage will not appear on the map.
Click the ellipsis button (or press Enter) to edit an optional description of the rain gage.
Optional label used to categorize or classify the rain gage.
Format in which the rain data are supplied:
INTENSITY: each rainfall value is an average rate in inches/hour (or mm/hour) over the recording interval,
VOLUME: each rainfall value is the volume of rain that fell in
the recording interval (in inches or millimeters),
CUMULATIVE: each rainfall value represents the cumulative
rainfall that has occurred since the start of the last series of
non-zero values (in inches or millimeters).
Recording time interval between gage readings in either decimal
hours or hours:minutes format.
Factor that corrects gage readings for snowfall.
Source of rainfall data; either TIMESERIES for user-supplied time
series data or FILE for an external data file.
Name of time series with rainfall data if Data Source selection was
TIMESERIES; leave blank otherwise (double-click to edit the
series).
Name of external file containing rainfall data.
Recording gage station number.
Depth units (IN or MM) for rainfall values in the file.
229
230
Visual Object Properties
16.2 Subcatchment Properties
Name
X-Coordinate
Y-Coordinate
Description
Tag
Rain Gage
Outlet
Area
Width
% Slope
% Imperv
N-Imperv
N-Perv
Dstore-Imperv
Dstore-Perv
% Zero-Imperv
Subarea Routing
Percent Routed
Infiltration
LID Controls
Groundwater
Snow Pack
Initial Buildup
Land Uses
Curb Length
User-assigned subcatchment name.
Horizontal location of the subcatchment's centroid on the Study Area Map.
If left blank then the subcatchment will not appear on the map.
Vertical location of the subcatchment's centroid on the Study Area Map. If
left blank then the subcatchment will not appear on the map.
Click the ellipsis button (or press Enter) to edit an optional description of
the subcatchment.
Optional label used to categorize or classify the subcatchment.
Name of the rain gage associated with the subcatchment.
Name of the node or subcatchment which receives the subcatchment's
runoff.
Area of the subcatchment (acres or hectares).
Characteristic width of the overland flow path for sheet flow runoff (feet
or meters). An initial estimate of the characteristic width is given by the
subcatchment area divided by the average maximum overland flow length.
The maximum overland flow length is the length of the flow path from the
inlet to the furthest drainage point of the subcatchment. Maximum lengths
from several different possible flow paths should be averaged. These paths
should reflect slow flow, such as over pervious surfaces, more than rapid
flow over pavement, for example. Adjustments should be made to the
width parameter to produce good fits to measured runoff hydrographs.
Average percent slope of the subcatchment.
Percent of land area which is impervious.
Manning's n for overland flow over the impervious portion of the subcatchment (see Chapter 24, section 24.6 for typical values).
Manning's n for overland flow over the pervious portion of the subcatchment (see Chapter 24, section 24.6 for typical values).
Depth of depression storage on the impervious portion of the subcatchment (inches or millimeters) (Chapter 24, section 24.5).
Depth of depression storage on the pervious portion of the subcatchment
(inches or millimeters) (Chapter 24, section 24.5 for typical values).
Percent of the impervious area with no depression storage.
Choice of internal routing of runoff between pervious and impervious
areas:
IMPERV: runoff from pervious area flows to impervious area,
PERV:
runoff from impervious area flows to pervious area,
OUTLET: runoff from both areas flows directly to outlet.
Percent of runoff routed between subareas.
Click the ellipsis button (or press Enter) to edit infiltration parameters for
the subcatchment.
Click the ellipsis button (or press Enter) to edit the use of low impact
development controls in the subcatchment.
Click the ellipsis button (or press Enter) to edit groundwater flow parameters for the subcatchment.
Name of snow pack parameter set (if any) assigned to the subcatchment.
Click the ellipsis button (or press Enter) to specify initial quantities of
pollutant buildup over the subcatchment.
Click the ellipsis button (or press Enter) to assign land uses to the subcatchment.
Total length of curbs in the subcatchment (any length units). Used only
when pollutant buildup is normalized to curb length.
Visual Object Properties
231
16.3 Junction Properties
Name
X-Coordinate
Y-Coordinate
Description
Tag
Inflows
Treatment
Invert El.
Max. Depth
Initial Depth
Surcharge
Depth
Ponded Area
User-assigned junction name.
Horizontal location of the junction on the Study Area Map. If left blank then
the junction will not appear on the map.
Vertical location of the junction on the Study Area Map. If left blank then the
junction will not appear on the map.
Click the ellipsis button (or press Enter) to edit an optional description of the
junction.
Optional label used to categorize or classify the junction.
Click the ellipsis button (or press Enter) to assign external direct dry weather
or RDII inflows to the junction.
Click the ellipsis button (or press Enter) to edit a set of treatment functions
for pollutants entering the node.
Invert elevation of the junction (feet or meters).
Maximum depth of junction (i.e., from ground surface to invert) (feet or
meters). If zero then the distance from the invert to the top of the highest
connecting link will be used.
Depth of water at the junction at the start of the simulation (ft or meters).
Additional depth of water beyond the maximum depth that is allowed before
the junction floods (feet or meters). This parameter can be used to simulate
bolted manhole covers or force main connections.
Area occupied by ponded water atop the junction after flooding occurs (sq.
feet or sq. meters). If the Allow Ponding simulation option is turned on, a
non-zero value of this parameter will allow ponded water to be stored and
subsequently returned to the conveyance system when capacity exists.
16.4 Outfall Properties
Name
X-Coordinate
Y-Coordinate
Description
Tag
Inflows
Treatment
Invert El.
Tide Gate
Type
User-assigned outfall name.
Horizontal location of the outfall on the Study Area Map. If left blank
then the outfall will not appear on the map.
Vertical location of the outfall on the Study Area Map. If left blank then
the outfall will not appear on the map.
Click the ellipsis button (or press Enter) to edit an optional description
of the outfall.
Optional label used to categorize or classify the outfall.
Click the ellipsis button (or press Enter) to assign external direct dry
weather or RDII inflows to the outfall.
Click the ellipsis button (or press Enter) to edit a set of treatment functions for pollutants entering the node.
Invert elevation of the outfall (feet or meters).
YES - tide gate present to prevent backflow
NO - no tide gate present
Type of outfall boundary condition:
FREE: outfall stage determined by minimum of critical flow
depth and normal flow depth in the connecting conduit
NORMAL: outfall stage based on normal flow depth in connecting
conduit
FIXED: outfall stage set to a fixed value
TIDAL: outfall stage given by a table of tide elevation versus time
of day
232
Fixed Stage
Tidal Curve Name
Time Series Name
Visual Object Properties
TIMESERIES: outfall stage supplied from a time series of elevations.
Water elevation for a FIXED type of outfall (feet or meters).
Name of the Tidal Curve relating water elevation to hour of the day for
a TIDAL outfall (double-click to edit the curve).
Name of time series containing time history of outfall elevations for a
TIMESERIES outfall (double-click to edit the series).
16.5 Flow Divider Properties
Name
X-Coordinate
Y-Coordinate
Description
Tag
Inflows
Treatment
Invert El.
Max. Depth
Initial Depth
Surcharge Depth
Ponded Area
Diverted Link
Type
User-assigned divider name.
Horizontal location of the divider on the Study Area Map. If left blank
then the divider will not appear on the map.
Vertical location of the divider on the Study Area Map. If left blank then
the divider will not appear on the map.
Click the ellipsis button (or press Enter) to edit an optional description of
the divider.
Optional label used to categorize or classify the divider.
Click the ellipsis button (or press Enter) to assign external direct dry
weather or RDII inflows to the divider.
Click the ellipsis button (or press Enter) to edit a set of treatment functions for pollutants entering the node.
Invert elevation of the divider (feet or meters).
Maximum depth of divider (i.e., from ground surface to invert) (feet or
meters). See description for Junctions.
Depth of water at the divider at the start of the simulation (feet or meters).
Additional depth of water beyond the maximum depth that is allowed
before the junction floods (feet or meters). This parameter can be used to
simulate bolted manhole covers.
Area occupied by ponded water atop the junction after flooding occurs
(sq. feet or sq. meters). See description for Junctions..
Name of link which receives the diverted flow.
Type of flow divider. Choices are:
CUTOFF (diverts all inflow above a defined cutoff value),
OVERFLOW (diverts all inflow above the flow capacity of the nondiverted link),
TABULAR (uses a Diversion Curve to express diverted flow as a
function of the total inflow),
WEIR (uses a weir equation to compute diverted flow).
CUTOFF DIVIDER
- Cutoff Flow
Cutoff flow value used for a CUTOFF divider (flow units).
TABULAR DIVIDER
- Curve Name
Name of Diversion Curve used with a TABULAR divider (double-click to
edit the curve).
WEIR DIVIDER
- Min. Flow
Minimum flow at which diversion begins for a WEIR divider (flow
units).
- Max. Depth
Vertical height of WEIR opening (feet or meters)
- Coefficient
Product of WEIR's discharge coefficient and its length. Weir coefficients
are typically in the range of 2.65 to 3.10 per foot, for flows in CFS.
Visual Object Properties
233
16.6 Storage Unit Properties
Name
X-Coordinate
Y-Coordinate
Description
Tag
Inflows
Treatment
Invert El.
Max. Depth
Initial Depth
Ponded Area
Evap. Factor
Infiltration
Storage Curve
FUNCTIONAL
- Coeff.
- Exponent
- Constant
TABULAR
- Curve Name
User-assigned storage unit name.
Horizontal location of the storage unit on the Study Area Map. If left blank
then the storage unit will not appear on the map.
Vertical location of the storage unit on the Study Area Map. If left blank
then the storage unit will not appear on the map.
Click the ellipsis button (or press Enter) to edit an optional description of
the storage unit.
Optional label used to categorize or classify the storage unit.
Click the ellipsis button (or press Enter) to assign external direct dry
weather or RDII inflows to the storage unit.
Click the ellipsis button (or press Enter) to edit a set of treatment functions
for pollutants entering the storage unit.
Elevation of the bottom of the storage unit (feet or meters).
Maximum depth of the storage unit (feet or meters).
Initial depth of water in the storage unit at the start of the simulation (feet
or meters).
Surface area occupied by ponded water atop the storage unit once the
water depth exceeds the maximum depth (sq. feet or sq. meters). See description for junctions.
The fraction of the potential evaporation from the storage unit’s water
surface that is actually realized.
Click the ellipsis button (or press Enter) to supply a set of Green-Ampt
parameters that describe how water can infiltrate into the native soil below
the unit. See Section 7.7 for a description of these parameters, To disable
any infiltration, make sure that these parameters are blank
Method of describing the geometric shape of the storage unit.
FUNCTIONAL uses the function
Area = A*(Depth)^B + C
to describe how surface area varies with depth.
TABULAR uses a tabulated area versus depth curve.
In either case, depth is measured in feet (or meters) and surface area in sq.
feet (or sq. meters).
A-value in the functional relationship between surface area and storage
depth.
B-value in the functional relationship between surface area and storage
depth.
C-value in the functional relationship between surface area and storage
depth.
Name of the Storage Curve containing the relationship between surface
area and storage depth (double-click to edit the curve).
234
Visual Object Properties
16.7 Conduit Properties
Name
Inlet Node
Outlet Node
Description
Tag
Shape
Max. Depth
Length
Roughness
Inlet Offset
Outlet Offset
Initial Flow
Maximum Flow
Entry Loss Coeff.
Exit Loss Coeff.
Avg. Loss Coeff.
Flap Gate
Culvert Code
User-assigned conduit name.
Name of node on the inlet end of the conduit (which is normally the end
at higher elevation).
Name of node on the outlet end of the conduit (which is normally the
end at lower elevation).
Click the ellipsis button (or press Enter) to edit an optional description
of the conduit.
Optional label used to categorize or classify the conduit.
Click the ellipsis button (or press Enter) to edit the geometric properties
of the conduit's cross section.
Maximum depth of the conduit's cross section (ft or meters).
Conduit length (feet or meters).
Manning's roughness coefficient (see Chapter 24, section 24.7 for
closed conduit values or section 24.8 for open channel values).
Depth or elevation of the conduit invert above the node invert at the
upstream end of the conduit (feet or meters).
Depth or elevation of the conduit invert above the node invert at the
downstream end of the conduit (feet or meters).
Initial flow in the conduit at the start of the simulation (flow units).
Maximum flow allowed in the conduit under dynamic wave routing
(flow units) – use 0 or leave blank if not applicable.
Head loss coefficient associated with energy losses at the entrance of
the conduit.
Head loss coefficient associated with energy losses at the exit of the
conduit.
Head loss coefficient associated with energy losses along the length of
the conduit.
YES if a flap gate exists that prevents backflow through the conduit, or
NO if no flap gate exists.
Code number of inlet geometry if conduit is a culvert – leave blank
otherwise. Culvert code numbers are listed in Table 24-10.
NOTE: Conduits and flow regulators (orifices,
weirs, and outlets) can be offset some distance
above the invert of their connecting end nodes.
There are two different conventions available for
specifying the location of these offsets. The
Depth convention uses the offset distance from
the node’s invert (distance between ① and ② in
the figure on the right). The Elevation convention uses the absolute elevation of the offset
location (the elevation of point ① in the figure).
The choice of convention can be made on the
General Page of the Simulation Options dialog or
on the Node/Link Properties page of the Project
Defaults dialog.
Visual Object Properties
235
16.8 Pump Properties
Name
Inlet Node
Outlet Node
Description
Tag
Pump Curve
Initial Status
Startup Depth
Shutoff Depth
User-assigned pump name.
Name of node on the inlet side of the pump.
Name of node on the outlet side of the pump.
Click the ellipsis button (or press Enter) to edit an optional description of
the pump.
Optional label used to categorize or classify the pump.
Name of the Pump Curve which contains the pump's operating data (double-click to edit the curve). Use * for an Ideal pump.
Status of the pump (ON or OFF) at the start of the simulation.
Depth at inlet node when pump turns on (feet or meters)
Depth at inlet node when pump shuts off (feet or meters)
16.9 Orifice Properties
Name
Inlet Node
Outlet Node
Description
Tag
Type
Shape
Height
Width
Inlet Offset
Discharge Coeff.
Flap Gate
Time to
Open/Close
User-assigned orifice name.
Name of node on the inlet side of the orifice.
Name of node on the outlet side of the orifice.
Click the ellipsis button (or press Enter) to edit an optional description of
the orifice.
Optional label used to categorize or classify the orifice.
Type of orifice (SIDE or BOTTOM).
Orifice shape (CIRCULAR or RECT_CLOSED).
Height of orifice opening when fully open (feet or meters). Corresponds to
the diameter of a circular orifice or the height of a rectangular orifice.
Width of rectangular orifice when fully opened (feet or meters)
Depth or elevation of bottom of orifice above invert of inlet node (feet or
meters – see note below table of Conduit Properties).
Discharge coefficient (unitless). A typical value is 0.65.
YES if a flap gate exists which prevents backflow through the orifice, or
NO if no flap gate exists.
The time it takes to open a closed (or close an open) gated orifice in decimal hours. Use 0 or leave blank if timed openings/closings do not apply.
Use Control Rules to adjust gate position.
16.10 Weir Properties
Name
Inlet Node
Outlet Node
Description
Tag
Type
Height
Length
User-assigned weir name.
Name of node on inlet side of weir.
Name of node on outlet side of weir.
Click the ellipsis button (or press Enter) to edit an optional description
of the weir.
Optional label used to categorize or classify the weir.
Weir type: TRANSVERSE, SIDEFLOW, V-NOTCH, or
TRAPEZOIDAL
Vertical height of weir opening (feet or meters)
Horizontal length of weir opening (feet or meters)
236
Side Slope
Inlet Offset
Discharge Coeff.
Flap Gate
End Coeff.
End Contractions
Visual Object Properties
Slope (width-to-height) of side walls for a V-NOTCH or
TRAPEZOIDAL weir.
Depth or elevation of bottom of weir opening from invert of inlet node
(feet or meters – see note below table of Consuit Properties).
Discharge coefficient for flow through the central portion of the weir
(for flow in CFS when using US units or CMS when using SI units).
Typical values are: 3.33 US (1.84 SI) for sharp crested transverse
weirs, 2.5 - 3.3 US (1.38 - 1.83 SI) for broad crested rectangular
weirs, 2.4 - 2.8 US (1.35 - 1.55 SI) for V-notch (triangular) weirs
YES if the weir has a flap gate that prevents backflow, NO if it does
not.
Discharge coefficient for flow through the triangular ends of a
TRAPEZOIDAL weir. See the recommended values for V-notch
weirs listed above.
Number of end contractions for a TRANSVERSE or TRAPEZOIDAL
weir whose length is shorter than the channel it is placed in. Values
will be either 0, 1, or 2 depending on if no ends, one end, or both ends
are beveled in from the side walls.
16.11 Outlet Properties
Name
Inlet Node
Outlet Node
Description
Tag
Inlet Offset
Flap Gate
Rating Curve
FUNCTIONAL
- Coefficient
- Exponent
TABULAR
- Curve Name
User-assigned outlet name
Name of node on inflow side of outlet
Name of node on discharge side of outlet
Click the ellipsis button (or press Enter) to edit an optional description of the outlet.
Optional label used to categorize or classify the outlet
Depth or elevation of bottom of weir opening from invert of inlet
node (feet or meters – see note below table of Conduit Properties).
YES if a flap gate exists which prevents backflow through the outlet,
or NO if no flap gate exists.
Method of defining flow (Q) as a function of depth or head (y) across
the outlet.
FUNCTIONAL/DEPTH uses a power function (Q = AyB) to
describe this relation where y is the depth of water above the
outlet’s opening at the inlet node.
FUNCTIONAL/HEAD uses the same power function except
that y is the difference in head across the outlet’s nodes.
TABULAR/DEPTH uses a tabulated curve of flow versus depth
of water above the outlet’s opening at the inlet node.
TABULAR/HEAD uses a tabulated curve of flow versus difference in head across the outlet’s nodes
Coefficient (A) for the functional relationship between head and flow
rate.
Exponent (B) used for the functional relationship between head and
flow rate.
Name of Rating Curve containing the relationship between head and
flow rate (double-click to edit the curve).
Visual Object Properties
237
16.12 Map Label Properties
Text
X-Coordinate
Y-Coordinate
Anchor Node
Font
Text of label.
Horizontal location of the upper-left corner of the label on the Study
Area Map.
Vertical location of the upper-left corner of the label on the Study Area
Map.
Name of node (or subcatchment) that anchors the label's position when
the map is zoomed in (i.e., the pixel distance between the node and the
label remains constant). Leave blank if anchoring is not used.
Click the ellipsis button (or press Enter) to modify the font used to
draw the label.
238
Visual Object Properties
Chapter 17
Command Line SWMM
17.1 General Instructions
USEPA SWMM can also be run as a console application from the command line
within a DOS window. In this case the study area data are placed into a text file
and results are written to a text file. The command line for running SWMM in
this fashion is:
swmm5
inpfile
rptfile
outfile
where inpfile is the name of the input file, rptfile is the name of the output report file, and outfile is the name of an optional binary output file that
stores results in a special binary format. If the latter file is not needed then only
the input and report file names should be supplied. As written, the above command assumes that you are working in the directory in which SWMM was
installed or that this directory has been added to the PATH variable in your user
profile (or the autoexec.bat file in older versions of Windows). Otherwise full
pathnames for the executable swmm5.exe and the files on the command line
must be used.
17.2 Input File Format
The input file for command line SWMM has the same format as the project file
used by the Windows version of the program. Figure 17-1 illustrates an example
SWMM 5 input file. It is organized in sections, where each section begins with a
keyword enclosed in brackets. The various keywords are listed below.
[TITLE]
[OPTIONS]
[REPORT]
[FILES]
project title
analysis options
output reporting instructions
interface file options
[RAINGAGES]
[HYDROGRAPHS]
[EVAPORATION]
[TEMPERATURE]
rain gage information
unit hydrograph data used to construct RDII inflows
evaporation data
air temperature and snow melt data
[SUBCATCHMENTS] basic subcatchment information
239
240
Command Line SWMM
[SUBAREAS]
[INFILTRATION]
[LID_CONTROLS]
[LID_USAGE]
[AQUIFERS]
[GROUNDWATER]
[SNOWPACKS]
subcatchment impervious/pervious sub-area data
subcatchment infiltration parameters
low impact development control information
assignment of LID controls to subcatchments
groundwater aquifer parameters
subcatchment groundwater parameters
subcatchment snow pack parameters
[JUNCTIONS]
[OUTFALLS]
[DIVIDERS]
[STORAGE]
[CONDUITS]
[PUMPS]
[ORIFICES]
[WEIRS]
[OUTLETS]
[XSECTIONS]
[TRANSECTS]
[LOSSES]
[CONTROLS]
junction node information
outfall node information
flow divider node information
storage node information
conduit link information
pump link information
orifice link information
weir link information
outlet link information
conduit, orifice, and weir cross-section geometry
transect geometry for conduits with irregular
cross-sections
conduit entrance/exit losses and flap valves
rules that control pump and regulator operation
[POLLUTANTS]
[LANDUSES]
[COVERAGES]
[BUILDUP]
[WASHOFF]
[TREATMENT]
pollutant information
land use categories
assignment of land uses to subcatchments
buildup functions for pollutants and land uses
washoff functions for pollutants and land uses
pollutant removal functions at conveyance system nodes
[INFLOWS]
[DWF]
[PATTERNS]
[RDII]
[LOADINGS]
external hydrograph/pollutograph inflow at nodes
baseline dry weather sanitary inflow at nodes
periodic variation in dry weather inflow
rainfall-dependent I/I information at nodes
initial pollutant loads on subcatchments
[CURVES]
[TIMESERIES]
x-y tabular data referenced in other sections
time series data referenced in other sections
The sections can appear in any arbitrary order in the input file, and not all
sections must be present. Each section can contain one or more lines of data.
Blank lines may appear anywhere in the file. A semicolon (;) can be used to indicate that what follows on the line is a comment, not data. Data items can
appear in any column of a line. Observe how in Figure 17-1 these features were
used to create a tabular appearance for the data, complete with column headings.
Command Line SWMM
[TITLE]
Example SWMM Project
[OPTIONS]
FLOW_UNITS
INFILTRATION
FLOW_ROUTING
START_DATE
START_TIME
END_TIME
WET_STEP
DRY_STEP
ROUTING_STEP
CFS
GREEN_AMPT
KINWAVE
8/6/2002
10:00
18:00
00:15:00
01:00:00
00:05:00
[RAINGAGES]
;;Name
Format
Interval SCF DataSource SourceName
;;=========================================================
GAGE1
INTENSITY 0:15
1.0 TIMESERIES SERIES1
[EVAPORATION]
CONSTANT 0.02
[SUBCATCHMENTS]
;;Name Raingage Outlet Area
%Imperv
Width Slope
;;====================================================
AREA1
GAGE1
NODE1
2
80.0
800.0 1.0
AREA2
GAGE1
NODE2
2
75.0
50.0
1.0
[SUBAREAS]
;;Subcatch N_Imp N_Perv S_Imp S_Perv %ZER RouteTo
;;=====================================================
AREA1
0.2
0.02
0.02
0.1
20.0 OUTLET
AREA2
0.2
0.02
0.02
0.1
20.0 OUTLET
[INFILTRATION]
;;Subcatch
Suction
Conduct
InitDef
;;======================================
AREA1
4.0
1.0
0.34
AREA2
4.0
1.0
0.34
[JUNCTIONS]
;;Name
Elev
;;============
NODE1
10.0
NODE2
10.0
NODE3
5.0
NODE4
5.0
NODE6
1.0
NODE7
2.0
[DIVIDERS]
;;Name
Elev
Link
Type
Parameters
;;=======================================
NODE5
3.0
C6
CUTOFF 1.0
Figure 17-1 Example SWMM project file (continued on next page).
241
242
Command Line SWMM
[CONDUITS]
;;Name
Node1
Node2
Length N
Z1
Z2
Q0
;;===========================================================
C1
NODE1
NODE3
800
0.01
0
0
0
C2
NODE2
NODE4
800
0.01
0
0
0
C3
NODE3
NODE5
400
0.01
0
0
0
C4
NODE4
NODE5
400
0.01
0
0
0
C5
NODE5
NODE6
600
0.01
0
0
0
C6
NODE5
NODE7
400
0.01
0
0
0
[XSECTIONS]
;;Link
Type
G1
G2
G3
G4
;;===================================================
C1
RECT_OPEN
0.5
1
0
0
C2
RECT_OPEN
0.5
1
0
0
C3
CIRCULAR
1.0
0
0
0
C4
RECT_OPEN
1.0
1.0
0
0
C5
PARABOLIC
1.5
2.0
0
0
C6
PARABOLIC
1.5
2.0
0
0
[POLLUTANTS]
;;Name
Units Cppt Cgw Cii Kd Snow CoPollut CoFract
;;==========================================================
TSS
MG/L
0
0
0
0
Lead
UG/L
0
0
0
0
NO
TSS
0.20
[LANDUSES]
RESIDENTIAL
UNDEVELOPED
[WASHOFF]
;;Landuse
Pollutant
Type
Coeff Expon SweepEff BMPEff
;;===============================================================
RESIDENTIAL
TSS
EMC
23.4
0
0
0
UNDEVELOPED
TSS
EMC
12.1
0
0
0
[COVERAGES]
;;Subcatch
Landuse
Pcnt Landuse
Pcnt
;;==================================================
AREA1
RESIDENTIAL 80
UNDEVELOPED
20
AREA2
RESIDENTIAL 55
UNDEVELOPED
45
[TIMESERIES]
;Rainfall time series
SERIES1
0:0
0.1
SERIES1
0:45
0.1
[REPORT]
INPUT
SUBCATCHMENTS
NODES
LINKS
YES
ALL
ALL
C4
0:15
1:00
C5
1.0
0.0
0:30
2:00
0.5
0.0
C6
Figure 17-1 Example SWMM project file (continued from previous page).
Command Line SWMM
243
Section keywords can appear in mixed lower and upper case, and only the
first four characters (plus the open bracket) are used to distinguish one keyword
from another (e.g., [DIVIDERS] and [Divi] are equivalent). An option is
available in the [OPTIONS] section to choose flow units from among cubic feet
per second (CFS), gallons per minute (GPM), million gallons per day (MGD),
cubic meters per second (CMS), liters per second, (LPS), or million liters per
day (MLD). If cubic feet or gallons are chosen for flow units, then US units are
used for all other quantities. If cubic meters or liters are chosen, then metric
units apply to all other quantities. The default flow units are CFS.
A detailed description of the data in each section of the input file will now be
given. When listing the format of a line of data, mandatory keywords are
shown in boldface while optional items appear in parentheses. A list of keywords separated by a slash (YES/NO) means that only one of the words
should appear in the data line.
Section:
[TITLE]
Purpose:
Attaches a descriptive title to the problem being analyzed.
Format:
Any number of lines may be entered. The first line will be used as a page header
in the output report.
______________________________________________________________
Section:
[OPTIONS]
Purpose:
Provides values for various analysis options.
Format:
FLOW_UNITS
CFS / GPM / MGD / CMS / LPS / MLD
INFILTRATION
HORTON / GREEN_AMPT /CURVE_NUMBER
FLOW_ROUTING
STEADY / KINWAVE / DYNWAVE / NONE
LINK_OFFSETS
DEPTH / ELEVATION
FORCE-MAIN EQUATION H-W / D-W
IGNORE_RAINFALL
YES / NO
IGNORE_SNOWMELT
YES / NO
IGNORE_GROUNDWATER
YES / NO
IGNORE_ROUTING
YES / NO
IGNORE_QUALITY
YES / NO
ALLOW_PONDING
YES / NO
SKIP_STEADY_STATE
YES / NO
START_DATE
month/day/year
START_TIME
hours:minutes
END_DATE
month/day/year
END_TIME
hours:minutes
REPORT_START_DATE month/day/year
REPORT_START_TIME hours:minutes
SWEEP_START
month/day
SWEEP_END
month/day
DRY_DAYS
days
REPORT_STEP
hours:minutes:seconds
WET_STEP
hours:minutes:seconds
DRY_STEP
hours:minutes:seconds
244
Command Line SWMM
ROUTING_STEP
seconds
LENGTHENING_STEP
seconds
VARIABLE_STEP
value
INERTIAL_DAMPING
NONE / PARTIAL / FULL
NORMAL_FLOW_LIMITED
SLOPE / FROUDE / BOTH
MIN_SURFAREA
value
MIN_SLOPE
value
TEMPDIR
directory
Remarks:
FLOW_UNITS makes a choice of flow units. Selecting a US flow unit means
that all other quantities will be expressed in US units, while choosing a metric
flow unit will force all quantities to be expressed in metric units. The default is
CFS.
INFILTRATION selects a model for computing infiltration of rainfall into the
upper soil zone of subcatchments. The default model is HORTON.
FLOW_ROUTING determines which method is used to route flows through the
drainage system. STEADY refers to sequential steady state routing (i.e. hydrograph translation), KINWAVE to kinematic wave routing, DYNWAVE to
dynamic wave routing, and NONE is used to simulate runoff only. The default
routing method is KINWAVE.
LINK_OFFSETS determines the convention used to specify the position of a
link offset above the invert of its connecting node. DEPTH indicates that offsets
are expressed as the distance between the node invert and the link while
ELEVATION indicates that the absolute elevation of the offset is used.
FORCE_MAIN_EQUATION establishes whether the Hazen-Williams (H-W) or
the Darcy-Weisbach (D-W) equation will be used to compute friction losses for
pressurized flow in conduits that have been assigned a Circular Force Main
cross-section shape. The default is H-W.
IGNORE_RAINFALL is set to YES if all rainfall data and runoff calculations
should be ignored. In this case SWMM only performs flow and pollutant routing
based on user-supplied direct and dry weather inflows. The default is NO.
IGNORE_SNOWMELT is set to YES if snowmelt calculations should be ignored when a project file contains snow pack objects. The default is NO.
IGNORE_GROUNDWATER is set to YES if groundwater calculations should
be ignored when a project file contains aquifer objects. The default is NO.
IGNORE_ROUTING is set to YES if only runoff should be computed even if the
project contains drainage system links and nodes. The default is NO.
IGNORE_QUALITY is set to YES if pollutant washoff, routing, and treatment
should be ignored in a project that has pollutants defined. The default is NO.
ALLOW_PONDING determines whether excess water is allowed to collect atop
nodes and be re-introduced into the system as conditions permit. The default is
NO ponding. In order for ponding to actually occur at a particular node, a nonzero value for its Ponded Area attribute must be used.
SKIP_STEADY_STATE should be set to YES if flow routing computations
should be skipped during steady state periods of a simulation during which the
last set of computed flows will be used. A time step is considered to be in
Command Line SWMM
245
steady state if there has been no significant change in external inflows, storage
volumes, and either node water depths (for dynamic wave routing) or conduit
flows (for other forms of routing). The default for this option is NO.
START_DATE is the date when the simulation begins. If not supplied, a date of
1/1/2002 is used.
START_TIME is the time of day on the starting date when the simulation begins. The default is 12 midnight (0:00:00).
END_DATE is the date when the simulation is to end. The default is the start
date.
END_TIME is the time of day on the ending date when the simulation will end.
The default is 24:00:00.
REPORT_START_DATE is the date when reporting of results is to begin. The
default is the simulation start date.
REPORT_START_TIME is the time of day on the report starting date when
reporting is to begin. The default is the simulation start time of day.
SWEEP_START is the day of the year (month/day) when street sweeping operations begin. The default is 1/1.
SWEEP_END is the day of the year (month/day) when street sweeping operations end. The default is 12/31.
DRY_DAYS is the number of days with no rainfall prior to the start of the simulation. The default is 0.
REPORT_STEP is the time interval for reporting of computed results. The default is 0:15:00.
WET_STEP is the time step length used to compute runoff from subcatchments
during periods of rainfall or when ponded water still remains on the surface.
The default is 0:05:00.
DRY_STEP is the time step length used for runoff computations (consisting
essentially of pollutant buildup) during periods when there is no rainfall and no
ponded water. The default is 1:00:00.
ROUTING_STEP is the time step length in seconds used for routing flows and
water quality constituents through the conveyance system. The default is 600
sec (5 minutes) which should be reduced if using dynamic wave routing. Fractional values (e.g., 2.5) are permissible as are values entered in
hours:minutes:seconds format.
LENGTHENING_STEP is a time step, in seconds, used to lengthen conduits
under dynamic wave routing, so that they meet the Courant stability criterion
under full-flow conditions (i.e., the travel time of a wave will not be smaller than
the specified conduit lengthening time step). As this value is decreased, fewer
conduits will require lengthening. A value of 0 (the default) means that no conduits will be lengthened.
VARIABLE_STEP is a safety factor applied to a variable time step computed
for each time period under dynamic wave flow routing. The variable time step is
246
Command Line SWMM
computed so as to satisfy the Courant stability criterion for each conduit, and
yet not exceed the ROUTING_STEP value. If the safety factor is 0 (the default),
then no variable time step is used.
INERTIAL_DAMPING
indicates how the inertial terms in the Saint Venant
momentum equation will be handled under dynamic wave flow routing. Choosing NONE maintains these terms at their full value under all conditions.
Selecting PARTIAL will reduce the terms as flow comes closer to being critical
(and ignores them when flow is supercritical). Choosing FULL will drop the
terms altogether.
NORMAL_FLOW_LIMITED specifies which condition is checked to determine
if flow in a conduit is supercritical and should thus be limited to the normal flow.
Use SLOPE to check if the water surface slope is greater than the conduit
slope, FROUDE to check if the Froude number is greater than 1.0, or BOTH to
check both conditions. The default is BOTH.
MIN_SURFAREA is a minimum surface area used at nodes when computing
changes in water depth under dynamic wave routing. If 0 is entered, then the
2
default value of 12.566 ft (i.e., the area of a 4-ft diameter manhole) is used.
MIN_SLOPE is the minimum value allowed for a conduit’s slope (%). If zero
(the default) then no minimum is imposed (although SWMM uses a lower limit
on elevation drop of 0.001 ft (0.000 35 m) when computing a conduit slope).
TEMPDIR provides the name of a file directory (or folder) where SWMM writes
its temporary files. If the directory name contains spaces then it should be
placed within double quotes. If no directory is specified, then the temporary files
are written to the current directory that the user is working in.
__________________________________________________________________________
Section:
[REPORT]
Purpose:
Describes the contents of the report file that is produced.
Formats:
INPUT
CONTINUITY
FLOWSTATS
CONTROLS
SUBCATCHMENTS
NODES
names>
LINKS
Remarks:
YES / NO
YES / NO
YES / NO
YES / NO
ALL / NONE / <list of subcatchment names>
ALL / NONE / <list of node
ALL / NONE / <list of link names>
INPUT specifies whether or not a summary of the input data should be provided in
the output report. The default is NO.
CONTINUITY specifies whether continuity checks should be reported or not. The
default is YES.
FLOWSTATS specifies whether summary flow statistics should be reported or not.
The default is YES.
CONTROLS specifies whether all control actions taken during a simulation should
be listed or not. The default is NO.
247
Command Line SWMM
SUBCATCHMENTS gives a list of subcatchments whose results are to be reported. The default is NONE.
NODES gives a list of nodes whose results are to be reported. The default is
NONE.
LINKS gives a list of links whose results are to be reported. The default is NONE.
The SUBCATCHMENTS, NODES, and LINKS lines can be repeated multiple
times.
__________________________________________________________________________
Section:
[FILES]
Purpose:
Identifies optional interface files used or saved by a run.
Formats:
USE / SAVE
USE / SAVE
USE / SAVE
USE / SAVE
USE
SAVE
Remarks:
Fname
RAINFALL
Fname
RUNOFF
Fname
HOTSTART
Fname
RDII
INFLOWS
OUTFLOWS
Fname
Fname
Fname
name of interface file.
Refer to Chapter 14, section 14.7 for a description of interface files. Rainfall, Runoff, and RDII files can either be used or saved in a run, but not both. A run can
both use and save a Hot Start file (with different names).
______________________________________________________________
Section: [RAINGAGES]
Purpose: Identifies each rain gage that provides rainfall data for the study area.
Formats:
Name
Name
Form
Form
Intvl
Intvl
SCF
SCF
TIMESERIES
FILE Fname
Tseries
Sta
Units
Remarks:
Name name assigned to rain gage.
Form
form of recorded rainfall, either INTENSITY, VOLUME or
CUMULATIVE.
Intvl
time interval between gage readings in decimal hours or
hours:minutes format (e.g., 0:15 for 15-minute readings).
SCF
snow catch deficiency correction factor (use 1.0 for no adjustment).
Tseries
name of time series in [TIMESERIES] section with rainfall data.
Fname
name of external file with rainfall data. Rainfall files are discussed in
Chapter 14, section 14.3.
Sta
name of recording station used in the rain file.
Units
rain depth units used in the rain file, either IN (inches) or MM
(millimeters).
______________________________________________________________
Section:
[EVAPORATION]
Purpose:
Formats:
Specifies how daily evaporation rates vary with time for the study area.
CONSTANT
evap
MONTHLY
evap1 evap2 ... evap12
TIMESERIES
Tseries
248
Command Line SWMM
TEMPERATURE FILE
(pan1 pan2 ... pan12)
RECOVERY
patternID
DRY_ONLY
NO / YES
Remarks:
evap
evap1
…
evap12
Tseries
pan1
…
pan12
patternID
constant evaporation rate (in/day or mm/day).
evaporation rate in January (in/day or mm/day).
evaporation rate in December (in/day or mm/day).
name of time series in [TIMESERIES] section with evaporation data.
pan coefficient for January.
pan coefficient for December
name of a monthly time pattern
Use only one of the above formats (CONSTANT, MONTHLY, TIMESERIES,
TEMPERATURE, or FILE). If no [EVAPORATION] section appears, then evaporation is assumed to be 0.
TEMPERATURE indicates that evaporation rates will be computed from the daily
air temperatures contained in an external climate file whose name is provided in the
[TEMPERATURE] section (see below). This method also uses the site’s latitude,
which can also be specified in the [TEMPERATURE] section.
FILE indicates that evaporation data will be read directly from the same external
climate file used for air temperatures as specified in the [TEMPERATURE] section
(see below).
RECOVERY identifies an optional monthly time pattern of multipliers used to modify infiltration recovery rates during dry periods. For example, if the normal infiltration
recovery rate was 1% during a specific time period and a pattern factor of 0.8 applied to this period, then the actual recovery rate would be 0.8%.
DRY_ONLY determines if evaporation only occurs during periods with no precipitation. The default is NO.
______________________________________________________________
Section:
[TEMPERATURE]
Purpose:
Specifies daily air temperatures, monthly wind speed, and various snowmelt parameters for the study area . Required only when snowmelt is being modeled or
when evaporation rates are computed from daily temperatures or are read from an
external climate file.
Formats:
TIMESERIES
FILE Fname
Tseries
(Start)
WINDSPEED
WINDSPEED
MONTHLY s1 s2 … s11 s12
FILE
SNOWMELT
Stemp
ADC IMPERVIOUS
ADC PERVIOUS
Remarks:
Tseries
Fname
Start
s1
ATIwt
f.0
f.0
RNM
Elev
f.1 … f.8 f.9
f.1 … f.8 f.9
Lat
DTLong
name of time series in [TIMESERIES] section with temperature
data.
name of external Climate file with temperature data.
date to begin reading from the file in month/day/year format (default
is the beginning of the file).
average wind speed in January (mph or km/hr).
249
Command Line SWMM
…
s12
Stemp
ATIwt
RNM
Elev
Lat
DTLong
f.0
f.9
average wind speed in December (mph or km/hr).
air temperature at which precipitation falls as snow (deg F or C).
antecedent temperature index weight (default is 0.5).
negative melt ratio (default is 0.6).
average elevation of study area above mean sea level (ft or m) (default is 0).
latitude of the study area in degrees North (default is 50).
correction, in minutes of time, between true solar time and the
standard clock time (default is 0).
fraction of area covered by snow when ratio of snow depth to depth
at 100% cover is 0.
fraction of area covered by snow when ratio of snow depth to depth
at 100% cover is 0.9.
Use the TIMESERIES line to read air temperature from a time series or the FILE
line to read it from an external Climate file. Climate files are discussed in Chapter
14, section 14.4. If neither format is used, then air temperature remains constant at
70 degrees F.
Wind speed can be specified either by monthly average values or by the same
Climate file used for air temperature. If neither option appears, then wind speed is
assumed to be 0.
Separate Areal Depletion Curves (ADC) can be defined for impervious and pervious sub-areas. The ADC parameters will default to 1.0 (meaning no depletion) if
no data are supplied for a particular type of sub-area.
______________________________________________________________
Section:
[SUBCATCHMENTS]
Purpose:
Identifies each subcatchment within the study area. Subcatchments are land
area units which generate runoff from rainfall.
Format:
Name Rgage OutID Area
%Imperv Width
Slope Clength
(Spack)
Remarks:
Name name assigned to subcatchment.
Rgage
name of rain gage in [RAINGAGES] section assigned to subcatchment.
OutID
name of node or subcatchment that receives runoff from subcatchment.
Area
area of subcatchment (acres or hectares).
%Imperv
percent imperviousness of subcatchment.
Width
characteristic width of subcatchment (ft or meters).
Slope
subcatchment slope (percent).
Clength
total curb length (any length units).
Spack
name of snow pack object (from [SNOWPACKS] section) that characterizes snow accumulation and melting over the subcatchment.
__________________________________________________________________________
Section:
[SUBAREAS]
Purpose:
Supplies information about pervious and impervious areas for each subcatchment.
Each subcatchment can consist of a pervious sub-area, an impervious sub-area
with depression storage, and an impervious sub-area without depression storage.
Format:
Subcat
Nimp
Nperv
Simp
Sperv
%Zero
(RouteTo %Rted)
250
Remarks:
Command Line SWMM
Subcat
Nimp
Nperv
Simp
Sperv
%Zero
RouteTo
%Rted
subcatchment name.
Manning's n for overland flow over the impervious sub-area.
Manning's n for overland flow over the pervious sub-area.
depression storage for impervious sub-area (inches or mm).
depression storage for pervious sub-area (inches or mm).
percent of impervious area with no depression storage.
Use IMPERVIOUS if pervious area runoff runs onto impervious area, PERVIOUS if impervious runoff runs onto pervious area, or
OUTLET if both areas drain to the subcatchment's outlet (default =
OUTLET).
Percent of runoff routed from one type of area to another (default =
100).
Section: [INFILTRATION]
Purpose:
Supplies infiltration parameters for each subcatchment. Rainfall lost to infiltration
only occurs over the pervious sub-area of a subcatchment.
Formats:
Subcat
Subcat
Subcat
Remarks:
Subcat subcatchment name.
For Horton Infiltration:
MaxRate
Maximum infiltration rate on Horton curve (in/hr or mm/hr).
MinRate
Minimum infiltration rate on Horton curve (in/hr or mm/hr).
Decay
Decay rate constant of Horton curve (1/hr).
DryTime
Time it takes for fully saturated soil to dry (days).
MaxInf
Maximum infiltration volume possible (0 if not applicable) (in or
mm).
MaxRate
Suction
CurveNo
MinRate
Conduct
Conduct
Decay DryTime MaxInf
InitDef
DryTime
For Green-Ampt Infiltration:
Suction
Soil capillary suction (in or mm).
Conduct
Soil saturated hydraulic conductivity (in/hr or mm/hr).
InitDef
Initial soil moisture deficit (volume of voids / total volume).
For Curve-Number Infiltration:
CurveNo
SCS Curve Number.
Conduct
Soil saturated hydraulic conductivity (in/hr or mm/hr) (This property has been deprecated (sic) and is no longer used.
DryTime
Time it takes for fully saturated soil to dry (days).
Section:
[AQUIFERS]
Purpose:
Supplies parameters for each unconfined groundwater aquifer in the study area.
Aquifers consist of two zones – a lower saturated zone and an upper unsaturated
zone.
Formats:
Name
Remarks:
Name name assigned to aquifer.
Por
soil porosity (volumetric fraction).
WP
soil wilting point (volumetric fraction).
FC
soil field capacity (volumetric fraction).
K
saturated hydraulic conductivity (in/hr or mm/hr).
Por
WP FC K Ks Ps UEF LED GWR BE WTE UMC
Command Line SWMM
251
Ks
slope of the logarithm of hydraulic conductivity versus moisture deficit (i.e. porosity minus moisture content) curve (in/hr or mm/hr.
Ps
slope of soil tension versus moisture content curve (inches or mm).
UEF
fraction of total evaporation available for evapotranspiration in the
upper unsaturated zone.
LED
maximum depth into the lower saturated zone over which evapotranspiration can occur (ft or m).
GWR
rate of percolation from saturated zone to deep groundwater when
water table is at ground surface (in/hr or mm/hr).
BE
elevation of the bottom of the aquifer (ft or m).
WTE
water table elevation at start of simulation (ft or m).
UMC
unsaturated zone moisture content at start of simulation (volumetric
fraction).
__________________________________________________________________________
Section:
[GROUNDWATER]
Purpose:
Supplies parameters that determine the rate of groundwater flow between the
aquifer underneath a subcatchment and a node of the conveyance system.
Subcat Aquifer Node SurfEl A1 B1 A2 B2 A3 TW (H*)
Formats:
Remarks:
Subcat subcatchment name.
Aquifer
name of groundwater aquifer underneath the subcatchment.
Node
name of node in conveyance system exchanging groundwater with
aquifer.
SurfEl
surface elevation of subcatchment (ft or m).
A1
groundwater flow coefficient (see below).
B1
groundwater flow exponent (see below).
A2
surface water flow coefficient (see below).
B2
surface water flow exponent (see below).
A3
surface water – groundwater interaction coefficient (see below).
TW
fixed depth of surface water at receiving node (ft or m) (set to zero if
surface water depth will vary as computed by flow routing).
H*
groundwater table height which must be reached before any flow
occurs (ft or m). Leave blank to use the height of the receiving
node's invert above the aquifer bottom.
The flow coefficients are used in the following equation that determines a groundwater flow rate based on groundwater and surface water elevations:
Qgw = A1(H gw ! H *)B1 ! A2(H sw ! H *)B2 + A3H gw H sw
where:
Qgw =
groundwater flow (cfs per acre or cms per hectare),
Hgw =
height of saturated zone above bottom of aquifer (ft or m),
Hsw =
height of surface water at receiving node above aquifer bottom,
H* =
threshold groundwater table height (ft or m).
__________________________________________________________________________
Section:
[SNOWPACKS]
Purpose:
Specifies parameters that govern how snowfall accumulates and melts on the
plowable, impervious and pervious surfaces of subcatchments.
Formats:
Name
Name
Name
Name
PLOWABLE Cmin Cmax Tbase FWF SD0 FW0 SNN0
IMPERVIOUS Cmin Cmax Tbase FWF SD0 FW0 SD100
PERVIOUS
Cmin Cmax Tbase FWF SD0 FW0 SD100
REMOVAL Dplow Fout Fimp Fperv Fimelt (Fsub Scatch)
252
Remarks:
Command Line SWMM
Name name assigned to snowpack parameter set .
Cmin
minimum melt coefficient (in/hr-deg F or mm/hr-deg C).
Cmax
maximum melt coefficient (in/hr-deg F or mm/hr-deg C).
Tbase
snow melt base temperature (deg F or deg C).
FWF
ratio of free water holding capacity to snow depth (fraction).
SD0
initial snow depth (in or mm water equivalent).
FW0
initial free water in pack (in or mm).
SNN0
fraction of impervious area that can be plowed.
SD100
snow depth above which there is 100% cover (in or mm water
equivalent).
SDplow
depth of snow on plowable areas at which snow removal begins (in
or mm).
Fout
fraction of snow on plowable area transferred out of watershed.
Fimp
fraction of snow on plowable area transferred to impervious area by
plowing.
Fperv
fraction of snow on plowable area transferred to pervious area by
plowing.
Fimelt
fraction of snow on plowable area converted into immediate melt.
Fsub
fraction of snow on plowable area transferred to pervious area in
another subcatchment.
Scatch
name of subcatchment receiving the Fsubcatch fraction of transferred snow.
Use one set of PLOWABLE, IMPERVIOUS, and PERVIOUS lines for each snow
pack parameter set created. Snow pack parameter sets are associated with specific subcatchments in the [SUBCATCHMENTS] section. Multiple subcatchments
can share the same set of snow pack parameters.
The PLOWABLE line contains parameters for the impervious area of a subcatchment that is subject to snow removal by plowing but not to areal depletion. This
area is the fraction SNN0 of the total impervious area. The IMPERVIOUS line
contains parameter values for the remaining impervious area and the PERVIOUS
line does the same for the entire pervious area. Both of the latter two areas are
subject to areal depletion.
The REMOVAL line describes how snow removed from the plowable area is transferred onto other areas. The various transfer fractions should sum to no more than
1.0. If the line is omitted then no snow removal takes place.
______________________________________________________________
Section:
[JUNCTIONS]
Purpose:
Identifies each junction node of the drainage system. Junctions are points in
space where channels and pipes connect together. For sewer systems they can
be either connection fittings or manholes.
Format:
Name Elev
Remarks:
(Ymax
Y0
Ysur
Apond)
Name name assigned to junction node.
Elev
elevation of junction invert (ft or m).
Ymax
depth from ground to invert elevation (ft or m) (default is 0).
Y0
water depth at start of simulation (ft or m) (default is 0).
Ysur
max. additional head above ground elevation that manhole junction
can sustain under surcharge conditions (ft or m) (default is 0).
Apond
area subjected to surface ponding once water depth exceeds Ymax
2
2
(ft or m ) (default is 0).
253
Command Line SWMM
Section:
[OUTFALLS]
Purpose:
Identifies each outfall node (i.e., final downstream boundary) of the drainage system and the corresponding water stage elevation. Only one link can be incident on
an outfall node.
Formats:
Name
Name
Name
Name Elev
Name
Remarks:
Name
Elev
Stage
Tcurve
Tseries
Gate
Elev
Elev
Elev
TIDAL
Elev
FREE
Gate
NORMAL Gate
FIXED
Stage Gate
Tcurve Gate
TIMESERIES Tseries Gate
name assigned to outfall node.
invert elevation (ft or m).
elevation of fixed stage outfall (ft or m).
name of curve in [CURVES] section containing tidal height (i.e. outfall stage) v. hour of day over a complete tidal cycle.
name of time series in [TIMESERIES] section that describes how
outfall stage varies with time.
YES or NO depending on whether a flap gate is present that prevents reverse flow.
________________________________________________________________
Section:
[DIVIDERS]
Purpose:
Identifies each flow divider node of the drainage system. Flow dividers are junctions with exactly two outflow conduits where the total outflow is divided between
the two in a prescribed manner.
Formats:
Name
Name
Name
Name
Elev
Elev
Elev
Elev
DivLink
DivLink
DivLink
DivLink
OVERFLOW (Ymax Y0 Ysur Apond)
CUTOFF Qmin (Ymax Y0 Ysur Apond)
TABULAR Dcurve (Ymax Y0 Ysur Apond)
WEIR Qmin Ht Cd (Ymax Y0 Ysur Apond)
Remarks:
Name name assigned to divider node.
Elev
invert elevation (ft or m).
DivLink
name of link to which flow is diverted.
Qmin
flow at which diversion begins for either a CUTOFF or WEIR divider
(flow units).
Dcurve
name of curve for TABULAR divider that relates diverted flow to total flow.
Ht
height of WEIR divider (ft or m).
Cd
discharge coefficient for WEIR divider.
Ymax
depth from ground to invert elevation (ft or m) (default is 0).
Y0
water depth at start of simulation (ft or m) (default is 0).
Ysur
maximum additional head above ground elevation that node can
sustain under surcharge conditions (ft or m) (default is 0).
Apond
area subjected to surface ponding once water depth exceeds Ymax
2
2
(ft or m ) (default is 0).
__________________________________________________________________________
Section:
[STORAGE]
Purpose:
Identifies each storage node of the drainage system. Storage nodes can have any
shape as specified by a surface area versus water depth relation.
Formats:
Name Elev Ymax Y0 TABULAR Acurve (Apond Fevap SH HC IMD)
254
Command Line SWMM
Name Elev Ymax Y0 FUNCTIONAL A1 A2 A0 (Apond Fevap SH HS IMD)
Remarks:
Name name assigned to storage node.
Elev
invert elevation (ft or m).
Ymax
maximum water depth possible (ft or m).
Y0
water depth at start of simulation (ft or m).
2
m2
Acurve
name of curve in [CURVES] section with surface area (ft or ) as a
function of depth (ft or m) for TABULAR geometry.
A1
coefficient of FUNCTIONAL relation between surface area and
depth.
A2
exponent of FUNCTIONAL relation between surface area and
depth.
A0
constant of FUNCTIONAL relation between surface area and depth.
Apond
surface area subjected to ponding once water depth exceeds Ymax
2
2
(ft or m ) (default is 0).
Fevap
fraction of potential evaporation from surface realized (default is 0).
The following Green-Ampt infiltration parameters are only used when the storage
node is intended to act as an infiltration basin:
SH
Soil capillary suction head (in or mm).
HC
Soil saturated hydraulic conductivity (in/hr or mm/hr).
IMD
Initial soil moisture deficit (volume of voids / total volume).
2
A1, A2, and A0 are used in the following expression that relates surface area (ft
2
or m ) to water depth (ft or m) for a storage unit with FUNCTIONAL geometry:
A2
Area = A0 + A1 x Depth
__________________________________________________________________________
Section:
[CONDUITS]
Purpose:
Identifies each conduit link of the drainage system. Conduits are pipes or channels
that convey water from one node to another.
Format:
Name Node1
Remarks:
Name
Node1
Node2
Length
N
Z1
Z2
Q0
Node2
Length
N
Z1
Z2
(Q0)
name assigned to conduit link.
name of upstream node.
name of downstream node.
conduit length (ft or m).
value of n (i.e., roughness parameter) in Manning’s equation.
offset height of upstream end of conduit invert above the invert elevation of its upstream node (ft or m).
offset height of downstream end of conduit invert above the invert
elevation of its downstream node (ft or m).
flow in conduit at start of simulation (flow units) (default is 0).
The figure below illustrates the meaning of the Z1 and Z2 parameters.
Z1
Z2
255
Command Line SWMM
These offsets are expressed as a relative distance above the node invert if the LINK_OFFSETS
option is set to DEPTH (the default) or as an absolute elevation if it is set to ELEVATION.
__________________________________________________________________________
Section: [PUMPS]
Purpose:
Identifies each pump link of the drainage system.
Format:
Name
Remarks:
Name
Node1
Node2
Pcurve
Status
Startup
Shutoff
Node1
Node2
Pcurve
(Status
Startup
Shutoff)
name assigned to pump link.
name of node on inlet side of pump.
name of node on outlet side of pump.
name of pump curve listed in the [CURVES] section of the input.
status at start of simulation (either ON or OFF; default is ON).
depth at inlet node when pump turns on (ft or m) (default is 0).
depth at inlet node when pump shuts off (ft or m) (default is 0).
See Chapter 5, section 5.2 for a description of the different types of pumps available.
__________________________________________________________________________
Section:
[ORIFICES]
Purpose:
Identifies each orifice link of the drainage system. An orifice link serves to limit the
flow exiting a node and is often used to model flow diversions.
Format:
Name
Remarks:
Name
Node1
Node2
Type
Offset
Cd
Flap
Orate
Node1
Node2
Type
Offset Cd
(Flap Orate)
name assigned to orifice link.
name of node on inlet end of orifice.
name of node on outlet end of orifice.
orientation of orifice: either SIDE or BOTTOM.
amount that a Side Orifice’s bottom or the position of a Bottom Orifice is offset above the invert of inlet node (ft or m, expressed as
either a depth or as an elevation, depending on the
LINK_OFFSETS option setting).
discharge coefficient (unitless).
YES if flap gate present to prevent reverse flow, NO if not (default is
NO).
time in decimal hours to open a fully closed orifice (or close a fully
open one). Use 0 if the orifice can open/close instantaneously.
The geometry of an orifice’s opening must be described in the [XSECTIONS] section. The only allowable shapes are CIRCULAR and RECT_CLOSED (closed
rectangular).
Regulator
Structure
Orifice
Offset
256
Command Line SWMM
Section: [WEIRS]
Purpose:
Identifies each weir link of the drainage system. Weirs are used to model flow
diversions.
Format:
Name
Remarks:
Name
Node1
Node2
Type
Offset
Cd
Flap
EC
Cd2
Node1
Node2
Type
Offset
Cd
(Flap EC Cd2)
name assigned to weir link.
name of node on inlet side of wier.
name of node on outlet side of weir.
TRANSVERSE, SIDEFLOW, V-NOTCH, or TRAPEZOIDAL.
amount that the weir’s crest is offset above the invert of inlet node (ft
or m, expressed as either a depth or as an elevation, depending on
the LINK_OFFSETS option setting).
weir discharge coefficient (for CFS if using US flow units or CMS if
using metric flow units).
YES if flap gate present to prevent reverse flow, NO (default) if not.
number of end contractions for TRANSVERSE or TRAPEZOIDAL
weir (default is 0).
discharge coefficient for triangular ends of a TRAPEZOIDAL weir
(for CFS if using US flow units or CMS if using metric flow units) (default is value of Cd).
The geometry of a weir’s opening is described in the [XSECTIONS] section. The following
shapes must be used with each type of weir:
Weir Type
Cross-Section Shape
Transverse
RECT_OPEN
Sideflow
RECT_OPEN
V-Notch
TRIANGULAR
Trapezoidal
TRAPEZOIDAL
__________________________________________________________________________
Section:
[OUTLETS]
Purpose:
Identifies each outlet flow control device of the drainage system. These devices
are used to model outflows from storage units or flow diversions that have a userdefined relation between flow rate and water depth.
Format:
Remarks:
Name
Name
Name
Name
Name
Node1
Node2
Offset
Qcurve
Node1
Node1
Node1
Node1
Node2
Node2
Node2
Node2
Offset
Offset
Offset
Offset
TABULAR/DEPTH Qcurve (Flap)
TABULAR/HEAD Qcurve (Flap)
FUNCTIONAL/DEPTH C1 C2 (Flap)
FUNCTIONAL/HEAD C1 C2 (Flap)
name assigned to outlet link.
name of node on inlet end of link.
name of node on outflow end of link.
amount that the outlet is offset above the invert of inlet node (ft or m,
expressed as either a depth or as an elevation, depending on the
LINK_OFFSETSoption setting).
name of the rating curve listed in the [CURVES] section that describes outflow rate (flow units) as a function of:
•
water depth above the offset elevation at the inlet node (ft or
m) for a TABULAR/DEPTHoutlet
•
head difference (ft or m) between the inlet and outflow nodes
for a TABULAR/HEADoutlet.
257
Command Line SWMM
C1, C2
coefficient and exponent, respectively, of a power function that relates outflow (Q) to:
•
water depth (ft or m) above the offset elevation at the inlet node
for a FUNCTIONAL/DEPTH outlet
•
head difference (ft or m) between the inlet and outflow nodes for
a FUNCTIONAL/HEAD outlet (i.e., Q = C1(H)C2 where H is either depth or head).
Flap
YES if flap gate present to prevent reverse flow, NO (default) if not.
__________________________________________________________________________
Section: [XSECTIONS]
Purpose:
Provides cross-section geometric data for conduit and regulator links of the drainage system.
Formats:
Link
Link
Link
Remarks:
Shape Geom1 Geom2 Geom3 Geom4 ( Barrels Culvert)
CUSTOM Geom1 Curve
(Barrels)
IRREGULAR Tsect
Link
name of the conduit, orifice, or weir.
Shape
cross-section shape (see Table 17-1 below or Table 5-1 for available shapes).
Geom1
full height of the cross section (ft or m).
Geom2 - Geom4 auxiliary parameters (width, side slopes, etc). as listed in Table 17-1.
Barrels
number of barrels (i.e., number of parallel pipes of equal size, slope,
and roughness) associated with a conduit (default is 1).
Culvert
code number from Table 27-10 for the culvert’s inlet geometry if it is
a culvert subject to possible inlet flow control (leave blank otherwise).
Curve
name of a Shape Curve in the [CURVES] section that defines how
width varies with depth.
Tsect
name of an entry in the [TRANSECTS] section that describes the
cross-section geometry of an irregular channel.
The Culvert code number is used only for conduits that act as culverts and should be
analyzed for inlet control conditions using FHWA HEC-5 method.
The CUSTOM shape is a closed conduit whose width versus height is described by a
user-supplied Shape Curve.
An IRREGULAR cross-section is used to model an open channel whose geometry is
described by a Transect object.
Table 17-1 Geometric parameters of conduit cross sections.
Shape
CIRCULAR
FORCE_MAIN
FILLED_CIRCULAR2
RECT_CLOSED
RECT_OPEN
TRAPEZOIDAL
TRIANGULAR
HORIZ_ELLIPSE
VERT_ELLIPSE
Geom1
Diameter
Diameter
Diameter
Full Height
Full Height
Full Height
Full Height
Full Height
Full Height
Geom2
Geom3
Roughness1
Sediment Depth
Top Width
Top Width
Base Width
Left Slope
Top Width
Max. Width3
Max. Width3
Geom4
Right Slope
258
Command Line SWMM
ARCH (standard)
Size Code4
ARCH (non-standard)
Full Height
Max. Width
PARABOLIC
Full Height
Top Width
POWER
Full Height
Top Width
Exponent
RECT_TRIANGULAR
Full Height
Top Width
Triangle Height
RECT_ROUND
Full Height
Top Width
Bottom Radius
MODBASKETHANDLE
Full Height
Base Width
Top Radius5
EGG
Full Height
HORSESHOE
Full Height
GOTHIC
Full Height
CATENARY
Full Height
SEMIELLIPTICAL
Full Height
BASKETHANDLE
Full Height
SEMICIRCULAR
Full Height
1
C-factors are used when H-W is the FORCE MAIN EQUATION choice in the [OPTIONS] section
while roughness heights (in inches or mm) are used for D-W.
2
A circular conduit partially filled with sediment to a specified depth.
3
Set to zero to use a standard shaped elliptical pipe as cataloged in the publications mentioned in the
footnote below.
4
As listed in either the Concrete Pipe Design Manual" published by the American Concrete Pipe Association or Modern Sewer Design published by the American Iron and Steel Institute.
5
Set to zero to use a standard modified baskethandle shape whose top radius is half the base width.
__________________________________________________________________________
Section: [LOSSES]
Purpose:
Specifies minor head loss coefficients and flap gates for
Formats:
Conduit
Remarks:
Conduit
Kentry
Kexit
Kavg
Flap
Kentry
Kexit
Kavg
conduits.
(Flap)
name of conduit.
entrance minor head loss coefficient.
exit minor head loss coefficient.
average minor head loss coefficient across length of conduit.
YES if conduit has a flap valve that prevents back flow, NO
otherwise. (Default is NO).
Minor losses are only computed for the Dynamic Wave flow routing option (see
2
[OPTIONS] section). They are computed as Kv /2g where K = minor loss coefficient, v = velocity, and g = acceleration of gravity. Entrance losses are based on
the velocity at the entrance of the conduit, exit losses on the exit velocity, and average losses on the average velocity.
Only enter data for conduits that actually have minor losses or flap valves.
__________________________________________________________________________
Section: [TRANSECTS]
Purpose:
Describes the cross-section geometry of natural channels or conduits with irregular
shapes following the HEC-2 data format.
Formats:
NC Nleft
Nright Nchanl
X1 Name Nsta
Xleft Xright 0
GR Elev Station ... Elev Station
0
0 Lfactor Wfactor
Eoffset
Command Line SWMM
Remarks:
Nleft
Nright
Nchanl
Name
Nsta
Xleft
Xright
Lfactor
Wfactor
Eoffset
Elev
Station
259
Manning’s n of right overbank portion of channel (use 0 if no change
from previous NC line).
Manning’s n of right overbank portion of channel (use 0 if no change
from previous NC line.
Manning’s n of main channel portion of channel (use 0 if no change
from previous NC line.
name assigned to transect.
number of stations across cross-section at which elevation data is
supplied.
station position which ends the left overbank portion of the channel
(ft or m).
station position which begins the right overbank portion of the channel (ft or m).
meander modifier that represents the ratio of the length of a meandering main channel to the length of the overbank area that
surrounds it (use 0 if not applicable).
factor by which distances between stations should be multiplied to
increase (or decrease) the width of the channel (enter 0 if not applicable).
amount added (or subtracted) from the elevation of each station (ft
or m).
elevation of the channel bottom at a cross-section station relative to
some fixed reference (ft or m).
distance of a cross-section station from some fixed reference (ft or
m).
Transect geometry is described as shown below, assuming that one is looking in a
downstream direction:
The first line in this section must always be a NC line. After that, the NC line is only
needed when a transect has different Manning’s n values than the previous one.
The Manning’s n values on the NC line will supersede any roughness value entered for the conduit which uses the irregular cross-section.
There should be one X1 line for each transect. Any number of GR lines may follow, and each GR line can have any number of Elevation-Station data pairs. (In
HEC-2 the GR line is limited to 5 stations.)
The station that defines the left overbank boundary on the X1 line must correspond
to one of the station entries on the GR lines that follow. The same holds true for
260
Command Line SWMM
the right overbank boundary. If there is no match, a warning will be issued and the
program will assume that no overbank area exists.
The meander modifier is applied to all conduits that use this particular transect for
their cross section. It assumes that the length supplied for these conduits is that of
the longer main channel. SWMM will use the shorter overbank length in its calculations while increasing the main channel roughness to account for its longer length.
__________________________________________________________________________
Section: [CONTROLS]
Purpose:
Determines how pumps and regulators will be adjusted based on simulation time
or conditions at specific nodes and links.
Formats:
Each control rule is a series of statements of the form:
RULE
ruleID
IF
condition_1
AND
condition_2
OR
condition_3
AND
condition_4
Etc.
THEN
action_1
AND
action_2
Etc.
ELSE
action_3
AND
action_4
Etc.
PRIORITY
value
Remarks:
RuleID
condition_n
action_n
value
an ID label assigned to the rule.
a condition clause.
an action clause.
a priority value (e.g., a number from 1 to 5).
A condition clause of a Control Rule has the following format:
Object Name
Attribute
Relation
Value
where Object is a category of object, Name is the object’s assigned ID name, Attribute is the name of an attribute or property of the object, Relation is a relational
operator (=, <>, <, <=, >, >=), and Value is an attribute value.
Some examples of condition clauses are:
NODE N23 DEPTH > 10
PUMP P45 STATUS = OFF
SIMULATION TIME = 12:45:00
The objects and attributes that can appear in a condition clause are as follows:
Object
NODE
LINK
PUMP
Attributes
DEPTH
HEAD
INFLOW
FLOW
DEPTH
STATUS
FLOW
Value
numerical value
numerical value
numerical value
numerical value
numerical value
ON or OFF
numerical value
261
Command Line SWMM
ORIFICE
WEIR
SIMULATION
SETTING
SETTING
TIME
SIMULATION
DATE
CLOCKTIME
fraction open
fraction open
elapsed time in decimal
hours or hr:min:sec
month-day-year
time of day in hr:min:sec
An action clause of a Control Rule can have one of the following formats:
PUMP id STATUS = ON/OFF
PUMP/ORIFICE/WEIR/OUTLET id SETTING = value
where the meaning of SETTING depends on the object being controlled:
•
for Pumps it is a multiplier applied to the flow computed from the pump
curve,
•
for Orifices it is the fractional amount that the orifice is fully open,
•
for Weirs it is the fractional amount of the original freeboard that exists (i.e.
weir control is accomplished by moving the crest height up or down),
•
for Outlets it is a multiplier applied to the flow computed from the outlet's
rating curve.
Modulated controls are control rules that provide for a continuous degree of control
applied to a pump or flow regulator as determined by the value of some controller
variable, such as water depth at a node, or by time. The functional relation between the control setting and the controller variable is specified by using a control
curve, a time series, or a PID controller. To model these types of controls, the value entry on the right-hand side of the action clause is replaced by the keyword
CURVE, TIMESERIES, or PID and followed by the id name of the respective control curve or time series or by the gain, integral time (in minutes), and derivative
time (in minutes) of a PID controller. For direct action control the gain is a positive
number while for reverse action control it must be a negative number. By convention, the controller variable used in a control curve or PID control will always be the
object and attribute named in the last condition clause of the rule. The value specified for this clause will be the setpoint used in a PID controller.
Some examples of action clauses are:
PUMP P67 STATUS = OFF
ORIFICE O212 SETTING = 0.5
WEIR W25 SETTING = CURVE C25
ORIFICE ORI_23 SETTING = PID 0.1 0.1 0.0
Only the RULE, IF and THEN portions of a rule are required; the other portions are
optional. When mixing AND and OR clauses, the OR operator has higher precedence than AND, i.e.
IF A or B and C
is equivalent to
IF (A or B) and C.
If the interpretation was meant to be
IF A or (B and C)
then this can be expressed using two rules as in
IF A THEN ...
IF B and C THEN ...
The PRIORITY value is used to determine which rule applies when two or more
rules require that conflicting actions be taken on a link. A rule without a priority value always has a lower priority than one with a value. For two rules with the same
priority value, the rule that appears first is given the higher priority.
262
Command Line SWMM
Examples: ; Simple time-based pump control
RULE R1
IF SIMULATION TIME > 8
THEN PUMP 12 STATUS = ON
ELSE PUMP 12 STATUS = OFF
; Multi-condition orifice gate control
RULE R2A
IF NODE 23 DEPTH > 12
AND LINK 165 FLOW > 100
THEN ORIFICE R55 SETTING = 0.5
RULE R2B
IF NODE 23 DEPTH > 12
AND LINK 165 FLOW > 200
THEN ORIFICE R55 SETTING = 1.0
RULE R2C
IF NODE 23 DEPTH <= 12
OR LINK 165 FLOW <= 100
THEN ORIFICE R55 SETTING = 0
; PID control rule
RULE PID_1
IF NODE 23 DEPTH <> 12
THEN ORIFICE R55 SETTING = PID 0.5 0.1 0.0
; Pump station operation
RULE R3A
IF NODE N1 DEPTH > 5
THEN PUMP N1A STATUS = ON
RULE R3B
IF NODE N1 DEPTH > 7
THEN PUMP N1B STATUS = ON
RULE R3C
IF NODE N1 DEPTH <= 3
THEN PUMP N1A STATUS = OFF
AND PUMP N1B STATUS = OFF
__________________________________________________________________________
Section: [POLLUTANTS]
Purpose:
Identifies the pollutants being analyzed.
Format:
Name Units Crain Cgw Cii Kd (Sflag CoPoll CoFract Cdwf)
Remarks:
Name
Units
Crain
Cgw
Cii
Kdecay
Sflag
name assigned to pollutant.
concentration units (MG/L for milligrams per liter, UG/L for micrograms per liter, or #/L for direct count per liter).
concentration of pollutant in rainfall (concentration units).
concentration of pollutant in groundwater (concentration units).
concentration of pollutant in inflow/infiltration (concentration units).
first-order decay coefficient (1/days).
YES if pollutant buildup occurs only when there is snow cover, NO
otherwise (default is NO).
263
Command Line SWMM
CoPoll
CoFract
Cdwf
name of co-pollutant (default is no co-pollutant).
fraction of co-pollutant concentration (default is 0).
concentration of pollutant in dry weather flow (concentration units).
FLOW is a reserved word and cannot be used to name a pollutant.
If pollutant buildup is not restricted to times of snowfall and there is no co-pollutant,
then the last three parameters can be omitted.
When pollutant X has a co-pollutant Y, it means that fraction CoFract of pollutant
Y’s runoff concentration is added to pollutant X’s runoff concentration when wash
off from a subcatchment is computed.
The dry weather flow concentration can be overridden for any specific node of the
conveyance system by editing the node’s Inflows property
__________________________________________________________________________
Section:
[LANDUSES]
Purpose:
Identifies the various categories of land uses within the drainage area. Each subcatchment area can be assigned a different mix of land uses. Each land use can
be subjected to a different street sweeping schedule.
Format:
Name
(SweepInterval
Availability
LastSweep)
Remarks:
Name
land use name.
SweepInterval
days between street sweeping.
Availability
fraction of pollutant buildup available for removal by street
sweeping.
LastSweep
days since last sweeping at start of the simulation.
__________________________________________________________________________
Section:
[COVERAGES]
Purpose:
Specifies the percentage of a subcatchment’s area that is covered by each category of land use.
Format:
Subcat
Remarks:
Subcat
Landuse
Percent
Landuse
Percent
Landuse
Percent . . .
subcatchment name.
land use name.
percent of subcatchment area.
More than one pair of land use - percentage values can be entered per line. If
more than one line is needed, then the subcatchment name must still be entered
first on the succeeding lines.
If a land use does not pertain to a subcatchment, then it does not have to be entered.
If no land uses are associated with a subcatchment then no contaminants will
appear in the runoff from the subcatchment.
_________________________________________________________________________
264
Command Line SWMM
Section: [BUILDUP]
Purpose:
Specifies the rate at which pollutants build up over different land uses between
rain events.
Format:
Landuse
Remarks:
Landuse
land use name.
Pollutant
pollutant name.
FuncType
buildup function type: ( POW / EXP / SAT / EXT).
C1, C2, C3
buildup function parameters (see Table 17-2).
PerUnit AREA if buildup is per unit area, CURBLENGTH if per length of curb.
Pollutant
FuncType
C1
C2
C3
PerUnit
Buildup is measured in pounds (kilograms) per unit of area (or curb length) for
pollutants whose concentration units are either mg/L or ug/L. If the concentration
units are counts/L, then the buildup is expressed as counts per unit of area (or
curb length).
Table 17-2 Available pollutant buildup functions (t is antecedent dry days).
Name
Function
Power
Exponential
Saturation
External
POW
EXP
SAT
EXT
Equation
Min (C1, C2*tC3)
C1*(1 – exp(-C2*t))
C1*t / (C3 + t)
See below
For the EXT buildup function, C1 is the maximum possible buildup (mass per area
or curb length), C2 is a scaling factor, and C3 is the name of a Time Series that
contains buildup rates (as mass per area or curb length per day) as a function of
time.
__________________________________________________________________________
Section: [WASHOFF]
Purpose:
Specifies the rate at which pollutants are washed off from different land uses during rain events.
Format:
Landuse
Remarks:
Landuse
Pollutant
FuncType
C1, C2
SweepEffic
BMPEffic
Pollutant
FuncType
C1
C2
SweepEffic BMPEffic
land use name.
pollutant name.
washoff function type: EXP / RC / EMC.
washoff function coefficients(see Table 17-3).
street sweeping removal efficiency (percent)
.
BMP removal efficiency (percent).
Table 17-3 Pollutant wash off functions.
Name
EXP
RC
EMC
Function
Exponential
Rating Curve
Event Mean Concentration
Equation
C1 (runoff)C2 (buildup)
C1 (runoff)C2
C1
Units
Mass/hour
Mass/sec
Mass/Liter
Each washoff function expresses its results in different units.
265
Command Line SWMM
For the Exponential function the runoff variable is expressed in catchment depth
per unit of time (inches per hour or millimeters per hour), while for the Rating
Curve function it is in whatever flow units were specified in the [OPTIONS] section
of the input file (e.g., CFS, CMS, etc.). The buildup parameter in the Exponential
function is the current total buildup over the subcatchment’s land use area in mass
-C2
units. The units of C1 in the Exponential function are (in/hr) per hour (or (mm/hr)
-C2
per hour). For the Rating Curve function, the units of C1 depend on the flow
units employed. For the EMC (event mean concentration) function, C1 is always in
concentration units.
Section:
[TREATMENT]
Purpose:
Specifies the degree of treatment received by pollutants at specific nodes of the
drainage system.
Format:
Node
Remarks:
Node
Pollut
Result
Func
Pollut
Result = Func
Name of node where treatment occurs.
Name of pollutant receiving treatment.
Result computed by treatment function. Choices are:
C – function computes effluent concentration
R – function computes fractional removal.
mathematical function expressing treatment result in terms of pollutant concentrations, pollutant removals, and other standard
variables (see below).
Treatment functions can be any well-formed mathematical expression involving:
•
inlet pollutant concentrations (use the pollutant name to represent a concentration)
•
removal of other pollutants (use R_ prepended to the pollutant name to represent removal)
•
process variables which include:
FLOW for flow rate into node (user’s flow units)
DEPTH for water depth above node invert (ft or m)
2
m2
AREA for node surface area (ft or )
DT for routing time step (seconds)
HRT for hydraulic residence time (hours)
Examples:
; 1-st order decay of BOD
Node23 BOD C = BOD * exp(-0.05*HRT)
; lead removal is 20% of TSS removal
Node23 Lead R = 0.2 * R_TSS
__________________________________________________________________________
Section: [DWF]
Purpose:
Specifies dry weather flow and its quality entering the drainage system at specific
nodes.
Format:
Node
Remarks:
Node
Item
Value
Item
Value
(Pat1
Pat2 Pat3 Pat4)
name of node where dry weather flow enters.
keyword FLOW for flow or pollutant name for quality constituent.
average baseline value for corresponding Item (flow or concentration units).
266
Command Line SWMM
Pat1, Pat2, etc. names of up to four time patterns appearing in the
[PATTERNS] section.
The actual dry weather input will equal the product of the baseline value and any
adjustment factors supplied by the specified patterns. (If not supplied, an adjustment factor defaults to 1.0.)
__________________________________________________________________________
Section: [PATTERNS]
Purpose:
Specifies time pattern of dry weather flow or quality in the form of adjustment factors applied as multipliers to baseline values.
Format:
Name
Name
Name
Name
Remarks:
Name
name used to identify the pattern.
Factor1, Factor2, etc.
multiplier values.
MONTHLY
DAILY
HOURLY
WEEKEND
Factor1
Factor1
Factor1
Factor1
Factor2
Factor2
Factor2
Factor2
...
...
...
...
Factor12
Factor7
Factor24
Factor24
The MONTHLY format is used to set monthly pattern factors for dry weather flow
constituents.
The DAILY format is used to set dry weather pattern factors for each day of the
week, where Sunday is day 1.
The HOURLY format is used to set dry weather factors for each hour of the of the
day starting from midnight. If these factors are different for weekend days than for
weekday days then the WEEKEND format can be used to specify hourly adjustment factors just for weekends.
More than one line can be used to enter a pattern’s factors by repeating the pattern’s name (but not the pattern type) at the beginning of each additional line.
The pattern factors are applied as multipliers to any baseline dry weather flows or
quality concentrations supplied in the [DWF] section.
Examples: ; Day of week adjustment factors
D1 DAILY
0.5 1.0 1.0 1.0 1.0 1.0 0.5
D2 DAILY
0.8 0.9 1.0 1.1 1.0 0.9 0.8
; Hourly adjustment factors
H1 HOURLY 0.5 0.6 0.7 0.8 0.8 0.9
H1
1.1 1.2 1.3 1.5 1.1 1.0
H1
0.9 0.8 0.7 0.6 0.5 0.5
H1
0.5 0.5 0.5 0.5 0.5 0.5
__________________________________________________________________________
Section: [INFLOWS]
Purpose:
Formats:
Specifies external hydrographs and pollutographs that enter the drainage system
at specific nodes.
Node FLOW Fseries (FLOW 1.0 Sfactor Base Pat)
Node Pollut Pseries (Format (Mfactor Sfactor Base Pat)
267
Command Line SWMM
Remarks:
Fseries
Pollut
Pseries
Format
Mfactor
Sfactor
Base
Pat
Node
name of node where external inflow enters.
name of time series in [TIMESERIES] section describing how external inflows vary with time.
name of pollutant.
name of time series describing how external pollutant loading varies
with time.
CONCEN if pollutant inflow is described as a concentration, MASS if
it is described as a mass flow rate (default is CONCEN).
the factor that converts the inflow’s mass flow rate units into the project’s mass units per second, where the project’s mass units are
those specified for the pollutant in the [POLLUTANTS] section (default is 1.0 - see example below).
scaling factor that multiplies the recorded time series values (default
is 1.0).
constant baseline value added to the time series value (default is
0.0).
name of optional time pattern in [PATTERNS] section used to adjust
the baseline value on a periodic basis.
External inflows are represented by both a constant and time varying component as
follows:
Inflow = (Baseline value)*(Pattern factor) + (Scaling factor)*(Time series value)
If an external inflow of a pollutant concentration is specified for a node, then there
must also be an external inflow of FLOW provided for the same node, unless the
node is an Outfall. In that case a pollutant can enter the system during periods
when the outfall is submerged and reverse flow occurs.
Examples: NODE2
NODE33
FLOW
TSS
N2FLOW
N33TSS
CONCEN
;Mass inflow of BOD in time series N65BOD given in
lbs/hr ;(126 converts lbs/hr to mg/sec)
NODE65 BOD N65BOD MASS 126
;Flow inflow with baseline and scaling factor
N176 FLOW FLOW_176 FLOW 1.0 0.5 12.7 FlowPat
__________________________________________________________________________
Section: [LOADINGS]
Purpose:
Specifies the pollutant buildup that exists on each subcatchment at the start of a
simulation.
Format:
Subcat
Remarks:
Subcat
Pollut
InitBuildup
Pollut
InitBuildup
Pollut
InitBuildup ...
name of a subcatchment.
name of a pollutant.
initial buildup of pollutant (lbs/acre or kg/hectare).
More than one pair of pollutant - buildup values can be entered per line. If more
than one line is needed, then the subcatchment name must still be entered first on
the succeeding lines.
If an initial buildup is not specified for a pollutant, then its initial buildup is computed by applying the DRY_DAYS option (specified in the [OPTIONS] section) to the
pollutant’s buildup function for each land use in the subcatchment.
__________________________________________________________________________
268
Command Line SWMM
Section: [RDII]
Purpose:
Specifies the parameters that describe rainfall-dependent infiltration/inflow (RDII)
entering the drainage system at specific nodes.
Format:
Node
Remarks:
Node
UHgroup
UHgroup
SewerArea
name of a node.
name of an RDII unit hydrograph group specified in the
[HYDROGRAPHS] section.
SewerArea
area of the sewershed which contributes RDII to the node
(acres or hectares).
__________________________________________________________________________
Section: [HYDROGRAPHS]
Purpose: Specifies the shapes of the triangular unit hydrographs that determine the amount of
rainfall-dependent infiltration/inflow (RDII) entering the drainage system.
Formats: Name Raingage Name Month SHORT/MEDIUM/LONG R T K (Dmax Drec D0)
Remarks:
Name
name assigned to a unit hydrograph group.
Raingage name of the rain gage used by the unit hydrograph group.
Month
month of the year (e.g., JAN, FEB, etc. or ALL for all months).
R
response ratio for the unit hydrograph.
T
time to peak (hours) for the unit hydrograph.
K
recession limb ratio for the unit hydrograph.
Dmax
maximum initial abstraction depth available (in rain depth units).
Drec
initial abstraction recovery rate (in rain depth units per day)
D0
initial abstraction depth already filled at the start of the simulation
(in rain depth units).
For each group of unit hydrographs, use one line to specify its rain gage followed
by as many lines as are needed to define each unit hydrograph used by the
group throughout the year. Three separate unit hydrographs, that represent the
short-term, medium-term, and long-term RDII responses, can be defined for
each month (or all months taken together). Months not listed are assumed to
have no RDII.
The response ratio (R) is the fraction of a unit of rainfall depth that becomes
RDII. The sum of the ratios for a set of three hydrographs does not have to equal
1.0.
The recession limb ratio (K) is the ratio of the duration of the hydrograph’s recession limb to the time to peak (T) making the hydrograph time base equal to
T*(1+K) hours. The area under each unit hydrograph is 1 inch (or mm).
The optional initial abstraction parameters determine how much rainfall is lost at
the start of a storm to interception and depression storage. If not supplied then
the default is no initial abstraction.
Examples:
; All three unit hydrographs in this group have the same shapes except those
; in July, which have only a short- and medium-term response with different
; shapes than those for the other months of the year
UH101 RG1
UH101 ALL SHORT 0.033 1.0 2.0
UH101 ALL MEDIUM 0.300 3.0 2.0
269
Command Line SWMM
UH101 ALL LONG 0.033 10.0 2.0
UH101 JUL SHORT 0.033 0.5 2.0
UH101 JUL MEDIUM 0.011 2.0 2.0
__________________________________________________________________________
Section:
[CURVES]
Purpose:
Describes a relationship between two variables in tabular format.
Format:
Name
Remarks:
Type
X-value
Y-value ...
Name name assigned to table
Type
STORAGE / SHAPE / DIVERSION / TIDAL / PUMP1 / PUMP2 /
PUMP3 / PUMP4 / RATING / CONTROL
X-value
an x (independent variable) value
Y-value
the y (dependent variable) value corresponding to x
Multiple pairs of x-y values can appear on a line. If more than one line is needed,
repeat the curve's name (but not the type) on subsequent lines. The x-values must
be entered in increasing order.
Choices for curve type have the following meanings (flows are expressed in the
user’s choice of flow units set in the [OPTIONS] section):
STORAGE (surface area in ft2 (m2) v. depth in ft (m) for a storage unit node)
SHAPE
(width v. depth for a custom closed cross-section, both normalized with respect to full depth)
DIVERSION (diverted outflow v. total inflow for a flow divider node)
TIDAL
(water surface elevation in ft (m) v. hour of the day for an outfall
node)
PUMP1
(pump outflow v. increment of inlet node volume in ft3 (m3))
PUMP2
(pump outflow v. increment of inlet node depth in ft (m))
PUMP3
(pump outflow v. head difference between outlet and inlet nodes
in ft (m))
PUMP4
(pump outflow v. continuous depth in ft (m))
RATING
(outlet flow v. head in ft (m))
CONTROL (control setting v. controller variable)
See Chapter 5, section 5.2 for illustrations of the different types of pump curves.
Examples: ;Storage curve (x = depth, y = surface area)
AC1 STORAGE 0 1000 2 2000 4 3500 6 4200 8 5000
;Type1 pump curve (x = inlet wet well volume, y = flow )
PC1 PUMP1
PC1 100 5 300 10 500 20
__________________________________________________________________________
Section:
[TIMESERIES]
Purpose:
Describes how a quantity varies over time.
Formats:
Name ( Date )
Name Time
Name
Remarks:
Name name assigned to time series.
Hour
Value ...
Value ...
File
Fname
270
Command Line SWMM
Date
Hour
Time
Value
Fname
date in Month/Day/Year format (e.g., June 15, 2001 would be
6/15/2001).
24-hour military time (e.g., 8:40 pm would be 20:40) relative to the
last date specified (or to midnight of the starting date of the simulation if no previous date was specified).
hours since the start of the simulation, expressed as a decimal
number or as hours:minutes.
value corresponding to given date and time.
name of a file in which the time series data are stored.
There are two options for supplying the data for a time series:
•
directly within this input file section as described by the first two formats;
and
•
through an external data file named with the third format.
When direct data entry is used, multiple date-time-value or time-value entries can
appear on a line. If more than one line is needed, the table's name must be repeated as the first entry on subsequent lines.
When an external file is used, each line in the file must use the same formats listed
above, except that only one date-time-value (or time-value) entry is allowed per
line. Any line that begins with a semicolon is considered a comment line and is ignored. Blank lines are not allowed.
Note that there are two methods for describing the occurrence time of time series
data:
▪
as calendar date/time of day (which requires that at least one date, at the
start of the series, be entered)
▪
as elapsed hours since the start of the simulation.
For the first method, dates need only be entered at points in time when a new day
occurs.
Examples:
TS1
TS1
;Rainfall time series with dates specified
6-15-2001 7:00 0.1
8:00 0.2 9:00 0.05 10:00 0
6-21-2001 4:00 0.2
5:00 0
14:00 0.1 15:00 0
;Inflow hydrograph - time relative to start of simulation
;(hours can be expressed as decimal hours or hr:min)
HY1 0 0 1.25 100 2:30 150 3.0 120 4.5 0
HY1 32:10 0 34.0 57 35.33 85 48.67 24 50 0
Section:
[LID_CONTROLS]
Purpose:
Defines scale-independent LID controls that can be deployed within subcatchments.
Formats:
Name
Type
One or more of the following lines depending on Type:
Name
SURFACE StorHt VegFrac Rough Slope Xslope
Name
SOIL Thick Por FC WP Ksat Kcoeff Suct
Name
PAVEMENT Thick Vratio FracImp Perm Vclog
Name
STORAGE Height Vratio Filt Vclog
Name
DRAIN Coeff Expon Offset Delay
Remarks:
Name
Name assigned to LID process.
271
Command Line SWMM
Type
BC for bio-retention cell; PP for porous pavement; IT for infiltration trench; RB for rain barrel; VS for vegetative swale.
For LIDs with Surface Layers:
StorHt
When confining walls or berms are present this is the maximum depth to which water can pond above the surface of the
unit before overflow occurs (in inches or mm). For LIDs that
experience overland flow it is the height of any surface depression storage. For swales, it is the height of its trapezoidal
cross section.
VegFrac Fraction of the area above the surface that is filled with vegetation.
Rough
Manning's n for overland flow over the surface of porous
pavement or a vegetative swale. Use 0 for other types of
LIDs.
Slope
Slope of porous pavement surface or vegetative
swale (percent). Use 0 for other types of LIDs.
Xslope
Slope (run over rise) of the side walls of a vegetative swale's
cross section. Use 0 for other types of LIDs.
For LIDs with Pavement Layers:
Thick
Thickness of the pavement layer (inches or mm).
Vratio
Void ratio (volume of void space relative to the volume of solids in the pavement for continuous systems or for the fill
material used in modular systems). Note that porosity = void
ratio / (1 + void ratio).
FracImp Ratio of impervious paver material to total area for modular
sytems; 0 for continuous porous pavement systems.
Perm
Permeability of the concrete or asphalt used in continuous
systems or hydraulic conductivity of the fill material (gravel or
sand) used in modular systems (in/hr or mm/hr).
Vclog
Number of pavement layer void volumes of runoff treated it
takes to completely clog the pavement. Use a value of 0 to
ignore clogging.
For LIDs with Soil Layers:
Thick
Thickness of the soil layer (inches or mm).
Por
Soil porosity (volume of pore space relative to total volume).
The following table shows which layers are required (x) or are optional (o) for
each type of LID process:
LID Type
Bio-Retention Cell
Porous Pavement
Infiltration Trench
Rain Barrel
Vegetative Swale
Surface
x
x
x
Pavement
Soil
x
x
Storage
x
x
x
x
Underdrain
o
o
o
x
x
The equation used to compute flow rate out of the underdrain per unit area of the
n
LID (in in/hr or mm/hr) is q = C(h ! H d ) where q is outflow, h is height of stored
water (inches or mm) and Hd is the drain offset height.
The actual dimensions of an LID control are provided in the [LID_USAGE] section when it is placed in a particular subcatchment.
Examples:
;A street planter with no underdrain
Planter BC
272
Command Line SWMM
Planter SURFACE 6 0.3 0 0 0
Planter SOIL 24 0.5 0.1 0.05 1.2 2.4
Planter STORAGE 12 0.5 20 0
;A green roof with impermeable bottom
GR1 BC GR1 SURFACE 3 0 0 0 0
GR1 SOIL 3 0.5 0.1 0.05 1.2 2.4
GR1 STORAGE 3 0.5 0 0
GR1 DRAIN 5 0.5 0 0
;A rain barrel that drains 6 hours after rainfall ends
RB12 RB
RB12 STORAGE 36 0 0 0
RB12 DRAIN 10 0.5 0 6
;A grass swale 24 in. high with 5:1 side slope
Swale VS
Swale SURFACE 24 0 0.2 3 5
Section: [LID_USAGE]
Purpose: Deploys LID controls within specific subcatchment areas.
Format:
(RptFile)
Remarks:
Subcat LID Number Area Width InitSat FromImp ToPerv
Subcat The name of the subcatchment using the LID process.
LID
The name of an LID process defined in the
[LID_CONTROLS] section.
Number The number of replicate LID units deployed. or m 2
Area
The area of each replicate unit (ft2).
Width
The width of the outflow face of each identical LID unit (in ft or m).
This parameter only applies to LID processes such as porous
pavement and vegetative swales that use overland flow to convey
surface runoff off of the unit. (The other LID processes, such as bioretention cells and infiltration trenches simply spill any excess captured runoff over their berms.)
InitSat
The percent to which the unit's soil layer or storage layer is initially
filled with water.
FromImp The percent of the impervious portion of the subcatchment's nonLID area whose runoff is treated by the LID units. If the LID unit
treats only direct rainfall, such as with a green roof, then this value
should be 0. If the LID takes up the entire subcatchment then this
field is ignored.
ToPerv 1 if the outflow from the LID is returned onto the subcatchment's
pervious area rather than going to the subcatchment's outlet; 0 otherwise. An example of where this might apply is a rain barrel whose
contents are used to irrigate a lawn area. This field is ignored if the
LID takes up the entire subcatchment.
RptFile Optional name of a file to which detailed time series results for the
LID will be written. Enclose the name in double quotes if it contains
spaces and include the full path if it is different than the SWMM input file path.
More than one type of LID process can be deployed within a subcatchment as
long as their total area does not exceed that of the subcatchment and the total
percent impervious area treated does not exceed 100.
Command Line SWMM
Examples:
273
;34 rain barrels of 12 sq ft each are placed in
;subcatchment S1. They are initially empty and treat 17%
;of the runoff from the subcatchment’s impervious area.
;The outflow from the barrels is returned to the
;subcatchment’s pervious area.
S1 RB14 34 12 0 0 17 1
;Subcatchment S2 consists entirely of a single vegetative
;swale 200 ft long by 50 ft wide.
S2 Swale 1 10000 50 0 0 0 “swale.rpt”
17.3 Map Data Section
SWMM’s graphical user interface (GUI) can display a schematic map of the
drainage area being analyzed. This map displays subcatchments as polygons,
nodes as circles, links as polylines, and rain gages as bitmap symbols. In addition it can display text labels and a backdrop image, such as a street map. The
GUI has tools for drawing, editing, moving, and displaying these map elements.
The map’s coordinate data are stored in the format described below. Normally
these data are simply appended to the SWMM input file by the GUI so users do
not have to concern themselves with it. However it is sometimes more convenient to import map data from some other source, such as a CAD or GIS file,
rather than drawing a map from scratch using the GUI. In this case the data can
be added to the SWMM project file using any text editor or spreadsheet program. SWMM does not provide any automated facility for converting coordinate
data from other file formats into the SWMM map data format.
SWMM's map data are organized into the following seven sections:
[MAP]
X,Y coordinates of the map’s bounding rectangle
[POLYGONS]
X,Y coordinates for each vertex of subcatchment
polygons
[COORDINATES]
X,Y coordinates for nodes
[VERTICES]
X,Y coordinates for each interior vertex of polyline links
[LABELS]
X,Y coordinates and text of labels
[SYMBOLS]
X,Y coordinates for rain gages
[BACKDROP]
X,Y coordinates of the bounding rectangle and
file name of the backdrop image.
Figure 17-3 displays a sample map and Figure 17-2 the data that describes it.
Note that only one link, 3, has interior vertices which give it a curved shape.
Also observe that this map’s coordinate system has no units, so that the positions
of its objects may not necessarily coincide to their real-world locations.
274
Command Line SWMM
A detailed description of each map data section will now be given. Remember that map data are only used as a visualization aid for SWMM’s GUI and
they play no role in any of the runoff or routing computations. Map data are not
needed for running the command line version of SWMM.
[MAP]
DIMENSIONS
UNITS
0.00
None
[COORDINATES]
;;Node
N1
N2
N3
N4
4006.62
6953.64
4635.76
8509.93
[VERTICES]
;;Link
3
3
5430.46
7251.66
[SYMBOLS]
;;Gage
G1
5298.01
0.00
10000.00 10000.00
X-Coord
Y-Coord
5463.58
4768.21
3443.71
827.81
X-Coord
Y-Coord
2019.87
927.15
X-Coord
Y-Coord
9139.07
[Polygons]
;;Subcatchment
X-Coord
Y-Coord
S1
3708.61
8543.05
S1
4834.44
7019.87
S1
3675.50
4834.44
< additional vertices not listed >
S2
6523.18
8079.47
S2
8112.58
8841.06
[LABELS]
;;X-Coord
5033.11
1655.63
7715.23
Y-Coord
8807.95
7450.33
7549.67
Label
"G1"
"S1"
"S2"
Figure 17-2 Data for map shown in Figure 17-3.
Figure 17-3 Example study area map.
275
Command Line SWMM
Section: [MAP]
Purpose:
Provides dimensions and distance units for the map.
Formats:
DIMENSIONS
X1 Y1 X2 Y2
UNITS FEET / METERS / DEGREES / NONE
Remarks: X1
lower-left X coordinate of full map extent
Y1
lower-left Y coordinate of full map extent
X2
upper-right X coordinate of full map extent
Y2
upper-right Y coordinate of full map extent
__________________________________________________________________________
Section:
[COORDINATES]
Purpose:
Assigns X,Y coordinates to drainage system nodes.
Format:
Node
Xcoord
Ycoord
Remarks:
Node
name of node.
Xcoord
horizontal coordinate relative to origin in lower left of map.
Ycoord
vertical coordinate relative to origin in lower left of map.
________________________________________________________________________
Section:
[VERTICES]
Purpose:
Assigns X,Y coordinates to interior vertex points of curved drainage system links.
Format:
Remarks:
Link Xcoord Ycoord
Link
name of link.
Xcoord
horizontal coordinate of vertex relative to origin in lower left of
map.
Ycoord
vertical coordinate of vertex relative to origin in lower left of map.
Include a separate line for each interior vertex of the link, ordered from the inlet
node to the outlet node.
Straight-line links have no interior vertices and therefore are not listed in this section.
__________________________________________________________________________
Section:
[POLYGONS]
Purpose:
Assigns X,Y coordinates to vertex points of polygons that define a subcatchment
boundary.
Format:
Subcat
Remarks:
Subcat
Xcoord
map.
Ycoord
Xcoord
Ycoord
name of subcatchment.
horizontal coordinate of vertex relative to origin in lower left of
vertical coordinate of vertex relative to origin in lower left of map.
Include a separate line for each vertex of the subcatchment polygon, ordered in a
consistent clockwise or counter-clockwise sequence.
__________________________________________________________________________
276
Command Line SWMM
Section:
[SYMBOLS]
Purpose:
Assigns X,Y coordinates to rain gage symbols.
Format:
Gage
Xcoord
Ycoord
Remarks:
Gage
name of rain gage.
Xcoord
horizontal coordinate relative to origin in lower left of map.
Ycoord
vertical coordinate relative to origin in lower left of map.
__________________________________________________________________________
Section:
[LABELS]
Purpose:
Assigns X,Y coordinates to user-defined map labels.
Format:
Xcoord
Remarks:
Xcoord
Ycoord
Label
Anchor
Font
Size
Bold
Italic
Ycoord
Label
(Anchor
Font
Size
Bold
Italic)
horizontal coordinate relative to origin in lower left of map.
vertical coordinate relative to origin in lower left of map.
text of label surrounded by double quotes.
name of node or subcatchment that anchors the label on zoom-ins
(use an empty pair of double quotes if there is no anchor).
name of label’s font (surround by double quotes if the font name includes spaces).
font size in points.
YES for bold font, NO otherwise.
YES for italic font, NO otherwise.
Use of the anchor node feature will prevent the label from moving outside the
viewing area when the map is zoomed in on.
If no font information is provided then a default font is used to draw the label.
__________________________________________________________________________
Section:
[BACKDROP]
Purpose:
Specifies file name and coordinates of map’s backdrop image.
Formats:
FILE
DIMENSIONS
Remarks:
Fname name of file containing backdrop image
X1
lower-left X coordinate of backdrop image
Y1
lower-left Y coordinate of backdrop image
X2
upper-right X coordinate of backdrop image
Y2
upper-right Y coordinate of backdrop image
Fname
X1 Y1 X2 Y2
Chapter 18
Error Messages
ERROR 101: memory allocation error.
There is not enough physical memory in the computer to analyze the study area.
ERROR 103: cannot solve KW equations for Link xxx.
The internal solver for Kinematic Wave routing failed to converge for the specified link at some stage of the simulation.
ERROR 105: cannot open ODE solver.
The system could not open its Ordinary Differential Equation solver.
ERROR 107: cannot compute a valid time step.
A valid time step for runoff or flow routing calculations (i.e., a number greater
than 0) could not be computed at some stage of the simulation.
ERROR 108: ambiguous outlet ID name for Subcatchment xxx.
The name of the element identified as the outlet of a subcatchment belongs to
both a node and a subcatchment in the project's data base.
ERROR 109: invalid parameter values for Aquifer xxx.
The properties entered for an aquifer object were either invalid numbers or were
inconsistent with one another (e.g. the soil field capacity was higher than the
porosity).
ERROR 111: invalid length for Conduit xxx.
Conduits cannot have zero or negative lengths.
ERROR 113: invalid roughness for Conduit xxx.
Conduits cannot have zero or negative roughness values.
ERROR 114: invalid number of barrels for Conduit xxx.
Conduits must consist of one or more barrels.
ERROR 115: adverse slope for Conduit xxx.
Under Steady or Kinematic Wave routing, all conduits must have positive
slopes. This can usually be corrected by reversing the inlet and outlet nodes of
277
278
Error Messages
the conduit (i.e., right click on the conduit and select Reverse from the popup
menu). Adverse slopes are permitted under Dynamic Wave routing.
ERROR 117: no cross section defined for Link xxx.
Cross section geometry was never defined for the specified link.
ERROR 119: invalid cross section for Link xxx.
Either an invalid shape or invalid set of dimensions was specified for a link's
cross section.
ERROR 121: missing or invalid pump curve assigned to Pump xxx.
Either no pump curve or an invalid type of curve was specified for a pump.
ERROR 131: the following links form cyclic loops in the drainage system.
The Steady and Kinematic Wave flow routing methods cannot be applied to systems where a cyclic loop exists (i.e., a directed path along a set of links that
begins and ends at the same node). Most often the cyclic nature of the loop can
be eliminated by reversing the direction of one of its links (i.e., switching the
inlet and outlet nodes of the link). The names of the links that form the loop will
be listed following this message.
ERROR 133: Node xxx has more than one outlet link.
Under Steady and Kinematic Wave flow routing, a junction node can have only
a single outlet link.
ERROR 134: Node xxx has more than one DUMMY outlet link.
Only a single conduit with a DUMMY cross-section can be directed out of a
node.
ERROR 135: Divider xxx does not have two outlet links.
Flow divider nodes must have two outlet links connected to them.
ERROR 136: Divider xxx has invalid diversion link.
The link specified as being the one carrying the diverted flow from a flow divider node was defined with a different inlet node.
ERROR 137: Weir Divider xxx has invalid parameters.
The parameters of a Weir-type divider node either are non-positive numbers or
are inconsistent (i.e., the value of the discharge coefficient times the weir height
raised to the 3/2 power must be greater than the minimum flow parameter).
ERROR 138: Node xxx has initial depth greater than maximum depth.
Self-explanatory.
Error Messages
279
ERROR 139: Regulator xxx is the outlet of a non-storage node.
Under Steady or Kinematic Wave flow routing, orifices, weirs, and outlet links
can only be used as outflow links from storage nodes.
ERROR 141: Outfall xxx has more than 1 inlet link or an outlet link.
An outfall node is only permitted to have one link attached to it.
ERROR 143: Regulator xxx has invalid cross-section shape.
An orifice must have either a CIRCULAR or RECT_CLOSED shape, while a
weir must have a RECT_OPEN, TRAPEZOIDAL or TRIANGULAR shape.
ERROR 145: Drainage system has no acceptable outlet nodes.
Under Dynamic Wave flow routing, there must be at least one node designated
as an outfall.
ERROR 151: a Unit Hydrograph in set xxx has invalid time base.
The time base of a Unit Hydrograph cannot be negative and if positive, must not
be less than the recording interval for its rain gage
ERROR 153: a Unit Hydrograph in set xxx has invalid response ratios.
The response ratios for a set of Unit Hydrographs (the short-, medium-, and
long-term response hydrographs) must be between 0 and 1.0 and cannot add up
to a value greater than 1.0
ERROR 155: invalid sewer area for RDII at Node xxx.
The sewer area contributing RDII inflow to a node cannot be a negative number.
ERROR 156:
inconsistent data file name for Rain Gage xxx.
If two Rain Gages use files for their data sources and have the same Station IDs
then they must also use the same data files.
ERROR 157: inconsistent rainfall format for Rain Gage xxx.
If two or more rain gages use the same Time Series for their rainfall data then
they must all use the same data format (intensity, volume, or cumulative volume).
ERROR 158: time series for Rain Gage xxx is also used by another object.
A rainfall Time Series associated with a Rain Gage cannot be used by another
object that is not also a Rain Gage.
ERROR 159: inconsistent time interval for Rain Gage xxx.
The recording time interval specified for the rain gage is greater than the smallest time interval between values in the Time Series used by the gage.
280
Error Messages
ERROR 161: cyclic dependency in treatment functions at Node xxx.
An example would be where the removal of pollutant 1 is defined as a function
of the removal of pollutant 2 while the removal of pollutant 2 is defined as a
function of the removal of pollutant 1.
ERROR 171: Curve xxx has its data out of sequence.
The X-values of a curve object must be entered in increasing order.
ERROR 173: Time Series xxx has its data out of sequence.
The time (or date/time) values of a time series must be entered in sequential order.
ERROR 181: invalid Snow Melt Climatology parameters.
The ATI Weight or Negative Melt Ratio parameters are not between 0 and 1 or
the site latitude is not between -60 and +60 degrees.
ERROR 182: invalid parameters for Snow Pack xxx.
A snow pack’s minimum melt coefficient is greater than its maximum coefficient; the fractions of free water capacity or impervious plowable area are not
between 0 and 1; or the snow removal fractions sum to more than 1.0.
ERROR 183: no type specified for LID xxx.
A named LID control has layers defined for it but its LID type was never specified.
ERROR 184: missing layer for LID xxx.
A required design layer is missing for the specified LID control.
ERROR 185: invalid parameter value for LID xxx.
An invalid value was supplied for an LID control's design parameter.
ERROR 187: LID area exceeds total area for Subcatchment xxx.
The area of the LID controls placed within the subcatchment is greater than that
of the subcatchment itself.
ERROR 191: simulation start date comes after ending date.
Self-explanatory.
ERROR 193: report start date comes after ending date.
Self-explanatory.
ERROR 195: reporting time step is less than routing time step.
Self-explanatory.
Error Messages
281
ERROR 200: one or more errors in input file.
This message appears when one or more input file parsing errors (the 200-series
errors) occur.
ERROR 201: too many characters in input line.
A line in the input file cannot exceed 1024 characters.
ERROR 203: too few items at line n of input file.
Not enough data items were supplied on a line of the input file.
ERROR 205: invalid keyword at line n of input file.
An unrecognized keyword was found when parsing a line of the input file.
ERROR 207: duplicate ID name at line n of input file.
An ID name used for an object was already assigned to an object of the same
category.
ERROR 209: undefined object xxx at line n of input file.
A reference was made to an object that was never defined. An example would
be if node 123 were designated as the outlet point of a subcatchment, yet no
such node was ever defined in the study area.
ERROR 211: invalid number xxx at line n of input file.
Either a non-numeric character was encountered where a numerical value was
expected or an invalid number (e.g., a negative value) was supplied.
ERROR 213: invalid date/time xxx at line n of input file.
An invalid format for a date or time was encountered. Dates must be entered as
month/day/year and times as either decimal hours or as hour:minute:second.
ERROR 217: control rule clause out of sequence at line n of input file.
Errors of this nature can occur when the format for writing control rules is not
followed correctly (see Section 7.3).
ERROR 219: data provided for unidentified transect at line n of input file.
A GR line with Station-Elevation data was encountered in the [TRANSECTS]
section of the input file after an NC line but before any X1 line that contains the
transect’s ID name.
ERROR 221: transect station out of sequence at line n of input file.
The station distances specified for the transect of an irregular cross section must
be in increasing numerical order starting from the left bank.
282
Error Messages
ERROR 223: Transect xxx has too few stations.
A transect for an irregular cross section must have at least 2 stations defined.
ERROR 225: Transect xxx has too many stations.
A transect cannot have more than 1500 stations defined for it.
ERROR 227: Transect xxx has no Manning's N.
No Manning’s N was specified for a transect (i.e., there was no NC line in the
[TRANSECTS] section of the input file.
ERROR 229: Transect xxx has invalid overbank locations.
The distance values specified for either the left or right overbank locations of a
transect do not match any of the distances listed for the transect's stations.
ERROR 231: Transect xxx has no depth.
All of the stations for a transect were assigned the same elevation.
ERROR 233: invalid treatment function expression at line n of input file.
A treatment function supplied for a pollutant at a specific node is either not a
correctly formed mathematical expression or refers to unknown pollutants, process variables, or math functions.
ERROR 301: files share same names.
The input, report, and binary output files specified on the command line cannot
have the same names.
ERROR 303: cannot open input file.
The input file either does not exist or cannot be opened (e.g., it might be in use
by another program).
ERROR 305: cannot open report file.
The report file cannot be opened (e.g., it might reside in a directory to which the
user does not have write privileges).
ERROR 307: cannot open binary results file.
The binary output file cannot be opened (e.g., it might reside in a directory to
which the user does not have write privileges).
ERROR 309: error writing to binary results file.
There was an error in trying to write results to the binary output file (e.g., the
disk might be full or the file size exceeds the limit imposed by the operating system).
Error Messages
283
ERROR 311: error reading from binary results file.
The command line version of SWMM could not read results saved to the binary
output file when writing results to the report file.
ERROR 313: cannot open scratch rainfall interface file.
SWMM could not open the temporary file it uses to collate data together from
external rainfall files.
ERROR 315: cannot open rainfall interface file xxx.
SWMM could not open the specified rainfall interface file, possibly because it
does not exist or because the user does not have write privileges to its directory.
ERROR 317: cannot open rainfall data file xxx.
An external rainfall data file could not be opened, most likely because it does
not exist.
ERROR 319: invalid format for rainfall interface file.
SWMM was trying to read data from a designated rainfall interface file with the
wrong format (i.e., it may have been created for some other project or actually
be some other type of file).
ERROR 321: no data in rainfall interface file for gage xxx.
This message occurs when a project wants to use a previously saved rainfall interface file, but cannot find any data for one of its rain gages in the interface file.
It can also occur if the gage uses data from a user-prepared rainfall file and the
station id entered for the gage cannot be found in the file.
ERROR 323: cannot open runoff interface file xxx.
A runoff interface file could not be opened, possibly because it does not exist or
because the user does not have write privileges to its directory.
ERROR 325: incompatible data found in runoff interface file.
SWMM was trying to read data from a designated runoff interface file with the
wrong format (i.e., it may have been created for some other project or actually
be some other type of file).
ERROR 327: attempting to read beyond end of runoff interface file.
This can occur when a previously saved runoff interface file is being used in a
simulation with a longer duration than the one that created the interface file.
ERROR 329: error in reading from runoff interface file.
A format error was encountered while trying to read data from a previously
saved runoff interface file.
284
Error Messages
ERROR 331: cannot open hotstart interface file xxx.
A hotstart interface file could not be opened, possibly because it does not exist
or because the user does not have write privileges to its directory.
ERROR 333: incompatible data found in hotstart interface file.
SWMM was trying to read data from a designated hotstart interface file with the
wrong format (i.e., it may have been created for some other project or actually
be some other type of file).
ERROR 335: error in reading from hotstart interface file.
A format error was encountered while trying to read data from a previously
saved hotstart interface file.
ERROR 336: no climate file specified for evaporation and/or wind speed.
This error occurs when the user specifies that evaporation or wind speed data
will be read from an external climate file, but no name is supplied for the file.
ERROR 337: cannot open climate file xxx.
An external climate data file could not be opened, most likely because it does
not exist.
ERROR 338: error in reading from climate file xxx.
SWMM was trying to read data from an external climate file with the wrong
format.
ERROR 339: attempt to read beyond end of climate file xxx.
The specified external climate does not include data for the period of time being
simulated.
ERROR 341: cannot open scratch RDII interface file.
SWMM could not open the temporary file it uses to store RDII flow data.
ERROR 343: cannot open RDII interface file xxx.
An RDII interface file could not be opened, possibly because it does not exist or
because the user does not have write privileges to its directory.
ERROR 345: invalid format for RDII interface file.
SWMM was trying to read data from a designated RDII interface file with the
wrong format (i.e., it may have been created for some other project or actually
be some other type of file).
ERROR 351: cannot open routing interface file xxx.
A routing interface file could not be opened, possibly because it does not exist
or because the user does not have write privileges to its directory.
Error Messages
285
ERROR 353: invalid format for routing interface file xxx.
SWMM was trying to read data from a designated routing interface file with the
wrong format (i.e., it may have been created for some other project or actually
be some other type of file).
ERROR 355: mismatched names in routing interface file xxx.
The names of pollutants found in a designated routing interface file do not
match the names used in the current project.
ERROR 357: inflows and outflows interface files have same name.
In cases where a run uses one routing interface file to provide inflows for a set
of locations and another to save outflow results, the two files cannot both have
the same name
ERROR 361: could not open external file used for Time Series xxx.
The external file used to provide data for the named time series could not be
opened, most likely because it does not exist.
ERROR 363: invalid data in external file used for used for Time Series xxx.
The external file used to provide data for the named time series has one or more
lines with the wrong format.
WARNING 01: wet weather time step reduced to recording interval for Rain
Gage xxx.
The wet weather time step was automatically reduced so that no period with
rainfall would be skipped during a simulation.
WARNING 02: maximum depth increased for Node xxx.
The maximum depth for the node was automatically increased to match the top
of the highest connecting conduit.
WARNING 03: negative offset ignored for Link xxx.
The link’s stipulated offset was below the connecting node's invert so its actual
offset was set to 0.
WARNING 04: minimum elevation drop used for Conduit xxx.
The elevation drop between the end nodes of the conduit was below 0.001 ft
(0.000 35 m) so the latter value was used instead to calculate its slope.
WARNING 05: minimum slope used for Conduit xxx.
The conduit's computed slope was below the user-specified Minimum Conduit
Slope so the latter value was used instead.
286
Error Messages
WARNING 06: dry weather time step increased to wet weather time step.
The user-specified time step for computing runoff during dry weather periods
was lower than that set for wet weather periods and was automatically increased
to the wet weather value.
WARNING 07: routing time step reduced to wet weather time step.
The user-specified time step for flow routing was larger than the wet weather
runoff time step and was automatically reduced to the runoff time step to prevent loss of accuracy.
WARNING 08: elevation drop exceeds length for Conduit xxx.
The elevation drop across the ends of a conduit exceeds its length. The program
computes the conduit's slope as the elevation drop divided by the length instead
of using the more accurate right triangle method. The user should check for errors in the length and in both the invert elevations and offsets at the conduit's
upstream and downstream nodes.
WARNING 09: time series interval greater than recording interval for Rain
Gage xxx.
The smallest time interval between entries in the precipitation time series used
by the rain gage is greater than the recording time interval specified for the gage.
If this was not actually intended then what appear to be continuous periods of
rainfall in the time series will instead be read with time gaps in between them.
Chapter 19
Dynamic Wave Routing Quality Assurance
This chapter constitutes a reformatted and rearranged version of the original
report Stormwater Quality Assurance Report: Dynamic Wave Flow Routing,
EPA/600/R-06/097. The original report can be downloaded from the USEPA
website: www.epa.gov/ednnrmrl/swmm.
19.1 Introduction
The Storm Water Management Model (SWMM) was originally developed in
1971 as a computer-based tool for simulating storm water runoff quantity and
quality from primarily urban areas (Metcalf & Eddy, Inc., et al., 1971). Since
then it has undergone several major updates, the last of these being Version 4.4
(Huber and Dickinson, 1992) which is available through an Oregon State University web site (http://ccee.oregonstate.edu/swmm/). Throughout each of these
updates the general block nature of the overall program as well as the basic
structure of its Fortran source code has remained more or less intact.
In 2002, the United States Environmental Protection Agency’s Water Supply
and Water Resources Division partnered with the consulting firm CDM to develop a completely re-written version of SWMM. The goal of this project was to
apply modern software engineering techniques to produce a more maintainable,
extensible, and easier to use model. The result of this effort, SWMM 5
(Rossman, 2005), consists of a platform-independent computational engine written in C as well as a graphical user interface for the Microsoft Windows
operating system written in Delphi. A rigorous Quality Assurance (QA) program
was developed to ensure that the numerical results produced from the new
SWMM 5 model would be compatible with those obtained from SWMM 4.4
(Schade, 2002). The new SWMM 5 software was released to the public in October of 2004.
The most numerically challenging sub-model to implement within SWMM 5
was the dynamic wave flow routing routine known as Extran (for Extended
Transport). It routes non-steady flows through a general network of open channels, closed conduits, storage facilities, pumps, orifices and weirs. In contrast to
simpler routing methods, this procedure can model such phenomena as backwater effects, flow reversals, pressurized flow, and entrance/exit energy losses.
Rather than simply encode a line-for-line copy of Extran, SWMM 5 restructured
287
288
Dynamic Wave Routing Quality Assurance
the code in a more readable and maintainable fashion. It also employed a slightly modified computational scheme with the intent of producing more
numerically stable solutions in less time.
The following sections of this chapter document the Quality Assurance testing program that was used to compare the dynamic wave flow routing
procedures of SWMM 4.4 and SWMM 5 with one another. The SWMM 5 and
SWMM 4 implementations of the dynamic wave flow routing procedure are
contrasted in Chapter 5, section 5.4.5.
19.2 Testing Procedure
The testing procedure used for this study involved running both SWMM 4 and 5
on an identical set of dynamic wave flow routing test problems and then comparing the results. Equivalent sets of analysis options, such as routing time step
and minimum nodal surface area, were used with each program to maintain
comparability (see below). The results produced by each program were inspected in the following ways:
• For examples that included a runoff calculation, the overall flow
balances for runoff were compared to make sure that both versions
of SWMM produced the same total inflow quantities to the flow
routing computation.
• The flow balance error for the routing portion of each example was
checked to insure that both versions of SWMM maintained acceptable flow continuity.
• Scatter plots were used to visually compare the peak flows computed for all conduits in each example by each of the programs.
• Time series plots of flows and water depths at critical locations in
each example were visually compared, paying particular attention to
any evidence of numerical instability exhibited by either program.
The critical locations chosen for time series plots typically included system
outfalls, other significant system elements (such as orifices, weirs, storage units
and pump stations), and locations that exhibited significant differences in peak
flows between the two programs.
The test case examples used in this evaluation were divided into three distinct categories. The first category is the Extran Manual Test Cases. These
consist of the ten Extran example data sets that were presented in the last
SWMM 4.4 Users Manual (Roesner et al., 1992) and included in the SWMM
Users Guide (James et al, 2005). They serve as a useful benchmark to compare
against and model such elements as surcharged conduit flow, bottom and side
orifices, weirs, storage units, pumps, and a variety of cross-sectional shapes.
The second test case category is the Challenge Test Cases. These are five examples from a suite of test cases compiled by Robert E. Dickinson of CDM.
They all consist of several circular conduits connected in series that present dif-
Dynamic Wave Routing Quality Assurance
289
ferent types of challenges to modeling dynamic flows, such as flat slopes, pipe
constrictions, steep drops, adverse slopes, and inlet offsets.
The third test category is the User Submitted Test Cases. These contain five
real-world data sets contributed by SWMM users. They include models of either
storm sewer systems, combined sewer systems or natural channel systems and
range in size from 59 conduits up to 273 conduits. Each of these user examples
includes a runoff component that generates the flows supplied to the routing
component of the model.
All twenty test data sets used in this study are available in electronic format
at the EPA SWMM web site www.epa.gov/ednnrmrl/swmm. Each includes:
• The SWMM 4 Extran input file and, for the user-supplied test cases ,
the corresponding SWMM 4 Runoff input file.
• The equivalent SWMM 5 input file.
• Calibration files that contain the SWMM 4 time series results for
node depth and conduit flow that were used to generate the comparison plots in this report.
The SWMM 4 input data files have a “.dat” extension (e.g. extran1.dat)
while the SWMM 5 ones have a “.inp” extension (e.g. extran1.inp). The calibration files are named “xxxx_y.dat” for node depth results or “xxxx_q.dat” for link
flow results, where xxxx is the name of the test case.
The versions of SWMM used in this comparison study were SWMM 4.4h
(July 4, 2005) and SWMM 5.0.006 (September 2005). Unless otherwise indicated, the option settings listed in Table 19-1 were used in all runs to maintain
computational compatibility between the two versions of SWMM. Note that the
SWMM 4 ITMAX and SURTOL settings are not directly comparable to the
SWMM 5 settings for maximum iterations and convergence tolerance since the
former apply only to surcharge iterations while the latter are used throughout
SWMM 5’s successive approximation routine.
Table 19-1 Computational Settings Used for the Test Case Comparisons.
SWMM 4
SWMM 5
Meaning
Value
Setting
Solution method
0
Inertial terms
Normal flow limit criteri0
Normal flow limit criterion
on
NEQUAL Lengthen short conduits
0
Lengthen short conduits
AMEN
Minimum surface area, ft2 12.57 Minimum surface area, ft2
ITMAX
Maximum iterations
30
Maximum iterations (fixed internally)
(for surcharge only)
SURTOL Surcharge tolerance,
0.05 Convergence tolerance, expressed as an
expressed as a fractional
absolute head difference in feet (fixed
flow difference
internally)
Setting
ISOL
KSUPER
Value
Keep
Slope
No
12.57
4
0.005
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Dynamic Wave Routing Quality Assurance
19.3 SWMM 4 Routing Models
As mentioned in Chapter 5, section 5.4.5, SWMM 4.4 offers the user three different options for solving its dynamic wave flow routing model. The Explicit
Method is compared to the SWMM 5 approach in that section, and discussed in
detail in Chapter 21, sections 21.9 through 21.13. The Enhanced Explicit Method is identical to the Explicit Method except that it uses an alternate way to
express the inertial terms of the momentum equation in finite difference form.
The resulting flow updating equation that is used in place of equation 5.4 (see
Chapter 5, section 5.4.5) is:
Qt +Δt =
Qt + ΔQgravity
′ tial
1 + ΔQ friction + ΔQlosses − ΔQiner
(19.1)
where
′
ΔQinertial
= 2(A − At ) A + (Qt At )( A2 − A1 ) A (Δt L ) (19.2)
and the other terms have the same definitions as before.
The third solution method, called the Iterative Method, also uses the above
form of the flow updating formula. However, it replaces the Modified Euler integration method with a successive approximation method that is similar in
nature to SWMM 5’s method. It also replaces the surcharge algorithm with a
“Preissmann Slot” approach. This is a narrow wedge of additional flow area
added to the top of a closed conduit once it pressurizes. In addition, it employs a
variable routing time step that is adjusted during the simulation to try to satisfy
the Courant stability criterion as the simulation unfolds. One must consult the
SWMM 4.4 Fortran code itself to unravel all of the details of the Iterative Method as the description of it in the SWMM Extran Manual (Roesner, et al., 1992)
is somewhat out of date.
For the Quality Assurance testing of SWMM 5 against SWMM 4 it was decided that the Explicit Method would be used in all of the SWMM 4 runs. This
decision was based on a preliminary comparison of the three SWMM 4 solution
methods on a subset of the same test data sets that would be used in the full testing. This comparison revealed the following results:
1. The Enhanced Explicit method appeared to offer no consistent advantage over the Explicit method in the test cases studied. In most
cases it produced identical results. In at least one case (TEST5 described in section 19.4 Extran Manual Test Cases), it produced a
clearly incorrect solution (see Figure 19-1 below) with a continuity
error of -397 percent when compared with both the SWMM 4 Explicit method as well as SWMM 5. It also did not produce more
291
Dynamic Wave Routing Quality Assurance
stable solutions than the Explicit method when both were run at
higher routing time steps.
2. The Iterative method failed to perform acceptably in a consistent
fashion. In a number of examples, its flow solution was either clearly
different or markedly inferior to that of the Explicit method, including:
• Example EXTRAN1 (the simple 2-branch network described in
section 19.4). As seen in Figure 19-2, the Iterative method produced a flow hydrograph in surcharged pipe 1602 whose shape
is considerably different than both the SWMM 4 Explicit method and the SWMM 5 solution.
• Example TEST4 (the inverted siphon example described in
section 19.5). The Iterative method produced a solution that
was much more unstable than that produced by the Explicit
method (see Figure 19-3).
• Example USER1 (the 59 conduit storm sewer system described
in section 19.6). The flow continuity error produced by the Iterative method was -3150 percent compared with only 0.19
percent for the Explicit method.
• Example USER2 (the 83 conduit drainage system described in
section 19.6). The Iterative method took 8.75 minutes to execute and produced a flow continuity error of -317 percent
compared to 0.5 minutes and 0.4 percent, respectively, with the
Explicit method.
Explicit
Enhanced Explicit
4
6
200
180
160
Flow (cfs)
140
120
100
80
60
40
20
0
0
2
8
10
Time (hours)
Figure 19-1 Comparison of the SWMM 4 Explicit and Enhanced Explicit
Methods for the Outfall Flow in Example TEST5.
12
292
Dynamic Wave Routing Quality Assurance
Explicit Method
Iterative Method
SWMM 5
80
70
Flow (cfs)
60
50
40
30
20
10
0
0
1
2
3
4
5
6
7
8
Time (hours)
Figure 19-2 Comparison of the SWMM 4 Explicit and Iterative Methods and
SWMM 5 Results for Conduit 1602 of Example EXTRAN1.
Explicit Method
Iterative Method
200
Flow (cfs)
150
100
50
0
-50
-100
Time (hours)
Figure 19-3 Comparison of the SWMM 4 Explicit and Iterative Methods for
Conduit 6 of Example TEST4.
9
293
Dynamic Wave Routing Quality Assurance
19.4 Extran Manual Test Cases
Example EXTRAN1
The drainage network used in this example is displayed in Figure 19-4. It contains 7 circular conduits arranged in 2 branches that converge into a pair of
trapezoidal channels with a free outfall. Three locations as shown in the figure
are subjected to the inflow hydrographs shown in Figure 19-5. The system was
designed so that conduits 8040, 8060, and 1602 along the top branch become
surcharged and flooding occurs at node 80608. It was analyzed using a 20 second time step over an 8 hour simulation period.
SWMM 4 and 5 produced essentially identical results for this example.
Comparison plots for flow in selected conduits and water depth at selected nodes
are shown in Figures 19-6 through 19-9. The maximum flow at each conduit and
the maximum water elevation at each node are compared in Figures 19-10 and
19-11, respectively.
16109
1602
82309
8060
80608
8040
Inflow
80408
Inflow
1600
10208
1030
10309
1630
16009
1570
15009
8130
81309
8100
81009
Inflow
EXAMPLE 1 OF EXTRAN MANUAL
Figure 19-4 Schematic of the Drainage Network Used for Example
EXTRAN1.
294
Dynamic Wave Routing Quality Assurance
Link 8040
Link 1602
Link 8100
60
50
Inflow (cfs)
40
30
20
10
0
0
1
2
3
4
Time (hours)
Figure 19-5 External Inflows for Example EXTRAN1.
Link 1602 Flow
SWMM5
SWMM4
80.0
70.0
60.0
Flow (CFS)
50.0
40.0
30.0
20.0
10.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
Figure 19-6 Flow Comparison for Link 1602 of Example EXTRAN1.
8
9
295
Dynamic Wave Routing Quality Assurance
Link 1030 Flow
SWMM5
SWMM4
140.0
120.0
Flow (CFS)
100.0
80.0
60.0
40.0
20.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
9
8
9
Figure 19-7 Flow Comparison for Link 1030 of Example EXTRAN1.
Node 82309 Depth
SWMM5
SWMM4
25.0
20.0
Depth (ft)
15.0
10.0
5.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
Figure 19-8 Water Depth Comparison for Node 82309 of Example
EXTRAN1.
296
Dynamic Wave Routing Quality Assurance
Node 16009 Depth
SWMM5
SWMM4
3.0
2.5
1.5
1.0
0.5
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
9
Figure 19-9 Water Depth Comparison for Node 16009 of Example
EXTRAN1.
140
120
100
SWMM 5
Depth (ft)
2.0
80
60
40
20
0
0
20
40
60
80
100
120
SWMM 4
Figure 19-10 Comparison of Peak Flows (cfs) Computed for the Conduits
in Example EXTRAN1.
140
297
Dynamic Wave Routing Quality Assurance
160
150
140
SWMM 5
130
120
110
100
90
80
80
90
100
110
120
130
140
150
160
SWMM 4
Figure 19-11 Comparison of Maximum Water Elevations (ft) for the Nodes
of Example EXTRAN1.
Example EXTRAN2
This example is identical to EXTRAN1 except that the free outfall at node
10208 is replaced with a fixed-elevation outfall that includes a tide gate. Again,
the agreement between SWMM 4 and 5 is very good as shown in Figures 19-12
through 19-15.
Link 1030 Flow
SWMM5
SWMM4
140.0
120.0
Flow (CFS)
100.0
80.0
60.0
40.0
20.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
Figure 19-12 Flow Comparison for Link 1030 of Example EXTRAN2.
9
298
Dynamic Wave Routing Quality Assurance
Node 16009 Depth
SWMM5
SWMM4
3.5
3.0
Depth (ft)
2.5
2.0
1.5
1.0
0.5
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
9
Figure 19-13 Water Depth Comparison for Node 16009 of Example
EXTRAN2.
140
120
SWMM 5
100
80
60
40
20
0
0
20
40
60
80
100
120
SWMM 4
Figure 19-14 Comparison of Peak Flows (cfs) for the Conduits of Example
EXTRAN2.
140
299
Dynamic Wave Routing Quality Assurance
160
150
SWMM 5
140
130
120
110
100
90
80
80
90
100
110
120
130
140
150
160
SWMM 4
Figure 19-15 Comparison of Maximum Water Elevations (ft) for the Nodes
of Example EXTRAN2.
Example EXTRAN3
This example is also identical to EXTRAN1 except that a bottom circular orifice
is placed between nodes 82309 and 15009 to eliminate upstream flooding. The
modified network is shown in Figure 19-16, where the orifice has been labeled
90010.
Figure 19-17 compares the flow computed by SWMM 4 and SWMM 5
through the orifice while Figure 19-18 compares the depth of water above the
orifice at its inlet node. Although the flow through the orifice is the same between the two programs, there is clearly a difference in the depth of water above
the orifice opening. This can be attributed to the different ways in which each
program models an orifice. SWMM 4 uses an equivalent pipe while SWMM 5
uses the classical orifice equation directly. However this difference does not
appear to affect downstream conditions as evidenced by the comparison of flow
in conduit 1570 shown in Figure 19-19 and the depth at node 15009 shown in
Figure 19-20.
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Dynamic Wave Routing Quality Assurance
16109
1602
Inflow
82309
8060
80608
8040
Inflow
80408
8100
81009
1600
10208
90010
1030
10309
1630
16009
1570
15009
8130
81309
Inflow
EXAMPLE 3 OF EXTRAN MANUAL
Figure 19-16 Schematic of the Drainage Network Used for Example
EXTRAN3.
Link 90010 Flow
SWMM5
SWMM4
40.0
35.0
30.0
Flow (CFS)
25.0
20.0
15.0
10.0
5.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
Figure 19-17 Comparison of Flow Through the Bottom Orifice of Example
EXTRAN3.
9
301
Dynamic Wave Routing Quality Assurance
Node 82309 Depth
SWMM5
SWMM4
9.0
8.0
7.0
Depth (ft)
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
9
Figure 19-18 Comparison of Water Depth at the Inlet Node of the Orifice in
Example EXTRAN3.
Link 1570 Flow
SWMM5
SWMM4
90.0
80.0
70.0
Flow (CFS)
60.0
50.0
40.0
30.0
20.0
10.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
Figure 19-19 Flow Comparison for Link 1570 of Example EXTRAN3.
8
9
302
Dynamic Wave Routing Quality Assurance
Node 15009 Depth
SWMM5
SWMM4
4.0
3.5
3.0
2.0
1.5
1.0
0.5
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
9
Figure 19-20 Water Depth Comparison for Node 15009 of Example
EXTRAN3.
140
130
120
SWMM4
Depth (ft)
2.5
110
100
90
80
80
90
100
110
120
130
SWMM5
Figure 19-21 Comparison of Peak Flows (cfs) for the Conduits of Example
EXTRAN3.
140
303
Dynamic Wave Routing Quality Assurance
160
140
SWMM4
120
100
80
60
40
20
0
0
20
40
60
80
100
120
140
160
SWMM5
Figure 19-22 Comparison of Maximum Water Elevations (ft) for the Nodes
of Example EXTRAN3.
Example EXTRAN4
This example is identical to EXTRAN3, except that the bottom orifice 90010 is
replaced by a transverse weir. The weir opening is 3-ft high by 3-ft long and its
crest is 3-ft above the invert of Node 82309. Figure 19-23 compares the flow
through the weir computed by SWMM 4 and SWMM 5 while Figure 19-24
compares the water depths at the weir’s upstream node. The two programs produce nearly identical results. This was true as well for the remaining elements in
the network. Figure 19-25 compares the maximum flow in all conduits and Figure 19-26 compares the maximum water elevations at all nodes.
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Dynamic Wave Routing Quality Assurance
Link 90010 Flow
SWMM5
SWMM4
25.0
Flow (CFS)
20.0
15.0
10.0
5.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
9
Figure 19-23 Comparison of Flow Through the Transverse Weir of Example EXTRAN4.
Node 82309 Depth
SWMM5
SWMM4
16.0
14.0
12.0
Depth (ft)
10.0
8.0
6.0
4.0
2.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
Figure 19-24 Comparison of Water Depth at the Inlet Node of the Weir in
Example EXTRAN4.
9
305
Dynamic Wave Routing Quality Assurance
140
SWMM5
120
100
80
60
40
40
60
80
100
120
140
SWMM4
Figure 19-25 Comparison of Peak Flows (cfs) for the Conduits of Example
EXTRAN4.
140
130
SWMM5
120
110
100
90
80
80
90
100
110
120
130
140
SWMM4
Figure 19-26 Comparison of Maximum Water Elevations (ft) for the Nodes
of Example EXTRAN4.
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Dynamic Wave Routing Quality Assurance
Example EXTRAN5
Example EXTRAN5 modifies EXTRAN1 by replacing the node downstream of
the node that floods with a storage unit that has a side outlet orifice. The modified schematic is shown in Figure 19-27. Node 82309 was converted into a 40.5
ft. high storage unit with a constant 800 sq. ft. of surface area. A new node,
82308, was added to connect the outlet orifice to the original conduit 1602.
16109 1602
82308 90010
82309
8060
80608
8040
Inflow
80408
Inflow
1600
10208
1030
10309
1630
16009
1570
15009
8130
81309
8100
81009
Inflow
EXAMPLE 5 OF EXTRAN MANUAL
Figure 19-27 Schematic of the Drainage Network Used for Example
EXTRAN5.
Figure 19-28 compares the orifice flows computed by both SWMM 4 and
SWMM 5. With the exception of a few points in time, there is good agreement
between the two programs even though the orifice is modeled differently by
each. Figure 19-29 compares flows in conduit 1602 immediately downstream of
the orifice. Whatever differences in flow that existed through the orifice have
been essentially eliminated leaving almost perfect agreement between SWMM 4
and 5.
A comparison of the water depth at the storage unit node 82309 is shown in
Figure 19-30. Depth comparisons for the nodes both immediately upstream and
downstream of the storage node are shown in Figures 19-31 and 19-32, respectively. There is good agreement at all time points. Good agreement is also
obtained for the peak flows and water elevations in all conduits and nodes as
shown in Figures 19-33 and 19-34, respectively.
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Dynamic Wave Routing Quality Assurance
Link 90010 Flow
SWMM 5
SWMM 4
70.0
60.0
50.0
Flow (CFS)
40.0
30.0
20.0
10.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
9
Figure 19-28 Comparison of Flow Through the Outlet Orifice of Example
EXTRAN5.
Link 1602 Flow
SWMM 5
SWMM 4
70.0
60.0
Flow (CFS)
50.0
40.0
30.0
20.0
10.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
Figure 19-29 Comparison of Flow Through the Conduit Immediately Downstream of the Outlet Orifice of Example EXTRAN5.
9
308
Dynamic Wave Routing Quality Assurance
Node 82309 Depth
SWMM 5
SWMM 4
25.0
20.0
Depth (ft)
15.0
10.0
5.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
9
Figure 19-30 Comparison of Water Depth at the Storage Node in Example
EXTRAN5.
Node 80608 Depth
SWMM 5
SWMM 4
18.0
16.0
14.0
Depth (ft)
12.0
10.0
8.0
6.0
4.0
2.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
Figure 19-31 Comparison of Water Depth at the Node Immediately Upstream of the Storage Node in Example EXTRAN5.
8
9
309
Dynamic Wave Routing Quality Assurance
Node 82308 Depth
SWMM 5
SWMM 4
16.0
14.0
12.0
8.0
6.0
4.0
2.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
9
Figure 19-32 Comparison of Water Depth at the Node Immediately Downstream of the Storage Node in Example EXTRAN5.
120
100
SWMM5
Depth (ft)
10.0
80
60
40
40
60
80
100
SWMM4
Figure 19-33 Comparison of Peak Flows (cfs) for the Conduits of Example
EXTRAN5.
120
310
Dynamic Wave Routing Quality Assurance
140
130
SWMM5
120
110
100
90
80
80
90
100
110
120
130
140
SWMM4
Figure 19-34 Comparison of Maximum Water Elevations (ft) for the Nodes
of Example EXTRAN5.
Example EXTRAN6
Example EXTRAN6 modifies EXTRAN1 by adding an off-line pumping station
with wet well between nodes 82309 and 15009. The new wet well node, 82310,
is connected to node 82309 by a new conduit 8061 which is 300 feet of 4-foot
diameter pipe. The pump, link 90011, is represented by a Type 1 pump curve
which describes pumping rate as a function of wet well volume. The highest
point on this curve is 20 cfs at 1200 cubic feet. The latter number implicitly sets
the maximum volume of the wet well node 82310. The resulting schematic of
this network is displayed in Figure 19-35.
As shown in Figure 19-36, the flow through the pump computed by SWMM
4 and SWMM 5 is essentially the same. However, there is a significant difference in the way that the two programs handle the flow into the wet well coming
from conduit 8061. SWMM 4 internally restricts the flow coming into the wet
well so that the wet well does not flood. SWMM 5 allows the system to behave
as designed, and allows the wet well to flood if more volume flows in than can
be pumped. The resulting differences in the two programs are illustrated in Figures 19-37 and 19-38 which compares flow in conduit 8061, conduit 1602, and
the flooding at the wet well node 82310. Figure 19-39 compares the flow in the
outlet channel 1030 of this system. The mass balance report for SWMM 5 shows
that the reduction in flow volume leaving the system as compared to SWMM 4
exactly equals the volume of flooding experienced at the pump’s wet well.
311
Dynamic Wave Routing Quality Assurance
Inflow
Inflow
1602
8060
8040
8130
8100
8061
1600
1030
90011
1630
1570
Inflow
EXAMPLE 6 OF EXTRAN MANUAL
Figure 19-35 Schematic of the Drainage Network Used for Example
EXTRAN6.
Link 90011 Flow
SWMM5
SWMM4
20.0
Flow (CFS)
16.0
12.0
8.0
4.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
Figure 19-36 Comparison of Flow Through the Pump of Example
EXTRAN6.
8
9
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Dynamic Wave Routing Quality Assurance
Link 8061
Link 1602
70
Flow (CFS)
60
50
40
30
20
10
0
0
2
4
6
8
10
Elapsed Time (hours)
Figure 19-37 SWMM 4 Flows Leaving Node 82309 for Example EXTRAN6.
Link 8061
Link 1602
Wet Well Flooding
70
Flow (CFS)
60
50
40
30
20
10
0
0
2
4
6
8
Elapsed Time (hours)
Figure 19-38 SWMM 5 Flows Leaving Node 82309 for Example EXTRAN6.
10
313
Dynamic Wave Routing Quality Assurance
Link 1030 Flow
SWMM 5
SWMM 4
140.0
120.0
Flow (CFS)
100.0
80.0
60.0
40.0
20.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
Figure 19-39 Comparison of Outfall Flows for Example EXTRAN6.
Example EXTRAN7
This example replaces the off-line pump used in example EXTRAN6 with an inline Type 2 pump directly connecting nodes 82309 and 15009 as shown in Figure 19-40. The operating curve for this pump, which relates pumping rate to
water depth, is super-imposed on the figure.
Figure 19-41 compares the flow through the pump computed by both
SWMM 4 and 5. Figure 19-42 does the same for the water depth at the pump’s
inlet node. SWMM 4 appears to have some flow instability at the pump when
the inlet water depth falls to zero, while SWMM 5 produces a much smoother
response. (Both programs limit the pumping rate to the inflow flow rate if the
pump curve rate would cause the node to be pumped dry.) The overall higher
pumping volume produced by SWMM 4 probably contributes to its larger continuity error (-6.87 percent) as compared to that of SWMM 5 (0.24 percent).
9
314
Dynamic Wave Routing Quality Assurance
Inflow
16109
1602
82309
Inflow
8060
80608
8040
1600
10208
80408
Flow in Pump 90010
20
90010
18
16
14
1030
12
10
8
6
10309
1630
16009
1570
15009
8130
81309
0
20
8100
40
60
81009
80
100
Depth (ft)
Inflow
EXAMPLE 7 OF EXTRAN MANUAL
Figure 19-40 Schematic of the Drainage Network Used for Example
EXTRAN7.
Link 90010 Flow
SWMM5
SWMM4
12.0
10.0
Flow (CFS)
8.0
6.0
4.0
2.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
9
Figure 19-41 Comparison of Flow Through the Pump of Example
EXTRAN7.
Looking downstream of the pump, the water depths at the pump outlet node
15009 are compared in Figure 19-43. SWMM 4 maintains a higher water depth
at this node than does SWMM 5 after the inflow hydrograph has passed through
due to the cycling of the pump. There is also an anomalously high depth at the
start of the simulation with SWMM 4 which is difficult to explain. Even with
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Dynamic Wave Routing Quality Assurance
these discrepancies, the final outfall flows through channel 1030 for the two
programs are very close as shown in Figure 19-44. Also, the peak flows and
maximum water elevations are essentially identical as shown in Figures 19-45
and 19-46, respectively.
Node 82309 Depth
SWMM5
SWMM4
25.0
20.0
Depth (ft)
15.0
10.0
5.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
9
Figure 19-42 Comparison of Water Depth at the Inlet Node of the Pump in
Example EXTRAN7.
Node 15009 Depth
SWMM5
SWMM4
3.0
2.5
Depth (ft)
2.0
1.5
1.0
0.5
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
Figure 19-43 Comparison of Water Depth at the Outlet Node of the Pump
in Example EXTRAN7.
9
316
Dynamic Wave Routing Quality Assurance
Link 1030 Flow
SWMM 5
SWMM 4
140.0
120.0
80.0
60.0
40.0
20.0
0.0
0
1
2
3
4
5
Elapsed Time (hours)
6
7
8
9
Figure 19-44 Comparison of Outfall Flows for Example EXTRAN7.
140
120
SWMM5
Flow (CFS)
100.0
100
80
60
40
40
60
80
100
120
SWMM4
Figure 19-45 Comparison of Peak Flows (cfs) for the Conduits of Example
EXTRAN7.
140
317
Dynamic Wave Routing Quality Assurance
140
130
SWMM5
120
110
100
90
80
80
90
100
110
120
130
140
SWMM4
Figure 19-46 Comparison of Maximum Water Elevations (ft) for the Nodes
of Example EXTRAN7.
Example EXTRAN8
The schematic for example EXTRAN8 is shown in Figure 19-47. This example
utilizes various cross-sectional shapes for its conduits as listed in Table 19-1.
The geometries of the two irregular-shaped channels, 10081 and 10082, are depicted in Figure 19-48.
Table 19-2 Cross-Sectional Shapes Used in Example EXTRAN8.
Conduit
10001
10002
10003
10004
10005
10006
10007
10081
10082
Shape
Circular
Rectangular
Horseshoe
Egg
Baskethandle
Trapezoidal
Parabolic
Irregular
Irregular
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Dynamic Wave Routing Quality Assurance
Figure 19-47 Schematic of the Drainage Network Used for Example
EXTRAN8.
The inflows at nodes 30001, 30004, and 30007 are all triangular hydrographs
with a base time of 1 hour and peak flow of 15 cfs, 18 cfs, and 9 cfs, respectively. The inflow at node 30081 is a constant 20 cfs. The water surface elevation at
the outfall node 30083 is a fixed value. Following the protocol used in the
SWMM 4 Extran Manual, this example was first run for a 1-hour duration with
just the constant 20 cfs inflow to create a hot start file with the two natural channels 10081 and 10082 flowing at 20 cfs. Then the system was run using this hot
start file and the three inflow hydrographs for a period of 2 hours. The results at
selected locations are depicted in Figures 19-49 to 19-54 and show perfect
agreement between the two programs.
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Dynamic Wave Routing Quality Assurance
Figure 19-48 Geometry of Channels 10081 and 10082 in Example
EXTRAN8.
Link 10003 Flow
SWMM5
SWMM4
14.0
12.0
Flow (CFS)
10.0
8.0
6.0
4.0
2.0
0.0
0
0.4
0.8
1.2
Elapsed Time (hours)
1.6
Figure 19-49 Flow Comparison for Link 10003 of Example EXTRAN8.
2
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Dynamic Wave Routing Quality Assurance
Link 10006 Flow
SWMM5
SWMM4
40.0
35.0
30.0
Flow (CFS)
25.0
20.0
15.0
10.0
5.0
0.0
0
0.4
0.8
1.2
Elapsed Time (hours)
1.6
2
Figure 19-50 Flow Comparison for Link 10006 of Example EXTRAN8.
Link 10082 Flow
SWMM5
SWMM4
50.0
45.0
Flow (CFS)
40.0
35.0
30.0
25.0
20.0
15.0
0
0.4
0.8
1.2
Elapsed Time (hours)
1.6
Figure 19-51 Flow Comparison for Outfall Link 10082 of Example
EXTRAN8.
2
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Dynamic Wave Routing Quality Assurance
Node 30006 Depth
SWMM5
SWMM4
1.2
0.8
0.6
0.4
0.2
0.0
0
0.4
0.8
1.2
Elapsed Time (hours)
1.6
2
Figure 19-52 Water Depth Comparison for Node 30006 of Example
EXTRAN8.
60
50
40
SWMM5
Depth (ft)
1.0
30
20
10
0
0
10
20
30
40
50
SWMM4
Figure 19-53 Comparison of Peak Flows (cfs) for the Conduits of Example
EXTRAN8.
60
322
Dynamic Wave Routing Quality Assurance
810
808
806
SWMM5
804
802
800
798
796
794
792
790
790
792
794
796
798
800
802
804
806
808
810
SWMM4
Figure 19-54 Comparison of Maximum Water Elevations (ft) for the Nodes
of Example EXTRAN8.
Example EXTRAN9
This example illustrates hydrograph routing through a variable-area storage unit
with a side outlet orifice discharging to a free outfall. A schematic of the system
is shown in Figure 19-55. The inflow hydrograph is triangular with a 5 hour
time base and peak flow of 1.2 m3/s. The storage unit is shaped as shown in Figure 19-56. Comparisons of SWMM 4 and SWMM 5 results for depth in the
storage unit and outflow through the orifice are shown in Figures 19-57 and 1958, respectively. The results from the two programs are essentially the same.
Figure 19-55 Schematic of Example EXTRAN9
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Dynamic Wave Routing Quality Assurance
Depth (m)
Storage Curve Curve1
10
9
8
7
6
5
4
3
2
1
0
Figure 19-56 Storage Unit Shape for Example EXTRAN9.
Node 30001 Depth
SWMM5
SWMM4
7.0
6.0
Depth (m)
5.0
4.0
3.0
2.0
1.0
0.0
0
2
4
6
Elapsed Time (hours)
8
Figure 19-57 Water Depth Comparison for the Storage Unit of Example
EXTRAN9.
10
324
Dynamic Wave Routing Quality Assurance
Link 90001 Flow
SWMM5
SWMM4
0.5
Flow (CMS)
0.4
0.3
0.2
0.1
0.0
0
2
4
6
Elapsed Time (hours)
8
10
Figure 19-58 Flow Comparison for the Side Orifice of Example EXTRAN9.
Example EXTRAN10
This example illustrates a 5-pump pumping station that moves water up a 50foot hill from one storage unit to another. The schematic is shown in Figure
19-59. Each pump is a Type 3 pump that all share the same operating curve as
shown in Figure 19-60. However each pump has a different operating range as
shown in Table 19-3. These ranges are entered directly on the H1 lines of the
SWMM 4 input data file and are converted into a set of Control Rules for the
SWMM 5 input. As an example, the operating condition for pump 9002 can be
expressed through the following set of control rules in SWMM 5:
Figure 19-59 Schematic of Example EXTRAN10.
325
Dynamic Wave Routing Quality Assurance
Flow
(CFS)
10
0
9
0
8
0
7
0
6
0
5
0
4
0
3
0
2
0
1
0
5
0
5
2
5
4
5
6
5
8
6
0
Head
(ft)
6
2
6
4
6
6
6
8
7
0
Figure 19-60 Operating Curve for Pumps of Example EXTRAN 10
Table 19-3 Operating Ranges for the Pumps of Example EXTRAN10
(Pump turns on when clear well depth exceeds high level and shuts down
when depth reaches low level.)
Pump
90002
90003
90004
90005
90006
Low Level (feet)
2
3
4
5
6
High Level (feet)
6
7
8
9
10
RULE 90002A
IF NODE 401 DEPTH >= 6
AND PUMP 90002 STATUS = OFF
THEN PUMP 90002 STATUS = ON
RULE 90002B
IF NODE 401 DEPTH <= 2
AND PUMP 90002 STATUS = ON
THEN PUMP 90002 STATUS = OFF
The upstream storage unit 401 is subjected to an external inflow that ramps
up from 0 to 100 cfs over a period of an hour after which it remains constant at
326
Dynamic Wave Routing Quality Assurance
this rate. The system was solved using a 1 minute time step over a total duration
of 5 hours.
Figures 19.61 and 19.62 compare water depths in the two storage units computed by both SWMM 4 and SWMM 5. Figure 19.63 compares the outflow rate
from the system through conduit 100. These figures show almost perfect agreement between SWMM 4 and 5. As for the 5 pumps, 90002, 90005, and 90006
also show almost perfect agreement. As an example, the flow for 90002 is
shown in Figure 19.64. There are some differences in flow for Pumps 90003 and
90004 at 40 minutes into the simulation, as shown in Figure 19.65 for pump
90004. Table 19.4 compares the pump flows at 40 minutes for the two programs.
For the three pumps that are on, 90002, 90003, and 90004, SWMM 5 produces
the same flow rate which should be the case since each pump has the same operating curve and end nodes. SWMM 4, however, produces slightly different flow
rates, suggesting that something is not quite right with how its computing pump
flows.
Table 19-4 Pumping Rates for Example EXTRAN10 at Elapsed Time of 40
Minutes
Pump
90002
90003
90004
90005
90006
SWMM 5 Flow (cfs)
25.7
25.7
25.7
0
0
SWMM 4 Flow (cfs)
23.0
22.5
21.0
0
0
Node 401 Depth
SWMM5
SWMM4
12.0
Depth (ft)
10.0
8.0
6.0
4.0
2.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-61 Water Depth Comparison for the Storage Unit 401 of Example EXTRAN10.
327
Dynamic Wave Routing Quality Assurance
Node 301 Depth
SWMM5
SWMM4
30.0
25.0
Depth (ft)
20.0
15.0
10.0
5.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-62 Water Depth Comparison for the Storage Unit 301 of Example EXTRAN10.
Link 100 Flow
SWMM5
SWMM4
120.0
100.0
Flow (CFS)
80.0
60.0
40.0
20.0
0.0
0
1
2
3
Elapsed Time (hours)
4
Figure 19-63 Flow Comparison for Outflow Conduit 100 of Example
EXTRAN10.
5
328
Dynamic Wave Routing Quality Assurance
Link 90002 Flow
SWMM5
SWMM4
45.0
40.0
Flow (CFS)
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-64 Flow Comparison for Pump 90002 of Example EXTRAN10.
Link 90004 Flow
SWMM5
SWMM4
30.0
25.0
Flow (CFS)
20.0
15.0
10.0
5.0
0.0
0
1
2
3
Elapsed Time (hours)
4
Figure 19-65 Flow Comparison for Pump 90004 of Example EXTRAN10.
5
329
Dynamic Wave Routing Quality Assurance
19.5 Challenge Test Cases
Example TEST1
The first challenge example compares the two programs in modeling a flat run
of pipe. The profile of the pipe layout is displayed in Figure 19.66. It consists of
ten, 100-foot lengths of 4-foot diameter circular pipe placed on a flat (0%) slope.
The system was subjected to a 3-hour square wave inflow hydrograph of 100 cfs
magnitude at the upstream end and was run for a 5 hour simulation period using
a 5 second routing time step (larger time steps caused instability in both programs).
Figure 19.67a-d compares flows produced by SWMM 4 and 5 in selected
conduits while Figure 19.68a-d does the same for depth at selected nodes. Overall there is a very good agreement between the two programs, with SWMM 5
providing a slightly more stable solution for depth than SWMM 4.
21
0
1
2
3
4
5
6
7
8
9
20
19
18
Elevation (ft)
17
16
15
10
14
13
12
11
10
9
0
100
200
300
400
500
Distance (ft)
600
700
800
900
1,000
02/02/2002 00:04:30
Figure 19-66 Profile View of Example TEST1.
330
Dynamic Wave Routing Quality Assurance
Flow Between Nodes 0 and 1
SWMM5
SWMM4
120.0
100.0
Flow (CFS)
80.0
60.0
40.0
20.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-67a Flow Comparisons for Selected Conduits for Example
TEST1
Flow Between Nodes 3 and 4
SWMM5
SWMM4
120.0
100.0
Flow (CFS)
80.0
60.0
40.0
20.0
0.0
0
1
2
3
Elapsed Time (hours)
4
Figure 19-67b Flow Comparisons for Selected Conduits for Example
TEST1
5
331
Dynamic Wave Routing Quality Assurance
Flow Between Nodes 6 and 7
SWMM5
SWMM4
120.0
100.0
60.0
40.0
20.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-67c Flow Comparisons for Selected Conduits for Example
TEST1
Flow Between Nodes 9 and 10
SWMM5
SWMM4
120.0
100.0
80.0
Flow (CFS)
Flow (CFS)
80.0
60.0
40.0
20.0
0.0
0
1
2
3
Elapsed Time (hours)
4
Figure 19-67d Flow Comparisons for Selected Conduits for Example
TEST1
5
332
Dynamic Wave Routing Quality Assurance
Node 1 Depth
SWMM5
SWMM4
9.0
8.0
7.0
Depth (ft)
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-68a Depth Comparisons for Selected Nodes for Example TEST1
Node 3 Depth
SWMM5
SWMM4
8.0
7.0
6.0
Depth (ft)
5.0
4.0
3.0
2.0
1.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-68b Depth Comparisons for Selected Nodes for Example TEST1
333
Dynamic Wave Routing Quality Assurance
Node 7 Depth
SWMM5
SWMM4
5.0
4.5
4.0
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-68c Depth Comparisons for Selected Nodes for Example TEST1
Node 9 Depth
SWMM5
SWMM4
4.0
3.5
3.0
2.5
Depth (ft)
Depth (ft)
3.5
2.0
1.5
1.0
0.5
0.0
0
1
2
3
Elapsed Time (hours)
4
Figure 19-68d Depth Comparisons for Selected Nodes for Example
TEST1
5
334
Dynamic Wave Routing Quality Assurance
Example TEST2
The next challenge test example models a pipe constriction that is subjected to
surcharging. The profile of the system is shown in Figure 19.69. It consists of
alternating sections of 12-foot diameter circular pipe flowing into a 3-foot diameter pipe. Each section is 1000 feet long and has a slope of 0.05%. The inflow
hydrograph to the system is a 50 cfs, 3-hour square wave pattern as is shown in
Figure 19.70. The system was run for a 6-hour duration using a 5 second routing
time step.
245 1
240
2
3
235
230
225
4
Elevation (ft)
220
215
210
205
200
195
5
190
6
185
180
175
170
0
500
1,000
1,500
2,000
2,500
Distance (ft)
3,000
3,500
4,000
4,500
5,000
01/01/1988 01:55:30
Figure 19-69 Profile View of Example TEST2.
Node 1 Lateral Inflow
60.0
50.0
Lateral Inflow (CFS)
40.0
30.0
20.0
10.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
Figure 19-70 Inflow Hydrograph for Example TEST2.
6
7
335
Dynamic Wave Routing Quality Assurance
Comparisons of flow for various links are displayed in Figure 19.71a-d while
those for water depths in various nodes are given in Figure 19.72. Note how
much the constriction influences the shape of the inflow hydrograph as it moves
downstream. SWMM 4 has the upstream pipe segments reaching a surcharged
state about 10 minutes faster than does SWMM 5 and shows a slightly higher
degree of flow oscillation in the large 12-foot pipe between nodes 3 and 4. The
flow continuity error for both programs was 0.4%.
Flow Between Nodes 1 and 2
SWMM5
SWMM4
60.0
50.0
Flow (CFS)
40.0
30.0
20.0
10.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-71a Comparisons of Flow in Selected Conduits of Example
TEST2
Flow Between Nodes 2 and 3
SWMM5
SWMM4
60.0
50.0
Flow (CFS)
40.0
30.0
20.0
10.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-71b Comparisons of Flow in Selected Conduits of Example
TEST2
7
336
Dynamic Wave Routing Quality Assurance
Flow Between Nodes 3 and 4
SWMM5
SWMM4
50.0
45.0
40.0
Flow (CFS)
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-71c Comparisons of Flow in Selected Conduits of Example
TEST2
Flow Between Nodes 4 and 5
SWMM5
SWMM4
45.0
40.0
35.0
Flow (CFS)
30.0
25.0
20.0
15.0
10.0
5.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-71d Comparisons of Flow in Selected Conduits of Example
TEST2
7
337
Dynamic Wave Routing Quality Assurance
Depth for Node 1
SWMM5
SWMM4
25.0
20.0
Depth (ft)
15.0
10.0
5.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
5
6
7
Depth for Node 3
SWMM5
SWMM4
12.0
10.0
Depth (ft)
8.0
6.0
4.0
2.0
0.0
0
1
2
3
4
Elapsed Time (hours)
Depth for Node 5
SWMM5
SWMM4
3.0
2.5
Depth (ft)
2.0
1.5
1.0
0.5
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-72 Water Depth Comparisons for Selected Nodes of Example
TEST2
7
338
Dynamic Wave Routing Quality Assurance
Example TEST3
This example consists of six sections of 6-foot diameter circular pipe that drop
40 ft to connect with another six sections of 3-ft diameter pipe. Each section is
500 ft long with a slope of 0.10%. The profile for this example is shown in Figure 19-73 and the inflow hydrograph in Figure 19-74. Both SWMM 4 and 5
were run at a 5 second routing time step over a 6 hour simulation period.
190 1
2
4
3
6
5
180
170
160
Elevation (ft)
150
7
140
130
9
8
120
11
10
12
110
100
90
13
80
70
0
500
1,000
1,500
2,000
2,500
3,000
3,500
Distance (ft)
4,000
4,500
5,000
5,500
6,000
01/01/1988 00:47:00
Figure 19-73 Profile View of Example TEST3.
110
100
90
80
70
60
50
40
30
20
10
0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-74 Inflow Hydrograph (cfs) for Example TEST3.
7
339
Dynamic Wave Routing Quality Assurance
Flow Between Nodes 2 and 3
SWMM5
SWMM4
120.0
100.0
Flow (CFS)
80.0
60.0
40.0
20.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-75a Comparisons of Flow in Selected Conduits of Example
TEST3.
Flow Between Nodes 6 and 7
SWMM5
SWMM4
140.0
120.0
Flow (CFS)
100.0
80.0
60.0
40.0
20.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-75b Comparisons of Flow in Selected Conduits of Example
TEST3.
7
340
Dynamic Wave Routing Quality Assurance
Flow Between Nodes 7 and 8
SWMM5
SWMM4
120.0
100.0
60.0
40.0
20.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-75c Comparisons of Flow in Selected Conduits of Example
TEST3.
Flow to Outfall
SWMM5
SWMM4
90.0
80.0
70.0
60.0
Flow (CFS)
Flow (CFS)
80.0
50.0
40.0
30.0
20.0
10.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
Figure 19-75d Comparisons of Flow in Selected Conduits of Example
TEST3.
6
7
341
Dynamic Wave Routing Quality Assurance
Depth at Node 2
SWMM5
SWMM4
20.0
18.0
16.0
14.0
Depth (ft)
12.0
10.0
8.0
6.0
4.0
2.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-76a Water Depth Comparisons for Selected Nodes of Example
TEST3
Depth at Node 7
SWMM5
SWMM4
50.0
45.0
40.0
35.0
Depth (ft)
30.0
25.0
20.0
15.0
10.0
5.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-76b Water Depth Comparisons for Selected Nodes of Example
TEST3
7
342
Dynamic Wave Routing Quality Assurance
Depth at Node 8
SWMM5
SWMM4
40.0
35.0
30.0
Depth (ft)
25.0
20.0
15.0
10.0
5.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-76c Water Depth Comparisons for Selected Nodes of Example
TEST3
Depth at Node 12
SWMM5
SWMM4
10.0
9.0
8.0
7.0
Depth (ft)
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-76d Water Depth Comparisons for Selected Nodes of Example
TEST3
7
343
Dynamic Wave Routing Quality Assurance
Figure 19-75a-d shows flow comparisons between SWMM 4 and 5 at selected conduits while Figure 19-76a-d does the same for node water depth. Overall,
the shapes of the hydrographs and the depth profiles look similar. SWWM 4
exhibits some instabilities for short periods of time, particularly around the drop
location, that are not present with SWMM 5. Figure 19-77 illustrates what happens at the outfall when the routing time step is increased from 5 to 30 seconds.
SWMM 5 is still able to produce a stable solution while SWMM 4 becomes
highly unstable. The system flow continuity errors at this larger time step were
0.02 percent for SWMM 5 and 34.4 percent for SWMM 4.
Outfall Flow
SWMM 5
SWMM 4
90.0
80.0
70.0
Flow (CFS)
60.0
50.0
40.0
30.0
20.0
10.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-77 Outfall Flow Comparison for Example TEST3 at a 30 Second
Time Step.
Example TEST4
Example TEST4 is an inverted siphon. The profile is shown in Figure 19-78. All
conduits are 100-foot lengths of 4-foot diameter circular pipe. The inflow hydrograph, shown in Figure 19-79, is a 3-hour square wave of 100 cfs magnitude.
SWMM 4 and 5 were run using a 5 second time step for a period of 5 hours.
Elevation (ft)
344
Dynamic Wave Routing Quality Assurance
95 0
90
85
80
75
70
65
60
55
50
45
40
35
30
25
20
15
10
5
0
1
2
3
4
5
6
7
8
9
10
100
200
300
400
500
Distance (ft)
600
700
800
900
1,000
02/22/2002 02:00:00
Figure 19-78 Profile View of Example TEST4.
100
90
80
70
60
50
40
30
20
10
0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-79 Inflow Hydrograph (cfs) for Example TEST4.
Comparisons of flows in selected conduits are shown in Figure 19-80 while
those for depths at selected nodes are shown in Figure 19-81. There is very good
agreement between the two programs.
7
345
Dynamic Wave Routing Quality Assurance
Flow Between Nodes 1 and 2
SWMM5
SWMM4
120.0
100.0
Flow (CFS)
80.0
60.0
40.0
20.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-80a Comparisons of Flow in Selected Conduits of Example
TEST4
Flow Bewteen Nodes 3 and 4
SWMM5
SWMM4
120.0
100.0
Flow (CFS)
80.0
60.0
40.0
20.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-80b Comparisons of Flow in Selected Conduits of Example
TEST4
346
Dynamic Wave Routing Quality Assurance
Flow Between Nodes 5 and 6
SWMM5
SWMM4
120.0
100.0
60.0
40.0
20.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-80c Comparisons of Flow in Selected Conduits of Example
TEST4
Flow at Outfall
SWMM5
SWMM4
120.0
100.0
80.0
Flow (CFS)
Flow (CFS)
80.0
60.0
40.0
20.0
0.0
0
1
2
3
Elapsed Time (hours)
4
Figure 19-80d Comparisons of Flow in Selected Conduits of Example
TEST4
5
347
Dynamic Wave Routing Quality Assurance
Depth at Node 1
SWMM5
SWMM4
7.0
6.0
Depth (ft)
5.0
4.0
3.0
2.0
1.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-81a Water Depth Comparisons for Selected Nodes of Example
TEST4
Depth at Node 4
SWMM5
SWMM4
80.0
70.0
60.0
Depth (ft)
50.0
40.0
30.0
20.0
10.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-81b Water Depth Comparisons for Selected Nodes of Example
TEST4
348
Dynamic Wave Routing Quality Assurance
Depth at Node 7
SWMM5
SWMM4
5.0
4.5
4.0
3.5
2.5
2.0
1.5
1.0
0.5
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-81c Water Depth Comparisons for Selected Nodes of Example
TEST4
Depth at Node 9
SWMM5
SWMM4
4.0
3.5
3.0
2.5
Depth (ft)
Depth (ft)
3.0
2.0
1.5
1.0
0.5
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-81d Water Depth Comparisons for Selected Nodes of Example
TEST4
349
Dynamic Wave Routing Quality Assurance
Figure 19-82 illustrates what happens at the outfall when the routing time
step is increased to 10 seconds. The solution produced by SWMM 4 becomes
highly unstable at this time step while SWMM 5 still produces reasonable results.
Outfall Flow
SWMM 5
SWMM 4
300.0
250.0
Flow (CFS)
200.0
150.0
100.0
50.0
0.0
0
1
2
3
Elapsed Time (hours)
4
5
Figure 19-82 Outfall Flow Comparison for Example TEST4 at a 10 Second
Time Step.
Example TEST5
The final challenge test example is a sequence of conduits each of which has a
3-foot offset from the invert of its inlet node. Each conduit is a 100-foot length
of 4-foot diameter circular pipe at a 3% slope. The profile of this layout is
shown in Figure 19-83. The inflow hydrograph applied at the upstream end of
this system is shown in Figure 19-84. SWMM 4 and 5 were run using a 5 second
time step for a period of 12 hours.
350
Dynamic Wave Routing Quality Assurance
21
0
1
2
3
4
5
6
7
8
9
20
19
18
17
Elevation (ft)
16
15
10
14
13
12
11
10
9
0
100
200
300
400
500
Distance (ft)
600
700
800
900
1,000
02/22/2002 00:21:00
Figure 19-83 Profile View of Example TEST5.
40
35
30
25
20
15
10
5
0
0
1
2
3
4
5
6
7
Elapsed Time (hours)
8
9
10
11
12
Figure 19-84 Inflow Hydrograph (cfs) for Example TEST5.
Figure 19-85a-d shows flow comparisons between SWMM 4 and 5 at selected conduits while Figure 19-86a-d does the same for node water depth. The
results are seen to be identical between the two programs. When the routing time
step is increased to 10 seconds, the SWMM 5 solution remains the same while
SWMM 4 becomes highly unstable. Figure 19-87 illustrates this result by comparing outfall flows between the two programs run at the higher time step. The
system flow continuity error for SWMM 4 was greater than 800 percent compared with only 0.05 percent for SWMM 5.
351
Dynamic Wave Routing Quality Assurance
Flow Between Nodes 1 and 2
SWMM 5
SWMM 4
45.0
40.0
35.0
Flow (CFS)
30.0
25.0
20.0
15.0
10.0
5.0
0.0
0
2
4
6
8
Elapsed Time (hours)
10
12
14
Figure 19-85a Comparisons of Flow in Selected Conduits of Example
TEST5
Flow Between Nodes 3 and 4
SWMM5
SWMM4
45.0
40.0
35.0
Flow (CFS)
30.0
25.0
20.0
15.0
10.0
5.0
0.0
0
2
4
6
8
Elapsed Time (hours)
10
12
Figure 19-85b Comparisons of Flow in Selected Conduits of Example
TEST5
14
352
Dynamic Wave Routing Quality Assurance
Flow Between Nodes 6 and 7
SWMM 5
SWMM 4
45.0
40.0
35.0
25.0
20.0
15.0
10.0
5.0
0.0
0
2
4
6
8
Elapsed Time (hours)
10
12
14
Figure 19-85c Comparisons of Flow in Selected Conduits of Example
TEST5
Flow at Outfall
SWMM5
SWMM4
45.0
40.0
35.0
30.0
Flow (CFS)
Flow (CFS)
30.0
25.0
20.0
15.0
10.0
5.0
0.0
0
2
4
6
8
Elapsed Time (hours)
10
12
Figure 19-85d Comparisons of Flow in Selected Conduits of Example
TEST5.
14
353
Dynamic Wave Routing Quality Assurance
Node 2 Depth
SWMM5
SWMM4
4.5
4.0
3.5
Depth (ft)
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
2
4
6
8
Elapsed Time (hours)
10
12
14
Figure 19-86a Water Depth Comparisons for Selected Nodes of Example
TEST5
Node 5 Depth
SWMM 5
SWMM 4
4.5
4.0
3.5
Depth (ft)
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
2
4
6
8
Elapsed Time (hours)
10
12
Figure 19-86b Water Depth Comparisons for Selected Nodes of Example
TEST5
14
354
Dynamic Wave Routing Quality Assurance
Node 9 Depth
SWMM 5
SWMM 4
5.0
4.5
4.0
Depth (ft)
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
2
4
6
8
Elapsed Time (hours)
10
12
14
Figure 19-86c Water Depth Comparisons for Selected Nodes of Example TEST5.
Flow at Outfall
SWMM 5
SWMM 4
100.0
Flow (CFS)
80.0
60.0
40.0
20.0
0.0
0
2
4
6
8
Elapsed Time (hours)
10
12
Figure 19-87 Outfall Flow Comparison for Example TEST5 at a 10 Second
Time Step.
14
Dynamic Wave Routing Quality Assurance
355
19.6 User-Supplied Test Cases
Example USER1
Example USER1 consists of a 175 hectare drainage area divided into 58 subcatchments. As shown in Figure 19-88, the conveyance system contains 59
circular conduits connected to 59 junctions and a single outfall. The elevation
profile of the main stem drops almost 19 meters over a distance of 2.5 km (see
Figure 19-89). The storm event used for the simulation is depicted in Figure 1990. The system was solved using a 5 second flow routing time step for a 7 hour
duration with a 1 minute reporting time step.
05y32
Outfall
13
05y36
23
05y41
05y44
64
Figure 19-88 Schematic of the Drainage Network for Example USER1.
356
Dynamic Wave Routing Quality Assurance
Main Stem Elevation Profile
22
20
18
16
14
Elevation (m)
12
10
8
6
4
2
0
-2
2,500
2,000
1,500
Distance (m)
1,000
500
0
10/01/2003 00:01:00
Figure 19-89 Elevation Profile of the Main Stem of the Drainage Network
for Example USER1.
70.0
60.0
Rainfall (mm/hr)
50.0
40.0
30.0
20.0
10.0
0.0
0
0.2
0.4
0.6
0.8
1
1.2
Elapsed Time (hours)
1.4
1.6
1.8
2
Figure 19-90 Rainfall Hyetograph for the Design Storm Used for Example
USER
Table 19-5 compares the runoff computation made by both SWMM 5 and
SWMM 4 for this example. SWMM 5 produces slightly more runoff than does
SWMM 4 and has a smaller continuity error. Figure 19-91 compares the peak
flows estimated by both SWMM 5 and SWMM 4 for all conduits in this exam-
357
Dynamic Wave Routing Quality Assurance
ple. SWMM 4 tends to produce slightly higher peaks than SWMM 5 but the average difference is only 2.2%. Comparisons for flows at selected locations are
displayed in Figure 19-92a-d. These locations include the outfall and conduits
13, 23, and 64 which are all identified on the system schematic in Figure 19-88.
The plots show an almost perfect match between SWMM 4 and 5. Comparisons
were also made of water depths at nodes 05y32, 05y36, 05y41, and 05y44
whose locations are also identified in the schematic of Figure 19-88. These results are shown in Figure 19-93a-d. The SWMM 5 depths match those of
SWMM 4 very well except for the peak time at node 05y44. The peak SWMM 4
depth here is about a meter higher than that of SWMM 5. However, it appears
that this might be a result of some numerical instability in the SWMM 4 solution
and not a true difference.
Table 19-5 System-Wide Runoff Results for Example USER1.
SWMM 5
26.448
0.000
7.257
19.189
0.097
-0.358
Precipitation (mm)
Evaporation (mm)
Infiltration (mm)
Runoff (mm)
Final Storage (mm)
Continuity Error (%)
SWMM 4
26.360
0.000
7.243
18.461
0.121
2.028
14
12
SWMM 4
10
8
6
4
2
0
0
2
4
6
8
10
12
SWMM 5
Figure 19-91 Comparison of Peak Flows (cms) for All Conduits in Example
USER1
14
358
Dynamic Wave Routing Quality Assurance
Outfall Flow
SWMM 5
SWMM 4
14.0
12.0
Flow (CMS)
10.0
8.0
6.0
4.0
2.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-92a Comparison of Flows at Select Locations for Example
USER1.
Link 13 Flow
SWMM 5
SWMM 4
9.0
8.0
7.0
Flow (CMS)
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-92b Comparison of Flows at Select Locations for Example
USER1.
7
359
Dynamic Wave Routing Quality Assurance
Link 23 Flow
SWMM 5
SWMM 4
6.0
5.0
Flow (CMS)
4.0
3.0
2.0
1.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-92c Comparison of Flows at Select Locations for Example
USER1.
Link 64 Flow
SWMM 5
SWMM 4
Flow (CMS)
0.4
0.2
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-92d Comparison of Flows at Select Locations for Example USER1.
7
360
Dynamic Wave Routing Quality Assurance
Node 05y32 Depth
SWMM 5
SWMM 4
1.6
1.4
1.2
Depth (m)
1.0
0.8
0.6
0.4
0.2
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-93a Comparison of Water Depths at Select Locations for Example USER1
Node 05y36 Depth
SWMM 5
SWMM 4
3.5
3.0
Depth (m)
2.5
2.0
1.5
1.0
0.5
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-93b Comparison of Water Depths at Select Locations for Example USER1
(See also Figures 19-93c and d overleaf).
7
361
Dynamic Wave Routing Quality Assurance
Node 05y41 Depth
SWMM 5
SWMM 4
3.5
3.0
Depth (m)
2.5
2.0
1.5
1.0
0.5
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-93c Comparison of Water Depths at Select Locations for Example USER1
Node 05y44 Depth
SWMM 5
SWMM 4
4.0
3.5
3.0
Depth (m)
2.5
2.0
1.5
1.0
0.5
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-93d Comparison of Water Depths at Select Locations for Example USER1.
7
362
Dynamic Wave Routing Quality Assurance
Example USER2
This example models a 3.5 square mile drainage area broken into 17 subcatchments. The conveyance system, shown in Figure 19-94, contains 83 conduits
that are a mixture of irregular natural channels, open channels and closed pipes
of various shapes. There are 28 storage units along with 19 weirs. Many of these
storage units and weirs represent junctions with above-ground surface storage
coupled with road overflows. A typical arrangement is shown in Figure 19-95. A
4.4 inch, 24-hour design storm, depicted in Figure 19-96, was applied to the system over a 36-hour simulation period using a 5 second flow routing time step
and a 5 minute reporting time step.
TW01240
TW01250
TW01170
TW01140
TW01020
Outfall
Figure 19-94 Schematic of the Drainage Network for Example USER2.
363
Dynamic Wave Routing Quality Assurance
Height (ft)
14
Surface Storage
Area
12
10
8
Overflow Channel
Connects Here
6
4
2
0
Drainage System
Connects Here
Figure 19-95 Configuration of Surface Storage Units with Road Overflows
Used Throughout Example USER2.
5.0
4.5
4.0
Rainfall (in/hr)
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
5
10
15
20
25
Elapsed Time (hours)
Figure 19-96 Rainfall Hyetograph for the Design Storm Used for Example
USER2.
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Dynamic Wave Routing Quality Assurance
Table 19-6 compares the runoff computations between the two programs.
The results are almost identical. Figure 19-97 compares the peak flows computed by the two programs in the system’s conduits. The agreement is very good
with the average difference being less than 2 percent. Figure 19-98a-d compares
flows produced by the two programs at the four locations pictured in Figure 1998a-d. Figure 19-99 does the same for node water depths at these same locations. Finally, Figure 19-100 depicts the behavior of the two programs at one of
the surface storage – road overflow locations, TW01240.
Table 19-6 System-Wide Runoff Results for Example USER2
Precipitation (in)
Evaporation (in)
Infiltration (in)
Runoff (in)
Final Storage (in)
SWMM 5
4.391
0.014
1.161
3.125
0.091
SWMM 4
4.391
0.014
1.162
3.123
0.091
1000
1500
2000
SWMM 4
1500
1000
500
0
0
500
2000
SWMM 5
Figure 19-97 Comparison of Peak Flows (cfs) for the Conduits in Example
USER2.
365
Dynamic Wave Routing Quality Assurance
Flow in Link TW01350
SWMM 5
SWMM 4
50.0
45.0
40.0
Flow (CFS)
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
0
5
10
15
20
Elapsed Time (hours)
25
30
35
40
Figure 19-98a Flow Comparisons for Example USER2 at Selected Locations
Flow in Link TW01170
SWMM 5
SWMM 4
1200.0
1000.0
Flow (CFS)
800.0
600.0
400.0
200.0
0.0
0
5
10
15
20
Elapsed Time (hours)
25
30
35
Figure 19-98b Flow Comparisons for Example USER2 at Selected Locations
40
366
Dynamic Wave Routing Quality Assurance
Flow in Link TW01140
SWMM 5
SWMM 4
1400.0
1200.0
Flow (CFS)
1000.0
800.0
600.0
400.0
200.0
0.0
0
5
10
15
20
Elapsed Time (hours)
25
30
35
40
Figure 19-98c Flow Comparisons for Example USER2 at Selected Locations
Flow in Link TW01020
SWMM 5
SWMM 4
1600.0
1400.0
1200.0
Flow (CFS)
1000.0
800.0
600.0
400.0
200.0
0.0
0
5
10
15
20
Elapsed Time (hours)
25
30
35
Figure 19-98d Flow Comparisons for Example USER2 at Selected Locations
40
367
Dynamic Wave Routing Quality Assurance
Depth at Node TW01350
SWMM 5
SWMM 4
1.6
1.4
1.2
Depth (ft)
1.0
0.8
0.6
0.4
0.2
0.0
0
5
10
15
20
Elapsed Time (hours)
25
30
35
40
Figure 19-99a Depth Comparisons for Selected Nodes in Example USER2
Depth at Node TW01170
SWMM 5
SWMM 4
7.0
6.0
Depth (ft)
5.0
4.0
3.0
2.0
1.0
0.0
0
5
10
15
20
Elapsed Time (hours)
25
30
35
40
Figure 19-99b Depth Comparisons for Selected Nodes in Example USER2
368
Dynamic Wave Routing Quality Assurance
Depth at Node TW01140
SWMM 5
SWMM 4
8.0
7.0
6.0
Depth (ft)
5.0
4.0
3.0
2.0
1.0
0.0
0
5
10
15
20
Elapsed Time (hours)
25
30
35
40
Figure 19-99c Depth Comparisons for Selected Nodes in Example USER2
Depth at Node TW01020
SWMM 5
SWMM 4
4.0
3.5
3.0
Depth (ft)
2.5
2.0
1.5
1.0
0.5
0.0
0
5
10
15
20
Elapsed Time (hours)
25
30
35
Figure 19-99d Depth Comparisons for Selected Nodes in Example USER2
40
369
Dynamic Wave Routing Quality Assurance
Surface Storage
Node TW01240
Road Overflow
Channel TW01241
Drainage System
Pipe TW01240
Flow in Link TW01240
SWMM 5
SWMM 4
450.0
400.0
350.0
Flow (CFS)
300.0
250.0
200.0
150.0
100.0
50.0
0.0
0
5
10
15
20
Elapsed Time (hours)
25
30
35
40
Elevation (ft)
906
905
904
903
902
901
900
899
898
0
50
100
150
Station (ft)
200
250
300
Figure 19-100 Comparison of Surface Storage – Road Overflow Arrangement at Location TW01240
370
Dynamic Wave Routing Quality Assurance
Flow in Link TW01241
SWMM 5
SWMM 4
600.0
500.0
Flow (CFS)
400.0
300.0
200.0
100.0
0.0
0
5
10
15
20
Elapsed Time (hours)
25
30
35
40
Figure 19-100 cont'd Comparison of Surface Storage – Road Overflow
Arrangement at Location TW01240 (continued)
Example USER3
The USER3 data set is a combined sewer system containing 168 subcatchments
that encompasses an area of 6 square kilometers. The network schematic is
shown in Figure 19-101. The system contains 134 pipes which have mostly circular or egg-shaped cross sections. Of the 141 nodes in the network, 6 are
outfalls (see Figure 19-102 for a detail drawing) and 130 are manhole or catch
basin structures that are represented as small storage units (see Figure 19-103 for
a representative profile). There are 5 pumps in the model that discharge directly
to the system’s outfalls. The 3-hour, 42 mm design storm used in the simulation
is shown in Figure 19-104. This system was analyzed using a 0.5 second routing
step, a 1 minute reporting time step and a 6 hour total duration.
371
Dynamic Wave Routing Quality Assurance
CMCPLOG
SXANEL
G
CLIPNOT
CLIPSAR
CLIPSMT
CAUBPOR
Detail A
Detail B
Figure 19-101 Schematic of the Drainage Network for Example USER3
372
Dynamic Wave Routing Quality Assurance
Detail A
SAUBOUT
SCANOUT
CAUBOUT SRUBOUT
Detail B
CMRYCOR-I
CCOROUT
CMRYOUT
Figure 19-102 Detailed Schematics of the Outfalls for Example USER3.
Height (m)
6
5
4
3
2
1
0
Figure 19-103 Profile View of a Typical Manhole Structure in Example
USER3
373
Dynamic Wave Routing Quality Assurance
80.0
70.0
60.0
Rainfall (mm/hr)
50.0
40.0
30.0
20.0
10.0
0.0
0
0.5
1
1.5
2
Elapsed Time (hours)
2.5
3
3.5
4
Figure 19-104 Rainfall Hyetograph for the Design Storm Used for Example
USER3.
Table 19-7 shows the overall results of the runoff calculations. Both programs produce essentially the same amounts of runoff. Table 19-8 compares the
flow balances for the routing calculations and shows a reasonable match between the two programs. The peak flows in each conduit are compared in Figure
19-105. SWMM 4 is clearly producing higher peak flows in many of the conduits than is SWMM 5 in this example. Flow comparisons for the system’s
outfalls are shown in Figures 19-106a-c and 19-107. The general shapes of these
hydrographs are similar, but SWMM 4 tends to produce a higher peak flow.
Figure 19-108a-d compares flows in several of the pipes shown along the main
trunk line between locations CMCPLOG and CAUBPOR. The SWMM 4 results
shown in this figure suggest that numerical instabilities might be causing the
higher peaks flows as compared with SWMM 5.
One possible cause of SWMM 4’s stability problem might be the shape of
the manhole storage units used throughout the model. Figure 19-109 compares
the SWMM 4 and 5 flow results for conduit SXANELG using the original set of
storage nodes along its trunk line while Figure 19-110 does the same for a simulation where these nodes were converted into simple junctions. Note the reduced
amount of instability in the SWMM 4 solution and the closer match it gives to
the SWMM 5 hydrograph. Finally, Figure 19-111 gives evidence of how
SWMM 5 is able to maintain the stability of its solution even when the flow
routing time step is raised from 0.5 to 5 seconds.
374
Dynamic Wave Routing Quality Assurance
Table 19-7 System-Wide Water Balances for Runoff in Example USER3
(quantities in mms).
System Total
Precipitation (mm)
Evaporation (mm)
Infiltration (mm)
Surface Runoff (mm)
SWMM 5
42.20
0.54
17.89
23.06
SWMM 4
42.20
0.53
17.92
23.00
Table 19-8 System-Wide Water Balances for Flow Routing in Example
USER3 (all quantities are in thousands of cubic meters).
System Total
Initial Storage
Total Inflow
Total Outflow
Final Storage
SWMM 5
23.0
290.0
287.7
25.1
SWMM 4
23.1
289.6
285.7
24.9
25
SWMM 4
20
15
10
5
0
0
5
10
15
20
25
SWMM 5
Figure 19-105 Comparison of Peak Flows (cfs) for the Conduits in Example
USER3.
375
Dynamic Wave Routing Quality Assurance
Flow at SAUBOUT Outfall
SWMM 5
SWMM 4
20.0
16.0
Flow (CMS)
12.0
8.0
4.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Flow at CAUBOUT Outfall
SWMM 5
SWMM 4
9.0
8.0
7.0
Flow (CMS)
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Flow at SRUBOUT Outfall
SWMM 5
SWMM 4
12.0
10.0
Flow (CMS)
8.0
6.0
4.0
2.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-106 Comparisons of Flows at Outfalls SAUBOUT, CAUBOUT,
AND SRUBOUT for Example USER3
376
Dynamic Wave Routing Quality Assurance
Flow at SCANOUT Oufall
SWMM 5
SWMM 4
12.0
10.0
Flow (CMS)
8.0
6.0
4.0
2.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
5
6
7
5
6
7
Flow at CMRYOUT Outfall
SWMM 5
SWMM 4
1.0
Flow (CMS)
0.8
0.6
0.4
0.2
0.0
0
1
2
3
4
Elapsed Time (hours)
Flow at CCOROUT Outfall
SWMM5
SWMM 4
4.0
3.5
Flow (CMS)
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
1
2
3
4
Elapsed Time (hours)
Figure 19-107 Comparisons of Flows at Outfalls SCANOUT, CMRYOUT,
and CCOROUT for Example USER3.
377
Dynamic Wave Routing Quality Assurance
Flow in Link CMCPLOG
SWMM 5
SWMM 4
1.0
Flow (CMS)
0.8
0.6
0.4
0.2
0.0
-0.2
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-108a Comparison of Flows Along a Main Trunk Line of Example
USER3
Flow in Link CLIPNOT
SWMM 5
SWMM 4
4.0
3.0
Flow (CMS)
2.0
1.0
0.0
-1.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-108b Comparison of Flows Along a Main Trunk Line of Example
USER3
7
378
Dynamic Wave Routing Quality Assurance
Flow in Link CLIPSAR
SWMM 5
SWMM 4
6.0
5.0
Flow (CMS)
4.0
3.0
2.0
1.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-108c Comparison of Flows Along a Main Trunk Line of Example
USER3
Flow in Link CAUBPOR
SWMM 5
SWMM 4
10.0
9.0
8.0
Flow (CMS)
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-108d Comparison of Flows Along a Main Trunk Line of Example
USER3
7
379
Dynamic Wave Routing Quality Assurance
SWMM 5
SWMM 4
25.0
20.0
Flow (CMS)
15.0
10.0
5.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
7
Figure 19-109 Flow in Conduit SXANELG in the Original Model for Example USER3.
SWMM 5
SWMM 4
10.0
9.0
8.0
Flow (CMS)
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
Figure 19-110 Flow in Conduit SXANELG After Converting Storage Nodes
to Junctions Along its Trunk Line
7
380
Dynamic Wave Routing Quality Assurance
Flow in Link CLIPSAR
SWMM 5
SWMM 4
6.0
5.0
Flow (CMS)
4.0
3.0
2.0
1.0
0.0
0
1
2
3
4
Elapsed Time (hours)
5
6
5
6
7
Flow in Link CAUBPOR
SWMM 5
SWMM 4
20.0
15.0
Flow (CMS)
10.0
5.0
0.0
-5.0
0
1
2
3
4
Elapsed Time (hours)
Figure 19-111 Flow Comparisons for Selected Conduits of Example
USER3 for a 5 Second Routing Time Step
7
381
Dynamic Wave Routing Quality Assurance
Example USER4
Example USER4 is a combined sewer system covering 528 acres divided into
112 subcatchments. Its schematic is shown in Figure 19-112. There are 209 circular conduits connecting 209 junctions and one outfall. Each subcatchment
contributes both a dry weather sanitary flow (modeled as an external time series
inflow applied to the subcatchment’s outlet node) as well as a wet weather flow
produced for the storm shown in Figure 19-113. The basin is fairly steep as
shown by the profiles plotted in Figure 19-114. The system was analyzed over a
24 hour simulation period using a 5 second flow routing time step and a 5 minute reporting time step.
A
B
P1
P3
P2
P4
Outfall
Figure 19-112 Schematic of the Drainage System for Example USER4
382
Dynamic Wave Routing Quality Assurance
1.2
Rainfall (in/hr)
1.0
0.8
0.6
0.4
0.2
0.0
0
5
10
15
Elapsed Time (hours)
20
25
Figure 19-113 Rainfall Hyetograph for Example USER4.
The runoff calculations for both SWMM 4 and 5 are summarized in Table 19-9. Both programs produce essentially the same amount of runoff. The
peak flows in each conduit are compared in Figure 19-115. Again, there is excellent agreement between the two programs. Flow hydrographs for conduits P1,
P2, P3 and P4 are compared in Figure 19-116a-d while water depths at the upstream end of these conduits are compared in Figure 19-117a-d. Note how these
results reflect the steep-sloped nature of the drainage system, wherein the runoff
hydrographs entering the system are essentially translated downstream with little
delay or change in shape.
Table 19-9 System-Wide Water Balances for Runoff in Example USER4
(quantities in inches).
System Total
Precipitation
Evaporation
Infiltration
Surface Runoff
Final Surface Storage
SWMM 5
1.29
0.04
0.78
0.46
0.02
SWMM 4
1.28
0.06
0.77
0.45
0.00
383
Dynamic Wave Routing Quality Assurance
Profile of Trunk Line A
910
900
890
Elevation (ft)
880
870
860
850
840
830
820
5,000
4,000
3,000
Distance (ft)
2,000
1,000
0
05/08/2002 00:05:00
Profile of Trunk Line B
910
900
Elevation (ft)
890
880
870
860
850
840
830
820
0
500
1,000
1,500
2,000
Distance (ft)
2,500
3,000
3,500
4,000
05/08/2002 00:05:00
Figure 19-114 Elevation Profiles of Trunk Lines A and B for Example
USER4
384
Dynamic Wave Routing Quality Assurance
200
SWMM 4
150
100
50
0
0
50
100
150
200
SWMM 5
Figure 19-115 Comparison of Peak Flows (cfs) for the Conduits in Example
USER4
Flow in Conduit P1
SWMM 5
SWMM 4
25.0
Flow (CFS)
20.0
15.0
10.0
5.0
0.0
0
5
10
15
Elapsed Time (hours)
20
Figure 19-116a Comparison of Flows in Selected Conduits for Example
USER4
(continued overleaf)
25
385
Dynamic Wave Routing Quality Assurance
Flow in Conduit P2
SWMM 5
SWMM 4
100.0
90.0
80.0
Flow (CFS)
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
0
5
10
15
Elapsed Time (hours)
20
25
20
25
20
25
Flow in Conduit P3
SWMM 5
SWMM 4
35.0
30.0
Flow (CFS)
25.0
20.0
15.0
10.0
5.0
0.0
0
5
10
15
Elapsed Time (hours)
Flow in Conduit P4
SWMM 5
SWMM 4
180.0
160.0
140.0
Flow (CFS)
120.0
100.0
80.0
60.0
40.0
20.0
0.0
0
5
10
15
Elapsed Time (hours)
Figure 19-116 contd. Comparison of Flows in Selected Conduits for Example USER4
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Dynamic Wave Routing Quality Assurance
Depth at Upstream End of P1
SWMM 5
SWMM 4
1.2
Depth (ft)
1.0
0.8
0.6
0.4
0.2
0.0
0
5
10
15
Elapsed Time (hours)
20
25
Figure 19-117a Comparison of Water Depths at the Upstream Nodes of
Selected Conduits for Example USER4
Depth at Upstream End of P2
SWMM 5
SWMM 4
2.5
Depth (ft)
2.0
1.5
1.0
0.5
0.0
0
5
10
15
Elapsed Time (hours)
20
Figure 19-117b Comparison of Water Depths at the Upstream Nodes of
Selected Conduits for Example USER4 (continued overleaf)
25
387
Dynamic Wave Routing Quality Assurance
Depth at Upstream End of P3
SWMM 5
SWMM 4
1.2
0.8
0.6
0.4
0.2
0.0
0
5
10
15
Elapsed Time (hours)
20
25
Figure 19-117c Comparison of Water Depths at the Upstream Nodes of
Selected Conduits for Example USER4
Depth at Upstream End of P4
SWMM 5
SWMM 4
5.0
4.5
4.0
3.5
Depth (ft)
Depth (ft)
1.0
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
5
10
15
Elapsed Time (hours)
20
Figure 19-117d Comparison of Water Depths at the Upstream Nodes of
Selected Conduits for Example USER4
25
388
Dynamic Wave Routing Quality Assurance
Example USER5
Outfall
700pipe
740pipe
644
Inflow1
714
768pipe
893pipe
Detail A
Weir1
Inflow2
604
Detail B
Inflow3
Figure 19-118 Drainage System Schematic for Example USER5.
The final user-supplied example, USER5, models a 1,177 acre watershed using
145 subcatchments draining to 273 conduits, the majority of which are irregular
natural channels. The drainage system schematic is shown in Figure 19-118. The
design storm event is displayed in Figure 19-119. In addition, the system receives inflows at 3 locations from upper portions of the watershed that were
modeled separately. The inflow hydrographs for these locations are shown in
Figure 19-120. The system was analyzed over a 4 hour period using a 1 minute
reporting time step and a 0.5 second flow routing time step. Larger routing time
steps caused SWMM 4 (but not 5) to become highly unstable.
Table 19-10 System-Wide Water Balances for Runoff in Example USER5
(quantities in in.).
System Total
Precipitation
Evaporation
Infiltration
Surface Runoff
Final Surface Storage
Continuity Error (percent)
SWMM 5
2.93
0.02
1.00
1.77
0.15
0.10
SWMM 4
2.93
0.02
1.00
1.72
0.15
1.45
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Dynamic Wave Routing Quality Assurance
9.0
8.0
7.0
Rainfall (in/hr)
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0
0.2
0.4
0.6
0.8
1
1.2
Elapsed Time (hours)
1.4
1.6
1.8
2
Figure 19-119 Design Storm Hyetograph Used in Example USER5.
External Inflows
Inflow 1
Inflow 2
Inflow 3
1600.0
1400.0
Lateral Inflow (CFS)
1200.0
1000.0
800.0
600.0
400.0
200.0
0.0
0
0.5
1
1.5
2
Elapsed Time (hours)
2.5
3
3.5
4
Figure 19-120 External Lateral Inflows for Example USER5.
Table 19-10 lists the water balances obtained by both SWMM 5 and 4 for the
overall runoff computations for this example. The runoff results are very similar
with SWMM 5 having a smaller mass balance error than SWMM 4. Figure 19121 shows a comparison of the peak flows computed in the conduits by each
program (excepting the conduits contained in the portion of the drainage system
marked as Detail A, which will be discussed separately). For the remaining con-
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Dynamic Wave Routing Quality Assurance
duits there appears to be good agreement for peak flows with a few exceptions.
An example of one such exception is conduit 746_modify, located within the
area marked Detail B on the system schematic. The time series of flows in this
conduit computed by each program is shown in Figure 19-122. The difference in
peak flows can be attributed to the larger instability produced by SWMM 4
around the peak flow period. Similar behavior was observed at the other conduits where peak flow differences were large.
1500
SWMM 4
1000
500
0
0
500
1000
1500
SWMM 5
Figure 19-121 Comparison of Peak Flows (cfs) Produced by SWMM 4 and
5 for Example USER5
Flow in Conduit 746_modify
SWMM 5
SWMM 4
1200.0
1000.0
Flow (CFS)
800.0
600.0
400.0
200.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
Figure 19-122 Comparison of Flows in Conduit 746_modify for Example
USER5
4
391
Dynamic Wave Routing Quality Assurance
Conduit 644
SWMM 5
SWMM 4
70.0
60.0
Flow (CFS)
50.0
40.0
30.0
20.0
10.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
4
Figure 19-123a Comparison of Flows in Selected Conduits for Example
USER5
Conduit 893pipe
SWMM 5
SWMM 4
120.0
100.0
Flow (CFS)
80.0
60.0
40.0
20.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
Figure 19-123b Comparison of Flows in Selected Conduits for Example
USER5
4
392
Dynamic Wave Routing Quality Assurance
Conduit 604
SWMM 5
SWMM 4
400.0
350.0
Flow (CFS)
300.0
250.0
200.0
150.0
100.0
50.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
4
Figure 19-123c Comparison of Flows in Selected Conduits for Example
USER5
Conduit 714
SWMM 5
SWMM 4
900.0
800.0
700.0
Flow (CFS)
600.0
500.0
400.0
300.0
200.0
100.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
Figure 19-123d Comparison of Flows in Selected Conduits for Example
USER5.
4
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Dynamic Wave Routing Quality Assurance
Conduit 768pipe
SWMM 5
SWMM 4
200.0
180.0
160.0
Flow (CFS)
140.0
120.0
100.0
80.0
60.0
40.0
20.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
4
Figure 19-124a Comparison of Flows in Selected Conduits for Example
USER5
Conduit 700pipe
SWMM 5
SWMM 4
140.0
120.0
Flow (CFS)
100.0
80.0
60.0
40.0
20.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
Figure 19-124b Comparison of Flows in Selected Conduits for Example
USER5
4
394
Dynamic Wave Routing Quality Assurance
Conduit 740pipe
SWMM 5
SWMM 4
60.0
50.0
Flow (CFS)
40.0
30.0
20.0
10.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
4
Figure 19-124c Comparison of Flows in Selected Conduits for Example
USER5
Outfall
SWMM 5
SWMM 4
1400.0
1200.0
Flow (CFS)
1000.0
800.0
600.0
400.0
200.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
Figure 19-124d Comparison of Flows in Selected Conduits for Example
USER5
4
395
Dynamic Wave Routing Quality Assurance
Storage Unit 1SB1 (Conduit 644)
SWMM 5
SWMM 4
4.0
3.5
3.0
Depth (ft)
2.5
2.0
1.5
1.0
0.5
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
4
Figure 19-125a Comparison of Water Depths at the Upstream Nodes of
Selected Conduits for Example USER5
Node 46SB1 (Conduit 893pipe)
SWMM 5
SWMM 4
6.0
5.0
Depth (ft)
4.0
3.0
2.0
1.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
Figure 19-125b Comparison of Water Depths at the Upstream Nodes of
Selected Conduits for Example USER5
4
396
Dynamic Wave Routing Quality Assurance
Node 5SB6 (Conduit 604)
SWMM 5
SWMM 4
7.0
6.0
Depth (ft)
5.0
4.0
3.0
2.0
1.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
4
Figure 19-125c Comparison of Water Depths at the Upstream Nodes of
Selected Conduits for Example USER5
Node SB1018_OF (Conduit 714)
SWMM 5
SWMM 4
6.0
5.0
Depth (ft)
4.0
3.0
2.0
1.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
Figure 19-125d Comparison of Water Depths at the Upstream Nodes of
Selected Conduits for Example USER5
4
397
Dynamic Wave Routing Quality Assurance
Node 2SB11 (Conduit 768pipe)
SWMM 5
SWMM 4
14.0
12.0
Depth (ft)
10.0
8.0
6.0
4.0
2.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
4
Figure 19-126a Comparison of Water Depths at the Upstream Nodes of
Selected Conduits for Example USER5
Node 19SB17 (Conduit 700pipe)
SWMM 5
SWMM 4
10.0
9.0
8.0
Depth (ft)
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
Figure 19-126b Comparison of Water Depths at the Upstream Nodes of
Selected Conduits for Example USER5
4
398
Dynamic Wave Routing Quality Assurance
Node 10SB14 (Conduit 740pipe)
SWMM 5
SWMM 4
8.0
7.0
6.0
Depth (ft)
5.0
4.0
3.0
2.0
1.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
4
Figure 19-126c Comparison of Water Depths at the Upstream Nodes of
Selected Conduits for Example USER5
Node 0.10_RM (Upstream of Outfall)
SWMM 5
SWMM 4
10.0
9.0
8.0
Depth (ft)
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
4
Figure 19-126d Comparison of Water Depths at the Upstream Nodes of
Selected Conduits for Example USER5
Most conduits had similar flow profiles under both SWMM 4 and 5. Some
examples are shown in Figures 19-123a-d and 19-124a-d for the conduits labeled on the system schematic. Water depth profiles at the upstream nodes of
these same conduits are compared in Figures 19-125a-d and 19-126a-d.
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Dynamic Wave Routing Quality Assurance
One area of this system which showed considerable differences between
SWMM 4 and 5 is the one marked Detail A in Figure 19-118. The schematic of
this portion of the system is shown in Figure 19-127. It consists of a 130-foot
wide, flat channel that is fed by both a diversion box culvert and the outlet from
a 3.2 acre detention basin. The downstream end of the channel flows into an
outflow structure that consists of three weir openings at different heights. The
channel is divided into 10 individual segments whose elevation profile is shown
in Figure 19-128. Figures 19-129 through 19-131 display the time histories of
the flow entering the channel as well as the flows in the first and third sections
of the channel. Both SWMM 4 and 5 produce an oscillatory flow motion in these sections due to the outflow control exercised at its downstream end. The
magnitude of this oscillation seems suspiciously high in SWMM 4 when compared against the inflow to the channel. Interestingly, the oscillation appears to
be caused by the inertial terms of the momentum equation (those involving
changes in flow area with respect to space and time). Figure 19-132 shows what
happens in the third channel section when these terms are dropped from SWMM
5 using its “Ignore Inertial Terms” option.
Outlet Structure
Wide Flat Channel
Box Culvert
Inflow2
Detention Basin
Figure 19-127 Schematic of Detail A Portion of Example USER5.
1127
1126
1125
1124
1123
1122
1121
100
1120
0
1119
1118
Dynamic Wave Routing Quality Assurance
2SB2_MIL
400
750
740
Elevation (ft)
730
720
710
700
690
680
670
200
300
400
Distance (ft)
500
600
700
800
08/11/1998 00:01:00
Figure 19-128 Elevation Profile of the Channels in the Detail A Portion of
Example USER5.
Inflow
SWMM 5
SWMM 4
1200.0
1000.0
Flow (CFS)
800.0
600.0
400.0
200.0
0.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
Figure 19-129 Inflow to the Channel of Detail A for Example USER5.
4
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Dynamic Wave Routing Quality Assurance
First Section
SWMM 5
SWMM 4
2000.0
1500.0
Flow (CFS)
1000.0
500.0
0.0
-500.0
-1000.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
4
Figure 19-130 Flow in the First Section of the Channel of Detail A for Example USER5
Third Section
SWMM 5
SWMM 4
5000.0
4000.0
Flow (CFS)
3000.0
2000.0
1000.0
0.0
-1000.0
-2000.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
Figure 19-131 Flow in the Third Section of the Channel of Detail A for Example USER5.
4
402
Dynamic Wave Routing Quality Assurance
Third Section
SWMM 5 (non-inertial)
SWMM 4
2000.0
1500.0
Flow (CFS)
1000.0
500.0
0.0
-500.0
0
0.5
1
1.5
2
2.5
Elapsed Time (hours)
3
3.5
4
Figure 19-132 Flow in the Third Section of the Channel of Detail A for Example USER5 with Inertial Terms Ignored in SWMM 5.
As a final note on this example, both SWMM 4 and 5 were run with the routing time step increased from 0.5 to 5 seconds. SWMM 5 produced essentially
the same results, with an overall continuity error of 1.29 percent. The continuity
error produced by SWMM 4 was 619 percent with most flow time histories being clearly in error. As an example, Figure 19-133 compares the flow at the
outfall produced by the two programs and also plots the total inflow into the
system. The SWMM 5 outflow matches that of the run using the smaller time
step (see the last plot in Figure 19-124 (19-124d), although a visual comparison
is difficult due to the vast difference in the vertical axis scales in the two plots).
As reflected in its extremely high continuity error, the SWMM 4 outflow is an
order of magnitude too high for this system at the larger time step.
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Dynamic Wave Routing Quality Assurance
SWMM 4
SWMM 5
System Inflow
12000
Flow (cfs)
10000
8000
6000
4000
2000
0
Time (hours)
Figure 19-133 Flow Computed at the Outfall of Example USER5 Using a 5
Second Routing Time Step
19.7 Summary and Conclusions
The dynamic wave flow routing computations in SWMM 5 (version 5.0.006)
and SWMM 4 (version 4.4h) were compared against one another on a total of 20
test examples. These examples included:
• 10 examples from the original SWMM Extran Users Manual that
modeled various types of drainage system elements, such as orifices, weirs, pumps, irregular-shaped channels, and storage units
• 5 examples that tested the ability to model flat slopes, pipe constrictions, steep drops, adverse slopes, and inlet offsets.
• 5 real-world systems ranging in size from 59 to 273 conduits that
modeled a variety of storm sewer, combined sewer, and natural
channel drainage systems.
For the most part the time histories of flows and water depths produced by
SWMM 5 closely matched those of SWMM 4. There were some exceptions
however. In two cases these were due to differences in the assumptions used to
model specific elements between the two programs - bottom orifices and Type 1
pump wet wells. In some of the User Supplied test cases differences arose due to
numerical instabilities in the SWMM 4 solution, even with as low a time step as
0.5 seconds. These instabilities were most apparent in the examples that includ-
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Dynamic Wave Routing Quality Assurance
ed odd-shaped storage units and oscillatory flows due to significant inertial effects. In contrast SWMM 5 had no problem in handling these features.
SWWM 5 was generally able to produce stable solutions using a much higher routing time step than was SWMM 4. This was the case for 50 percent of the
Challenge and User-Supplied test examples. SWMM 5 also executed slightly
faster than SWMM 4 as shown by the run times for the User-Supplied examples
compared in Table 19-11.
Table 19-11 Execution Times for the User-Supplied Test Examples (in seconds).
Example
USER1
USER2
USER3
USER4
USER5
SWMM 4
4
17
52
30
56
SWMM 5
2
10
34
22
75
Overall, the Quality Assurance testing conducted in this study indicates that
the updated SWMM 5.0 program performs dynamic wave flow routing as good
as or better than SWMM 4.4.
References
Huber, W. C. and Dickinson, R.E., “Storm Water Management Model, Version 4: User’s
Manual”, EPA/600/3-88/001a, Environmental Research Laboratory, U.S. Environmental Protection Agency, Athens, GA, October 1992.
Metcalf & Eddy, Inc., University of Florida, Water Resources Engineers, Inc. “Storm
Water Management Model, Volume I – Final Report”, 11024DOC07/71, Water Quality Office, Environmental Protection Agency, Washington, DC, July 1971.
Roesner, L.A., Aldrich, J.A., and Dickinson, R.E., “Storm Water Management Model
User’s Manual Version 4: Extran Addendum”, EPA/600/3-88/001b, Environmental
Research Laboratory, U.S. Environmental Protection Agency, Athens, GA, October
1992.
Rossman, L.A. “Storm Water Management Model User’s Manual Version 5.0”,
EPA/600/R-05/040, National Risk Management Research Laboratory, U.S. Environmental Protection Agency, Cincinnati, OH, June 2005.
Schade, T., “Quality Assurance Project Plan SWMM Redevelopment”, National Risk
Management Research Laboratory, U.S. Environmental Protection Agency, Cincinnati, OH, November 2002.
Chapter 20
Land surface phase: theoretical basis
from earlier documentation for
SWMM 4 RUNOFF
20.1 Introduction
This chapter describes the theoretical basis of the land surface phase (hydrology), extracted from the earlier documentation for the SWMM 4 RUNOFF
Module. Because SWMM 5 was intended to be largely upwardly compatible
with SWMM 4, it follows that most of the input was kept similar, and thus most
of the input parameters and variables are also common. For these reasons alone
the theoretical background to SWMM 4 is indicative of the underlying methodology used in SWMM 5. Of course, differences arise in the details, particularly
in numerical procedures, and new processes added to SWMM 5 are unlikely to
be adequately covered.
SWMM routines have been developed to simulate both the quantity and quality of runoff in a drainage basin and represent the basin by an aggregate of
idealized subcatchments and gutters or pipes (links). The program accepts an
arbitrary rainfall or snowfall hyetograph and makes a step by step accounting of
snowmelt, infiltration losses in pervious areas, surface detention, overland flow,
channel flow, and the constituents washed into inlets (nodes), leading to the calculation of a number of hydrographs and pollutographs (at nodes).
Infiltration capacity is regenerated during dry periods by three methods.
Monthly evaporation totals are used to regenerate depression storage on both
pervious and impervious areas and are also considered an initial loss for each
time step with rainfall. Computations are bypassed during dry periods if infiltration and depression storage regeneration is complete.
Pollutant loadings on the subcatchment surfaces are generated during dry
time steps (i.e. no runoff) depending upon how they are input initially. Linear or
non-linear buildup may be used, and an upper limit should be specified. If desired, a rating curve (load versus flow) may be used instead of a washoff
equation.
Street sweeping occurs at intervals specified for each land use. The intervals
are computed on the basis of intervening dry time steps. A dry time step is one
in which the subcatchment receives no precipitation and has no water remaining
in impervious area depression storage or as snow. When snowmelt is simulated,
405
406
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
street sweeping may be bypassed for a specified interval of the year (e.g. the
winter months). Water quality parameters are simulated with arbitrary units. As
a user option, regeneration of selected constituents (e.g. chlorides) during dry
periods will occur only when snow is present.
The land surface phase may be run for periods ranging from fractions of a
second to decades. The overall catchment may be divided into an unlimited
number of subcatchments and of channel/pipes (links) plus inlets (nodes).
20.1.1 Basic Sources of Data
Importance of Land Surface Phase Data
The land surface phase forms the source of runoff and quality hydrographs and
pollutographs for most SWMM applications. Although SWMM allows direct
input of special hydrographs and pollutographs either bypassing the interfacing
file or in addition to it, in most cases these will be generated by the conversion
of rainfall or snowmelt into runoff and pollutant loads in the land surface phase.
Hence, the input data for this phase are probably the most important in the model. They are also most uncertain, and candidates for calibration.
Meteorological Data
Precipitation data are usually obtained from onsite gages maintained by an
agency that has performed rainfall and runoff monitoring such as a local consulting firm, water authority, or city, county, state, provincial or federal agency. In
the unfortunate event of a missing rain gage, precipitation data should be obtained from the nearest National Weather Service (NWS) for the United States,
or Atmospheric Environment Service (AES) Canada, station. The fundamental
data are precipitation hyetographs for the duration of the simulation. (See the
subsequent discussion on the use of synthetic rainfall data.) When snowmelt is
simulated, air temperatures and wind speed are needed in addition.
Surface Quantity Data
Flow routing data are usually derived from digital topographic maps, aerial photos and drainage system plans. These are customarily obtained from the local
agency responsible for drainage, usually the city or county. Some cities have
placed their data on the web. Especially for topographic maps, there is great variation in the quality of such data. Seekers of basic quantity data must be
prepared to spend several days at the municipal engineer's office to locate needed maps, plans etc. in public files.
A significant problem concerns the reliability of such data sources. Most
municipal offices contain design drainage drawings, but recent as-built information is sometimes rare. In older cities, design drawings may date back many
decades and only serve as a guide to what actually exists in the field. This most
often affects sewer slopes and cross sections (due to deterioration of old sewers).
Finally, combined sewer regulators and other hydraulic control locations are
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
407
often different from design drawings because of deterioration and maintenance.
In many instances, hydraulic connections exist that are not included on any
plans because of pragmatic action by maintenance crews. In other cases, evident
connections have been blocked off. In summary, all such data should be field
checked.
Surface Quality Data
Data required to formulate pollutographs are the most controversial of any
SWMM input data. Such data and their possible sources are discussed later. At
this point it is only re-emphasized that unless field sampling of runoff quality
has been performed, typically by a government or pollution control agency, the
credibility of predicted quality results cannot be established.
Default Parameters
Very few default values for parameters are included in the model. The objective
is to encourage you to obtain reasonable values for all parameters on a site specific basis, rather than to depend upon generalizations. Representative values
and guidelines for selection of such parameters are included herein.
20.1.2 General Control Data
Parameters govern the length of the wet time step (WET), the transitional time
step(s) between wet and dry (WETDRY), the dry (DRY) time step, the time
units of simulation, and the total simulation length. WET should be less than or
equal to the rainfall interval entered. It can be longer, but information is lost by
averaging the rainfall over a longer time period. A wet time step is a time step
with precipitation occurring on any subcatchment. A transitional time step has
no precipitation input on any subcatchment, but the subcatchment(s) still have
water remaining in surface storage. A dry time step has no precipitation input or
surface storage. However, it can have groundwater flow. The model is considered to be either globally wet, in the transitional period, or dry.
The time step should be smaller for periods of rapid change (i.e. during rainfall) and longer during periods of slower change (i.e. during transitional and dry
time steps). Land surface phase computations can use any time step from 1 second to 1 year. The solution technique is stable and convergent for any length
time step.
The rainfall intensity is constant over the wet time step when WET is a fraction of the rainfall interval. A smaller wet time step would be desirable when the
subcatchment is small and the time of concentration is a fraction of the rainfall
interval. When using one hour rainfall from the NWS wet time steps of 10
minutes, 15 minutes or longer can be used by the model.
The overland flow routing technique loses water through infiltration, evaporation, and surface water outflow during the transition periods. A subcatchment's
surface storage and surface flow always decreases during the transition from a
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
wet condition to a dry condition. A smooth curve or straight line are good models for the shape of the hydrograph. Transport routines usually have small time
steps and use linear interpolation for input hydrographs with longer time steps.
The transition time step, WETDRY, can be substantially longer than WET and
generate a good overland flow hydrograph. For example, a WET of 5 minutes
can be coupled with a WETDRY of 15 minutes or 30 minutes. When using
hourly rainfall input a WET of 15 minutes can be coupled to a WETDRY of 2
hours or 3 hours.
The dry time step should be 1 day to a week. The dry time step is used to update the infiltration parameters, generate groundwater flow, and produce a time
step value for the interface file. The dry time step should be day(s) in wet climates and days or week(s) in very dry climates. A synoptic analysis will be of
use in selecting the appropriate dry time step. Examine the average storm
interevent duration in the storm summary table. The average storm interevent
duration ranges from half a week to months.
The model can achieve substantial time savings with judicious usage of
WET, DRY, and WETDRY for both short and long simulations. As an example
consider using time steps of a WET of 2 minutes, a WETDRY of 15 minutes,
and a DRY of 1 hour (cf routing time-steps of several seconds, and print cycles
of 5 minutes)
20.2 Rainfall
20.2.1 Choice of Rainfall Data
Without doubt, rainfall data are the single most important group of hydrologic
data required by SWMM. Yet, they are often prepared as an afterthought, without proper consideration of the implications of their choice. The following
discussion will briefly describe options for rainfall input and their consequences.
Only rainfall is considered since for snow it is the physics of snowmelt rather
than snowfall which is important in determining runoff.
SWMM requires a hyetograph of rainfall intensities versus time for the period of simulation. For single event simulation this is usually a single storm,
whereas for continuous simulation, hourly, 15 min or other continuous data from
at least one gage are required - usually obtained from the nearest NWS or AES
station. For continuous simulation, the options are fewer since a satisfactory
generator of, say, a synthetic sub-hourly rainfall sequence is not usually available, and hence, a historical rainfall sequence is usually used.
For single event simulation, on the other hand, synthetic design storm sequences are indeed an option in lieu of historical records. However, several
pitfalls exist in the use of synthetic hyetographs.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
409
20.2.2 Modeling Objectives
Models might be used to aid in urban drainage design for protection against
flooding for a certain return period (e.g. five or ten years for minor drainage systems, and 100 years for major systems), or to protect against pollution of
receiving waters at a certain frequency (e.g. only one combined sewer overflow
per year). In these contexts, the frequency or return period needs to be associated
with a very specific parameter. That is, for rainfall one may speak of frequency
distributions of interevent times, total storm depth, total storm duration or average storm intensity, all of which are different (Eagleson, 1970, pp. 183–190).
Traditional urban drainage techniques often utilize frequencies of depths for
given durations, taken from intensity-duration-frequency (IDF) curves, which
are really conditional frequency distributions. But for the above objectives, and
in fact, for almost all urban hydrology, the frequencies of runoff quantity and
quality parameters are required, not those of rainfall at all. Thus, one may speak
of the frequencies of maximum flow rate, total runoff volume or duration or of
total pollutant loads. These distributions are in no way the same as for similar
rainfall parameters, although they may be related through analytical methods
(Howard, 1976; Chan and Bras, 1979; Hydroscience, 1979). Finally, for pollution control, the real interest may lie in the frequency of water quality standards
violations in the receiving water, which leads to further complications.
Ideally an engineer would develop costs and benefits for designs at several
frequencies in preparation for an economic optimization. In practice, it is often
difficult to accomplish this for even one case.
However, continuous simulation offers an excellent, if not the only, method
for obtaining the frequency of events of interest, be they related to quantity or
quality. But continuous simulation has the disadvantage of the need for a continuous rainfall record. This has led to the use of a design storm or design
rainfall or design event in a single event simulation instead. Of course, this idea
long preceded continuous simulation, before the advent of modern computers.
However, because of inherent simplifications, the choice of a design event leads
to problems.
20.2.3 Design Events
Two types of design events are used: historical sequence and synthetic sequence.
Synthetic sequences are usually constructed by the following steps (Arnell,
1982):
1. A storm duration is chosen, whether on an arbitrary basis or to coincide with the assumed catchment time of concentration tc (i.e.
equilibrium time at which outflow equals a constant fraction of
steady rainfall, or outflow equals rainfall on a catchment without
losses). The latter method itself has difficulties because of the dependence of tc on rainfall intensity and other parameters (Eagleson,
1970).
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
2. A return period is chosen in order to select the total storm depth for
the specified duration from intensity-duration-frequency (IDF)
curves.
3. A time history for the storm is assumed, usually on the basis of historical percentage mass curves. If peak intensities occur at the
beginning of the storm, the hyetograph takes on the appearance of a
decaying exponential curve. If the peak intensities occur near the
middle, a circus tent hyetograph results. The hyetograph is shaped
such that depths (or average intensities) for any duration centered
about the peak match those from the IDF curve. Several shapes are
commonly used (Arnell, 1982); in the U.S., the Chicago storm
(Keifer and Chu, 1957) and the SCS Type-II distribution (SCS,
1972) are frequently encountered.
4. The continuous hyetograph must then be discretized into a histogram for input to most models.
This procedure was apparently first detailed by Keifer and Chu (1957) and
then by Tholin and Keifer (1960) in Chicago. It has since been emulated by
many others (Arnell, 1982).
Many problems with this procedure for construction of synthetic hyetographs
(McPherson, 1978; Patry and McPherson, 1979; Arnell, 1982; Harremoes, 1983;
Adams and Howard, 1985), and with the underlying rational method and IDF
curves on which it is based (McPherson, 1969), have been enumerated. For example:
1. IDF curves themselves may consist of components of several different storms. They in no way represent the time history of a real storm.
2. When frequencies are assigned to total storm depths (independent of
duration) they generally do not coincide with the conditional frequencies of depth for the given duration obtained from IDF curves.
Thus, IDF curves cannot be used to assign frequencies to storm volumes. If synthetic hyetographs are used for studies of detention
storage or pollutant loads, where volumetric considerations are key,
no frequency should be assigned to the results.
3. Although the time history assigned to a synthetic storm may represent an average of many storms, there is often considerable
variability (see P. Bock, Discussion of Tholin and Keifer, 1960). If a
frequency could be assigned to a synthetic storm, it would probably
be considerably rarer than its nominal frequency, because the joint
probability of all time sequences within the storm corresponding to
those of an IDF curve is very low.
4. Antecedent conditions must still be chosen arbitrarily when using a
design event (either a synthetic or historical storm.) However, historical storms also provide their historical antecedent conditions. That
is, a historical storm can be run in a single-event mode using several
days of historical antecedent rainfall to generate realistic antecedent
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
411
moisture conditions in the catchment. This is not possible with synthetic storms.
5. A synthetic design event is one that never really happened. McPherson (1978) emphasizes the need to design with a real (historical)
event to ensure credibility in the eyes of the public.
6. There is evidence that synthetic design events may produce an overdesign if the objective is a design for a given return period. Marsalek
(1979a,b) has compared continuous simulation results of flood peaks
and volumes versus return period with results obtained by single
event simulations using the same model with input of n year synthetic events of the type described earlier. Flood peaks are always higher
for the synthetic events. Flood volumes are higher for most synthetic
events, depending on the method of generation of the event, because
the return periods assigned to the synthetic volumes are incorrect.
The verdict is not clear, however. Huber et al. (1986) compared synthetic versus historical storms for simulation of peak flows for a
2000-ac catchment in Tallahassee, Florida. They found that a larger
peak was generated by a 22 y historical storm than by a 25 yr SCS
Type II synthetic storm. In other words, synthetic storms are not always conservative.
20.2.4 Design Event Alternatives
In spite of all of its problems, use of a design event may still be required. Fortunately, there are ways in which this may be accomplished satisfactorily.
Foremost among these is the use of continuous simulation as a screening
tool. From a simple long-term continuous simulation, critical subsets may be
identified for further analysis. Walesh and Snyder (1979) present ideas along
this line, and Robinson and James (1984) and Huber et al. (1986) demonstrate
the ideas.
Continuous simulation may also be used to calibrate a synthetic design
event. That is, the design hyetograph may be adjusted such that it produces
flows or volumes that correspond for its return period to those produced by a
continuous simulation run. This has been done in studies in Northern Virginia
(Shubinski and Fitch, 1976). Proper adjustment of antecedent conditions can
also cause results from synthetic design events to match historical results (Wenzel and Voorhees, 1978).
In any event, several storm events should be processed for design considerations. These may be selected from a continuous simulation run, as suggested
above, or chosen from the historical record on another basis. For urban drainage
or flood control design, it may be desirable to choose a particular, well-known
local rainfall event and make sure that a design will handle that storm.
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
The question of appropriate rainfall input for models has generated intense
interest. Good discussions are given by McPherson (1978), Patry and McPherson (1979), Arnell (1982), James and Robinson (1982), and Huber et al. (1986).
20.2.5 Precipitation Data
Period-of-record daily data for 75 000 stations in the Global Historical Climatology Network are free from NOAA (subject to legal constraints
described at www.ncdc.noaa.gov/oa/climate/ghcn-daily). For Calgary, for
example, this file is
ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/all/CA003031093.dly. The format is ugly, but can be converted to tabular format. The Calgary dataset
includes snowfall 2004–present, snow-on-ground since 1957, and daily precipitation and maximum and minimum temperatures from 1881 through to
about last week(!).
20.2.6 Atmospheric Environment Service Data
Similar data are available in Canada from the Atmospheric Environment Service; and from Environment Canada (www.cmc.ec.gc.ca) which offers rainfall
IDF graphs and statistics.
20.2.7 Temporal Rainfall Variations
The required time detail for rainfall hyetographs is a function of the catchment
response to rainfall input. Small, steep, smooth, impervious catchments have fast
response times, and vice versa. As a generality, shorter time increment data are
preferable to longer time increment data, but for a large (e.g. 10 mi2 or 26 km2)
subcatchment (coarse schematization), even the hourly inputs usually used for
continuous simulation may be appropriate.
The rain gage itself is usually the limiting factor. Shorter time increment data
may usually be obtained only from tipping bucket gage installations.
The rainfall records obtained from a gage may be of mixed quality. It may be
possible to define some storms down to 1 minute to 5 minute rainfall intensities,
while other events may be of such poor quality (because of poor reproduction of
charts or blurred traces of ink) that only 1-hr increments can be obtained. Variable precipitation intervals can be modeled. This will allow the interspersing of
(for example) 5-minute, 15-minute, and hourly rainfall in a simulation.
20.2.8 Spatial Rainfall Variations
Even for small catchments, runoff predictions (and prototype measurements)
may be very sensitive to spatial variations of the rainfall. For instance, thunderstorms (convective rainfall) may be very localized, and nearby gages may have
very dissimilar readings. For modeling accuracy (or even more specifically, for
a successful calibration of SWMM), it is essential that rain gages be located
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
413
within and adjacent to the catchment, or a storm model such as RAINPAK
(James and Scheckenberger, 1983) be used.
SWMM accounts for the spatial variability by the assignment of several gages to a particular subcatchment. (Clearly, there is no point in the input of more
gage data than there are subcatchments.) If multiple gages are available, this is a
much better procedure than is the use of spatially averaged (e.g. Thiessen
weighted) data, because averaged data tend to have short- term time variations
removed (i.e. rainfall pulses are lowered and spread out). In general, if the rainfall is uniform spatially, as might be expected from cyclonic (e.g. frontal)
systems, these spatial considerations are not as important. In making this judgment, the storm size and speed in relation to the total catchment must be
considered. It should be noted that a moving or kinematic storm may only be
simulated in SWMM by using multiple gages. Storm motion may very significantly affect hydrographs at the catchment outlet (Yen and Chow, 1968; Surkan,
1974; James and Drake, 1980; James and Shtifter, 1981).
20.3 Snowmelt
The snowmelt part of this chapter has been excerpted from the 1988 SWMM 4
manual, and should be cautiously applied to SWMM 5 routines. Please send
your suggestions, comments and corrections as you come across them to the
editor, [email protected]
20.3.1 Introduction
Snowmelt is an additional mechanism by which urban runoff may be generated.
Although flow rates are typically low, they may be sustained over several days
and remove a significant fraction of pollutants deposited during the winter.
Rainfall events superimposed upon snowmelt baseflow may produce higher
runoff peaks and volumes as well as add to the melt rate of the snow. In the
North this is a common cause of flooding.
In the context of long term continuous simulation, runoff and pollutant loads
are distributed quite differently in time between the cases when snowmelt is and
is not simulated. The water and pollutant storage that occurs during winter
months in colder estimates cannot be simulated without including snowmelt.
Several hydrologic models include snowmelt computations: for example
Stanford Watershed Model (Crawford and Linsley, 1966), HSPF (Johanson et
al., 1980), NWS (Anderson, 1973, 1976), STORM (Hydrologic Engineering
Center, 1977; Roesner et al., 1974) and SSARR (Corps of Engineers, 1971). Of
these, only HSPF and STORM include pollutant routing options. Useful summaries of snowmelt modeling techniques are available in texts by Fleming
(1975), Eagleson (1970), Linsley et al. (1975), Viessman et al. (1977), and Gray
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
(1970). All of these draw upon the classic work Snow Hydrology of the Corps of
Engineers (1956).
As part of a broad program of testing and adaptation to Canadian conditions,
a snowmelt routine was placed in SWMM for single event simulation by Proctor
and Redfern, Ltd. and James F. MacLaren, Ltd. (1976a, 1976b, 1977), from
1974 to 1976. The basic melt computations were based on routines developed by
the U.S. National Weather Service (Anderson, 1973). The work herein has used
the Canadian SWMM snowmelt routines as a starting point and has considerably
augmented their capabilities as well as added the facility for snowmelt computations while running continuous SWMM. In addition, features have been added
which aid in adapting the snowmelt process to urban conditions, since most efforts in the past (except for STORM) have been aimed at simulation of spring
melt in large river basins. The work of the National Weather Service (Anderson,
1973) has also been heavily utilized, especially for the extension to continuous
simulation and the resulting inclusion of cold content, variable melt coefficients
and areal depletion.
The following sections describe the methodology presently programmed in
SWMM. It is intended to aid in understanding the various input parameters required, computations performed, and the output produced.
Snow Depth
Throughout the program, all snow depths are treated as depth of water equivalent to avoid specification of the specific gravity of the snow pack, which is
highly variable with time. The specific gravity of new snow is of the order of
0.09; an 11:1 or 10:1 ratio of snow pack depth to water equivalent depth is often
used as a rule of thumb. With time, the pack compresses until the specific gravity can be considerably greater, to 0.5 and above. In urban areas, lingering snow
piles may resemble ice more than snow with specific gravities approaching 1.0.
Although snow pack heat conduction and storage depend on specific gravity,
sufficient accuracy may be obtained without using it. It is adequate to maintain
continuity through the use of depth of water equivalent.
Most input parameters are in units of inches of water equivalent (in. w.e.).
For all computations, conversions are made to feet of water equivalent.
Single Event Simulation
During simulation, melt is generated at each time step using a degree-day
type equation during dry weather and Anderson’s NWS equation (1973) during
rainfall periods. Specified constant areas of each subcatchment are designated as
snow covered. Melt, after routing through the remaining snow pack, is combined
with rainfall to form the spatially weighted effective rainfall for overland flow
routing.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
415
Continuous Simulation
For continuous simulation, hourly precipitation depths from NCDC are utilized
along with daily maximum and minimum temperatures. The latter are interpolated sinusoidally to produce the temperature value at the beginning of a time
step, as explained in detail in the next subsection. If temperatures are below a
dividing value (e.g. 32 ˚F), precipitation values are treated as snow and keyed
with a negative sign. The interpolated temperatures are also used in the melt
computations.
Melt is again generated using a degree-day type equation during dry weather
and Anderson's NWS equation during rainfall periods. In addition, a record of
the cold content of the snow is maintained. Thus, before melt can occur, the
pack must be ripened; that is, heated to a specified base temperature.
One partition of the urban subcatchment is the normally bare impervious area. This is intended to represent surfaces such as streets, parking lots and
sidewalks which are subject to plowing or snow redistribution. SWMM includes
this feature.
Following the practice of melt computations in natural basins, areal depletion curves describe the spatial extent of snow cover as the pack melts. For
instance, shaded areas would be expected to retain a snow cover longer than
exposed areas. Thus, the snow covered area of each subcatchment changes with
time during continuous simulation.
Melt computations themselves proceed as in the single event simulation, except that the degree-day melt coefficients vary sinusoidally, from a maximum on
June 21 to a minimum on December 21.
Pollutant Simulation
Pollutant washoff is simulated using combined runoff from snowmelt and rainfall. Regeneration of any pollutant may depend upon whether snow cover is
present if, for example, chlorides are to be simulated.
20.3.2 Snow and Temperature Generation
NCDC Data
SWMM utilizes long-term precipitation and temperature data obtained from the
National Climatic Data Center (NCDC) at Asheville, North Carolina for the
nearest NWS or airport weather station of record. (Similar data, but with a different format, are available in Canada from the Atmospheric Environment
Service or Environment Canada at www.cmc.ec.gc.ca). If snowmelt is not simulated only the precipitation data is needed; hourly precipitation totals are
included on it for every day with measurable precipitation. Without snowmelt,
all such hourly values are treated as rainfall.
Maximum and minimum temperatures as well as several other meteorological parameters are available for every day of the year from many sources,
including NCDC (phone: 828-271-4800; www.ncdc.noaa.gov), EarthInfo
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
(phone: 303-938-1788; www.earthinfo.com) and Hydrosphere (phone: 303-4437839; www.hydrosphere.com). For snowmelt, only the ID number, date and
maximum and minimum temperatures are used, although other data (e.g. evaporation) may be used for other purposes. Temperature data are input and
processed for every day of the year, including summer months. Should an entry
(date) be missing, the maximum and minimum values for the previous day are
used.
Creation of Hourly Temperatures
The data may not list the time of day at which the minimum and maximum temperatures occur. Hence, the minimum temperature is assumed to occur at sunrise
each day, and the maximum is assumed to occur three hours prior to sunset. All
times are rounded to the nearest hour. This scheme obviously cannot account for
many meteorological phenomena that would create other temperature-time distributions but is apparently the most appropriate one under the circumstances.
Given the maximum and minimum temperatures and their assumed hours of
occurrence, the other 22 hourly temperatures are readily created by sinusoidal
interpolation, as sketched in Figure 20.1.
The interpolation is performed, using three different periods:
1. between the maximum of the previous day and the minimum of the
present,
2. between the minimum and maximum of the present, and
3. between the maximum of the present and minimum of the following.
Figure 20-1 Sinusoidal Interpolation of Hourly Temperatures
The times of day of sunrise and sunset are easily obtained as a function of
latitude and longitude of the catchment and the date. Techniques for these computations are explained by List (1966) and by the TVA (1972). SWMM utilizes
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
417
approximate (but sufficiently accurate) formulas given in the latter reference.
Their use is explained briefly below.
The hour angle of the sun h is the angular distance between the instantaneous
meridian of the sun (i.e. the meridian through which passes a line from the center of the earth to the sun) and the meridian of the observer (i.e. the meridian of
the catchment). It may be measured in degrees or radians or readily converted to
hours, since 24 hours is equivalent to 360 degrees or 2π radians. The hour angle
is a function of latitude, declination of the earth and time of day and is zero at
noon, true solar time, and positive in the afternoon. However, at sunrise and
sunset, the solar altitude of the sun (vertical angle of the sun measured from the
earth's surface) is zero, and the hour angle is computed only as a function of latitude and declination,
cos ( h ) = ! tan (" ) # tan ($ )
(20-1)
where
h = hour angle, radians,
∂ = earth's declination, a function of season (date),
radians, and
φ = latitude of observer, radians.
The earth's declination is provided in tables (e.g. List, 1966), but for programming purposes an approximate formula is used (TVA, 1972):
# 23.45 " &
* 2"
! =%
(172 ) D )-/
( cos ,
$ 180 '
+ 365
.
(20-2)
where D is number of the day of the year (no leap year correction is warranted)
and d is in radians.
Having the latitude as an input parameter, the hour angle is thus computed in
hours, positive for sunset, negative for sunrise, as
" 12 %
h = $ ' ( cos )1 ( ) tan * ( tan + )
#! &
(20-3)
The computation is valid for any latitude between the arctic and antarctic circles, and no correction is made for obstruction of the horizon.
The hour of sunrise and sunset is symmetric about noon, true solar time. True
solar noon occurs when the sun is at its highest elevation for the day. It differs
from standard zone time, i.e. the time on clocks) because of a longitude effect
and because of the equation of time. The latter is of astronomical origin and
causes a correction that varies seasonally between approximately ±15 minutes; it
is neglected here. The longitude correction accounts for the time difference due
to the separation of the meridian of the observer and the meridian of the standard
time zone. These are listed in Table 20-1.
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Table 20-1 Time Zones and Standard Meridians
Time Zone
Newfoundland Std. Time
Atlantic Std. Time
Example Cities
Standard Meridian
St. Johns's, Newfoundland
52.5a
Halifax, Nova Scotia
60
San Juan, Puerto Rico
Eastern Std. Time
New York, New York
75
Central Std. Time
Chicago, Illinois
90
Mountain Std. Time
Denver, Colorado
105
Pacific Std. Time
San Francisco, California
120
Yukon Std. Time
Yakutat, Alaskab
135
Alaska Std. Time
Anchorage, Alaska
150
Hawaiian Std. Time
Honolulu, Hawaii
Bering Std. Time
Nome, Alaska
165
a
The island of Newfoundland time zone is offset one half hour from other zones.
b
All of the Yukon Territory is on Pacific Standard Time.
It is readily computed as
DTLONG = 4 !
min
! (" # SM )
deg
(20-4)
where
DTLONG = longitude correction, minutes (of time),
θ = longitude of the observer, degrees, and
SM = standard meridian of the time zone, degrees,
from Table 20-1.
Note that DTLONG can be either positive or negative, and the sign should be
retained. For instance, Boston at approx. 71 ˚W has DTLONG = -16 minutes,
meaning that mean solar noon precedes EST noon by 16 minutes. (Mean solar
time differs from true solar time by the neglected equation of time.)
The time of day of sunrise is then:
HSR = 12 ! h +
DTLONG
60
(20-5)
DTLONG
60
(20-6)
and the time of day of sunset is
HSS = 12 + h +
These times are rounded to the nearest hour for use in SWMM. As stated earlier, the maximum temperature is assumed to occur at hour HSS - 3.
Standard time is used in all calculations and in NWS (NCDC) data. There is
no input or output that includes allowance for daylight savings time.
Generation of Snowfall Intensities
The estimated hourly temperatures T, in ºF, are compared to a dividing temperature, SNOTMP, for each hour with precipitation. Then if
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
T > SNOTMP, precipitation = rain
T ≤ SNOTMP, precipitation = snow
(20-7)
Snowfall depths are tagged as negative quantities for identification by later
components of the program.
Gage Catch Deficiency Correction
SCF-Gage Catch Deficiency Correction Factor for Snowfall
Precipitation gages tend to produce inaccurate snowfall measurements because
of the complicated aerodynamics of snow flakes falling into the gage. Snowfall
totals are generally underestimated as a result, by a factor that varies considerably depending upon gage exposure, wind velocity and whether or not the gage
has a wind shield. The program includes a parameter, SCF, which multiplies
snow depths only.
Although it will vary considerable from storm to storm, SCF acts as a mean
correction factor over a season in the model. Anderson (1973) provides typical
values of SCF as a function of wind speed, as shown in Figure 20-2, that may be
helpful in establishing an initial estimate.
The value of SCF can also be used to account for other factors, such as losses
of snow due to interception and sublimation not accounted for in the model. Anderson (1973) states that both losses are usually small compared to the gage
catch deficiency.
3
2.5
2
1.5
1
0
4
8
12
16
20
Wind Speed (MPH) at the Gage
Figure 20-2 Typical Gage Catch Deficiency Correction (Anderson, 1973, p.
5-20).
24
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
20.3.3 Subcatchment Schematization
Land Surface–Snow Cover Combinations
In order to have flexibility in treating different combinations of snow cover and
ground surface types, four such combinations are provided, as described in Table 20-2 and illustrated in Figure 20-3.
When snowmelt is not simulated, only the first three are used, as in the past.
Type 3, impervious area with no depression storage, is specified in land surface
phase by the parameter PCTZER, percent of impervious area with immediate
runoff. Snow cover is treated identically on types 1 and 3 since these surfaces
are likely to be of similar nature (e.g. streets, sidewalks, parking lots). These
surfaces are considered normally bare because of probable plowing, salting or
other rapid snow removal, but are subject to snow cover also, as described subsequently.
Table 20-2 Subcatchment Surface Classification
Type
Perviousness
Depression
Storage
1 (A1)
Impervious
Yes
2 (A2)
Pervious
Yes
3 (A3)
4 (A4)
Impervious
Impervious
No
Yes
Snow Cover and Extent
100% covContinuous*
ered.BareConstant
fraction, SNCP, of
area is snow covered.Bare
100% covNormally bare, but may
ered.BareConstant
have snow cover over 100%
fraction, SNCP, of
of type 1 plus type 3 area.
area is snow covered.
100% covered.Bare Snow covered subject to
areal depletion curve.
100% covered.
Same as type 1.
Snow covered subject to
areal depletion curve.
Apportionment of impervious area is different when simulating with and
without snowmelt. For the latter situation, the area with zero depression storage
(type 3) is taken to be a percentage, PCTZER, of the total impervious area. For
the former situation (with snowmelt), it is taken as a percentage, the normally
bare impervious area. Thus the type 3 area will vary according to whether
snowmelt is simulated or not, as shown in Figure 20-3. The effect on outflow is
very minor. The fraction of impervious area with 100% snow cover or subject to
an areal depletion curve is an input parameter, for each subcatchment.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
421
.Figure 20-3 Subcatchment Schematization With and Without Snowmelt
Simulation
Redistribution and Simulation of Snow Removal
Snow removal practices form a major difference between the snow hydrology of
urban and rural areas. Much of the snow cover may be completely removed
from heavily urbanized areas, or plowed into windrows or piles, with melt characteristics that differ markedly from those of undisturbed snow. Management
practices in cities vary according to location, climate, topography and the storm
itself; they are summarized in a study by APWA (1974). It is probably not possible to treat them all in a simulation model. However, in SWMM, provision is
made to approximate simulation of some practices.
It is assumed that all snow subject to redistribution (e.g. plowing) resides on
the normally bare category, types 1 and 3 above (see Figure 20-3) that might
consist of streets, sidewalks or parking lots. The desired degree of definition
422
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
may be obtained by using several subcatchments, although a coarse schematization (for example one or two subcatchments) may be sufficient for some
continuous simulations.
For each subcatchment, a depth of snow is input for this area, above which
redistribution occurs as indicated in Figure 20-4. All snow in excess of this
depth, say 0.1 in. to 0.2 in. water equivalent (2.5 mm to 5.1 mm), is redistributed
to other areas according to five fractions, SFRAC, input for each subcatchment.
These are described on Figure 20-4.
Figure 20-4 Redistribution of Snow
For example, if snow is usually windrowed onto adjacent impervious or pervious areas, SFRAC(1) or SFRAC(2) may be used. If it is trucked to another
subcatchment (the last one input is used for this purpose), a fraction SFRAC(3)
will so indicate, or SFRAC(4) if the snow is removed entirely from the simulated watershed. In the latter case, such removals are tabulated and included in the
final continuity check. Finally, excess snow may be immediately melted (i.e.
treated as rainfall), using SFRAC(5). The transfers are area weighted, of course,
and the five fractions should sum to 1.0. A depth of snow remains on the normally bare area and is subject to melting as on the other areas. See Table 20.3
for guidelines as to typical levels of service for snow and ice control (Richardson et al, 1974).
423
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Table 20-3a Guidelines for Levels of Service in Snow Control (Richardson
et al., 1974)
Road Classification
Level of Service
1. Low-Speed
Multilane Urban
Expressway
Roadway routinely patrolled during storms
All traffic lanes treated with chemicals
All lanes (including breakdown lanes)
operable at all times but at reduced speeds
Occassional patches of well-sanded snow
pack
Roadway repeatedly cleared by echelons
Clear pavement obtaiend as soon as possible
2. High-Speed 4Roadway routinely patrolled during storms
lane Divided
Driving and passing lanes treated with
Highways Interstate chemicals
System, ADT
Driving lane operable at all times at re>10,000a
duced speeds
Passing lane operable depending on
equipment availability
Clear pavement obtained as soon as possible
3. Primary HighRoadway is routinely patrolled during
ways Undivided 2
storms
and 3 lanes, ADT
Mostly clear pavement after storm slope
a
500 – 5000
Hazardous areas receive treatment of
chemicals or abrasive
4. Secondary
Roadway is patrolled at least once during a
a
Roads, ADT <500
storm
Bare left-wheel track with intermittent
snow cover
Hazardous areas are plowed and treated
with chemicals or abrasives as a first order
of work
Full width of road is cleared as equipment
becomes available
Snow
Depth to
Start
Plowing
(Inches)
0.5 to 1
Max. Snow
Depth on
Pavement
(Inches)
Full Pavement
Clear of Snow
after Storm
(Hours)
1
1
1
2
1.5
1
2.5
2
2
3
3
Table 20-3b Guidelines for Levels of Service in Ice Control (Richardson et
al., 1974)
Road Classification
1. Low-Speed Multilane Urban Expressway
2. High-Speed 4-lane Divided Highways
Interstate System, ADT >10,000a
3. Primary Highways Undivided 2 and 3
lanes, ADT 500 – 5000a
4. Secondary Roads, ADT <500a
a
ADT – average daily traffic
Full Pavement Clear of Ice after Storm Hours
12
12
24
48
No pollutants are transferred with the snow. The transfers are assumed to
have no effect on pollutant washoff and regeneration. In addition, all the parameters of this process remain constant throughout the simulation and can only
represent averages over a snow season.
The redistribution simulation does not account for snow management practices using chemicals, e.g. roadway salting. This is handled using the melt
equations, as described subsequently.
424
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
20.3.4 Melt Calculations
Theory of Snowmelt
Introduction
Excellent descriptions of the processes of snowmelt and accumulation are available in several texts and simulation model reports and in the well known 1956
Snow Hydrology report by the Corps of Engineers (1956). The important heat
budget and melt components are first mentioned briefly here; any of the above
sources may be consulted for detailed explanations. A brief justification for the
techniques adopted for snowmelt calculations in SWMM is presented below.
Snowpack Heat Budget
Heat may be added or removed from a snowpack by the following processes:
1. Absorbed solar radiation (addition).
2. Net longwave radiation exchange with the surrounding environment (addition or removal).
3. Convective transfer of sensible heat from air (addition or removal).
4. Release of latent heat of vaporization by condensate (addition) or, the opposite, its removal by sublimation (removing the latent heat of vaporization
plus the latent heat of fusion).
5. Advection of heat by rain (addition) plus addition of the heat of fusion if the
rain freezes.
6. Conduction of heat from underlying ground (removal or addition).
The terms may be summed, with appropriate signs, and equated to the
change of heat stored in the snowpack to form a conservation of heat equation.
All of the processes listed above vary in relative importance with topography,
season, climate and local meteorological conditions, but items 1-4 are the most
important. Item 5 is of less importance on a seasonal basis, and item 6 is often
neglected.
A snow pack is termed ripe when any additional heat will produce liquid
runoff. Rainfall (item 5) will rapidly ripen a snowpack by release of its latent
heat of fusion as it freezes in subfreezing snow, followed by quickly filling the
free water holding capacity of the snow.
Melt Prediction Techniques
Prediction of melt follows from prediction of the heat storage of the snow pack.
Energy budget techniques are the most exact formulation since they evaluate
each of the heat budget terms individually, requiring, as meteorological input,
quantities such as solar radiation, air temperature, dew point or relative humidity, wind speed, and precipitation. Assumptions must be made about the density,
surface roughness and heat and water storage (mass balance) of the snow pack
as well as on related topographical and vegetative parameters. Further complications arise in dealing with heat conduction and roughness of the underlying
ground and whether or not it is permeable.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
425
Several models individually treat some or all of these effects. One of the
more recent was developed for the NWS river forecast system by Anderson
(1976). Interestingly, under many conditions he found that results obtained
using his energy balance model were not significantly better than those obtained
using simpler (e.g. degree-day or temperature-index) techniques in his earlier
model (1973). The more open and variable the conditions, the better is the energy balance technique. Closest agreement between his two models was for
heavily forested watersheds.
Minimal data needed to apply an energy balance model are a good estimate
of incoming solar radiation, plus measurements of air temperature, vapor pressure (or dew point or relative humidity) and wind speed. All of these data,
except possibly solar radiation, are available at least one location (e.g. the airport) for almost all reasonably sized cities. Even solar radiation measurements
are taken at several locations in most states. Predictive techniques are also available, for solar radiation and other parameters, based on available measurements
(TVA, 1972; Franz, 1974).
Choice of Predictive Method
Two major reasons suggest that simpler (e.g. temperature-index) techniques
should be used for simulation of snowmelt and accumulation in urban areas.
First, even though required meteorological data for energy balance models are
likely to be available, there is a large local variation in the magnitude of these
parameters due to the urbanization itself. For example, radiation melt will be
influenced heavily by shading of buildings, and albedo reduced by urban pollutants. In view of the many unknown properties of the snowpack itself in urban
areas, it may be overly ambitious to attempt to predict melt at all! But at the
least, simpler techniques are probably all that are warranted. They have the added advantage of considerably reducing the already extensive input data to a
model such as SWMM.
Second, the objective of the modeling should be examined. Although it may
contribute, snowmelt seldom causes flooding or hydrologic extremes in an urban
area itself, other than in the far North. Hence, exact prediction of flow magnitudes does not assume nearly the importance it has in the models of, say, the
NWS, in which river flood forecasting for large mountainous catchments is of
paramount importance. For planning purposes in urban areas, exact quantity (or
quality) prediction is not the objective in any event; rather, these efforts produce
a statistical evaluation of a complex system and help identify critical time periods for more detailed analysis.
For these and other reasons, simple snowmelt prediction techniques such as
Anderson's NWS (1973) temperature-index method were incorporated into
SWMM. As described subsequently, the snowmelt modeling follows Anderson's
work in several areas, not just in the melt equations. The energy budget technique is illustrated later to show how it reduces to a temperature-index equation
under certain assumptions. It may be noted that the STORM model (Hydrologic
426
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Engineering Center, 1977; Roesner et al., 1974) also uses the temperature-index
method for snowmelt prediction, in a considerably less complex manner than is
now programmed in SWMM.
SWMM Melt Equations
Anderson's NWS model (1973) treats two different melt situations: with and
without rainfall. When there is rainfall (greater than 0.1 in./6 hr or 2.5 mm/6 hr
in the NWS model; greater than 0.02 in./hr or 0.51 mm/hr in SWMM), accurate
assumptions may be made about several energy budget terms. These are: zero
solar radiation, incoming longwave radiation equals blackbody radiation at the
ambient air temperature, the snow surface temperature is 32˚F (0˚C), and the
dew point and rain water temperatures equal the ambient air temperature. Anderson combines the appropriate terms for each heat budget component into one
equation for the melt rate. As used in subroutine MELT in SWMM, it is:
SMELT = (TA ! 32 ) "(0.00167 + SGAMMA "UADJ +
(20-8)
0.007 " PREC) + 8.5 "UADJ "(EA ! 0.18)
where
SMELT
TA
SGAMMA
GAMMA
UADJ
PREC
EA
=
=
=
=
=
=
=
melt rate, in./hr,
air temperature, ˚F,
7.5.GAMMA, in. Hg/˚F,
psychometric constant, in. Hg/˚F,
wind speed function, in. /in. Hg - hr,
rainfall intensity, in./hr, and
saturation vapor pressure at air temperature,
in. Hg.
The psychometric constant, GAMMA, is calculated as:
GAMMA = 0.000359 ⋅ PA
(20-9)
where
PA = atmospheric pressure (in. Hg.).
Average atmospheric pressure is in turn calculated as a function of elevation,
z:
# z &
# z &
PA = 29.9 !1.02 " %
( + 0.0032 " %
(
$ 1000 '
$ 1000 '
where
2.4
(20-10)
z = average catchment elevation, ft.
The elevation, z, is an input parameter, ELEV. The wind function, UADJ,
accounts for turbulent transport of sensible heat and water vapor. Anderson
(1973) gives:
UADJ = 0.006 !u
where
UADJ = wind speed function, in./in. Hg - hr, and
(20-11)
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
427
u = average wind speed 1.64 ft (0.5 m) above the
snow surface, mi/hr.
In practice, available wind data are used and are seldom corrected for the actual elevation of the anemometer. For SWMM, average wind speeds are input
for each month. Finally, the saturation vapor pressure, EA, is given accurately
by the convenient exponential approximation,
⎡ − 7701.544 ⎤
EA = 8.1175 ⋅ 10 6 exp ⎢
⎥
⎣ (TA + 405.0265 ) ⎦
(20-12)
where
EA = saturation vapor pressure, in. Hg, and
TA = air temperature, ˚F.
The origin of numerical constants found in equation 20-8 for SMELT is given by Anderson (1973), and reflects units conversions as well as U.S. customary
units for physical properties.
During non-rain periods, melt is calculated as a linear function of the difference between the air temperature, TA, and a base temperature, TBASE, using a
degree-day or temperature-index type equation:
SMELT = DHM ⋅ (TA − TBASE )
where
(20-13)
SMELT = snowmelt, in./hr (internally as ft/sec,)
TA = air temperature, ˚F,
TBASE = base melt temperature, oF, and
DHM = melt factor, in./hr-oF (internally ft/sec-oF).
Different values of TBASE and DHM may be input for three area classifications for each subcatchment (see Table 20-3 and Figure 20-3). For instance,
these parameters may be used to account for street salting which lowers the base
melt temperature. If desired, rooftops could be simulated as a separate subcatchment using a lower value of TBASE to reflect heat transfer vertically
through the roof. Values of TBASE will probably range between 25 and 32 oF
(- 4 and 0 oC). Unfortunately, few urban area data exist to define adequately appropriate modified values for TBASE and DHM, and they may be considered
calibration parameters.
In rural areas, the melt coefficient ranges from 0.03 - 0.15 in./day-oF
(1.4 - 6.9 mm/day-oC) or from 0.001 - 0.006 in./hr-oF (0.057 - 0.29 mm/hr-oC).
In urban areas, values may tend toward the higher part of the range due to compression of the pack by vehicles, pedestrians, etc. Again there appear to be few
data available to produce accurate estimates. However, Bengtsson (1981) and
Westerstrom (1981) do describe preliminary results of urban snowmelt studies
in Sweden, including degree-day coefficients which range from 3 to 8
mm/oC-day (0.07 - 0.17 in./oF-day). Additional data for snowmelt on an asphalt
surface (Westerstrom, 1984) gave degree-day coefficients of 1.7 - 6.5
mm/oC-day (0.04 - 0.14 in./oF-day).
428
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
It is important to realize that a degree-day equation may be derived from the
complete energy budget equation if parameters other than air temperature are
held constant. The equation is simply linearized about a desired air temperature
range, and numerical values for DHM and TBASE computed. The values are
accurate for the assumed values of other parameters, but may not appear to make
sense physically, e.g. it is not difficult to use parameters that produce negative
values of TBASE.
Figure 20-5 Seasonal Variation of Melt Coefficients.
TBASE remains constant, but DHM is allowed a seasonal variation, as illustrated in Figure 20-5.
Following Anderson (1973), the minimum melt coefficient is assumed to occur on December 21 and the maximum of June 21. Parameters DHMIN and
DHMAX are input for the three areas of each subcatchment, and sinusoidal interpolation is used to produce a value of DHM, constant over each day,
DHM =
( DHMAX + DHMIN ) ( DHMAX ! DHMIN )
2
+
2
$ #
"sin &
( D ! 81)')
%182
(
(20-14)
where
DHMIN = minimum melt coefficient, occurring Dec. 21,
in./hr-oF,
DHMAX = maximum melt coefficient, occurring June 21,
in./hr-oF, and
D = number of the day of the year.
No special allowance is made for leap year. However, the correct date (and
day number, D) is maintained.
Heat Exchange During Non-Melt Periods
During subfreezing weather, the snow pack does not melt, and heat exchange
with the atmosphere can either warm or cool the pack. The difference between
the heat content of the subfreezing pack and the (higher) base melt temperature
is taken as positive and termed the cold content of the pack. No melt will occur
until this quantity, COLDC, is reduced to zero. It is maintained in inches (or
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
429
feet) of water equivalent. That is, a cold content of 0.1 in. (2.5 mm) is equivalent
to the heat required to melt 0.1 in. (2.5 m) of snow. Following Anderson (1973),
the heat exchange altering the cold content is proportional to the difference between the air temperature, TA, and an antecedent temperature index, ATI,
indicative of the temperature of the surface layer of the snow pack. The revised
value of ATI at time step 2 is calculated as
ATI 2 = ATI 1 + TIPM ⋅ ( TA2 − ATI 1 )
(20-15)
ATI = antecedent temperature index, oF,
TA = air temperature, oF,
TIPM = antecedent temperature index parameter,
0 ≤ TIPM ≤ 1.0, and subscripts 1 and 2 refer
to time steps 1 and 2, respectively. The value
of ATI is not allowed to exceed TBASE, and
when snowfall is occurring, ATI takes on the
current air temperature.
The weighting factor, TIPM, is an indication of the thickness of the surface
layer of snow. Values of TIPM less than 0.1 give significant weight to temperatures over the past week or more and would thus indicate a deeper layer than
TIPM values greater than, say, 0.5, which would essentially only give weight to
temperatures during the past day. In other words, the pack will both warm and
cool more slowly with low values of TIPM. Anderson states that TIPM = 0.5 has
given reasonable results in natural watersheds, although there is some evidence
that a lower value may be more appropriate. No calibration has been attempted
on urban watersheds.
Following computation of the antecedent temperature index, the cold content
is changed by an amount
where
DCOLDC = RNM ! DHM !(ATI " TA)! DELT
where
(20-16)
DCOLDC = change in cold content, ft water equivalent,
RNM = ratio of negative melt coefficient to melt coefficient,
DHM = melt coefficient, ft/sec-oF,
TA = air temperature, oF,
ATI = antecedent temperature index, oF, and
DELT = time step, sec.
Note that the cold content is increased, (DCOLDC is positive) when the air temperature is less (colder) than the antecedent temperature index. Since heat
transfer during non-melt periods is less than during melt periods, Anderson uses
a negative melt coefficient in the heat exchange computation. SWMM computes
this simply as a fraction, RNM, of the melt coefficient, DHM. Hence, the negative melt coefficient, i.e. the product RNM x DHM, also varies seasonally. A
typical value of RNM is 0.6.
430
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
When heat is added to a snow pack with zero cold content, liquid melt is
produced, but runoff does not occur, until the free water holding capacity of the
snow pack is filled. This is discussed subsequently. The value of COLDC is in
units of feet of water equivalent over the area in question. The cold content volume, equivalent to calories or BTUs, is obtained by multiplying by the area.
Finally, an adjustment is made to equation 20-16 depending on the areal extent
of snow cover. This is discussed below.
Reduction of Energy Balance Equation to Degree-Day Equation
Purpose
This section presents equations that can be used for each term in the energy balance equation discussed earlier. The equation is then linearized and typical
numerical values are used to reduce it to a degree-day or temperature-index type
equation. The energy budget method will thus be better understood, and a physical basis for the simple prediction equations will be seen. Notation and
equations used follow Eagleson (1970), although an identical development could
be based on several other references.
Energy Budget
The energy budget given earlier is repeated and symbols are assigned to each
term. Units for each energy budget term are energy/area-time, e.g. ly/day (one
langley = one cal/cm2). However, within this scope, there are mixtures of units
used as convenient, e.g. minutes and days, oC and oF. The equation is ultimately
converted to U.S. customary units.
The snow pack energy budget is (e.g. units of ly/day):
ΔH = H rs + H g + H rl + H c + H e + H p
where
(20-17)
∆H = change in heat storage in snow pack,
Hrs = net short wave radiation entering the snow
pack,
Hg = conduction of heat to snow pack from underlying ground,
Hrl = net (incoming minus outgoing) long wave
radiation entering the snow pack,
Hc = convective transport of sensible heat from air
to snow pack,
He = release of latent heat of vaporization by condensation of atmospheric water vapor, and
Hp = advection of heat to snow pack by rain.
All terms can be positive or negative except for He (sublimation will not be
considered since it also involves the heat of fusion), Hrs and Hp (heat cannot be
removed by rain).
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
431
It will be assumed that the snow pack is ripe, and all heat added will product
liquid melt. Since inches of melt are desired, and it requires about 80 cal to melt
one gram of water (the latent heat of fusion) or 80 ly per cm, it requires 2.54
cm/in. x 80 ly/cm = 203.2 ly per inch of melt. The above equation is eventually
linearized and put in the form of the simple degree-day equation:
SMELT =
ΔH
= DHM ⋅ (Ta − Tb )
203.2
(20-18)
where
SMELT = melt rate, in./day,
∆H = change in heat storage, ly/day,
DHM = melt coefficient, in./day-oF,
Ta = air temperature, oF, and
Tb = base melt temperature, oF.
Other terms are defined where introduced. Caution should be used to ensure
that all terms eventually have the same units.
Short Wave Radiation, Hrs
Measured values from NWS stations are ordinarily used. The albedo (reflection
coefficient) of new snow can be as high as 0.80 and is seldom lower than 0.4 in
natural areas. Albedos of dirty urban snow surfaces are not documented, but
probably lower than 0.4. Net shortwave radiation Hrs is incoming minus reflected. If measurements of incoming radiation are unavailable, predictive techniques
may be used (TVA, 1972; Franz, 1974).
Heat Conduction Through Ground, Hg
Few data are available to quantify this term, and it is often determined as a residual in the energy budget equation. For urban areas, the intriguing possibility
exists of predicting heat transfer through roofs based upon assumed temperature
differences across the roof surface and thermal properties of the roofing material. In most cases, however, such calculations will be inaccurate and/or
infeasible. Hence, this term is usually neglected.
Net Long Wave Radiation, Hrl
Incoming minus outgoing long wave radiation is given by the Stefan- Boltzman
law:
H rl = 0.97 ⋅ ε a ⋅ σ ⋅ Ta 4 − 0.97 ⋅ σ ⋅ Ts 4
where
ETAa = atmospheric emissivity, a function of water
vapor content,
SIGMA = Stefan-Boltzman constant = 0.826 x 10-10
ly/min-K4,
Ta = air temperature at specified elevation, K,
Ts = snow surface temperature, K.
(20-19)
432
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
The first factor of 0.97 accounts for three percent reflection of incoming long
wave radiation, and the second factor of 0.97 is the emissivity of the snow surface.
The key unknown is the atmospheric emissivity, for which several empirical
formulas are available and in which the effect of clouds may also be included
(TVA, 1972). For example, a simple formula due to Anderson (1973) for clear
skies is:
ε a = 0.74 + 0.0049e
(20-20)
where
e = ground level atmospheric vapor pressure, mb.
Clouds may be assumed to radiate with an emissivity of 0.97 at the cloud
base temperature, if known.
The snow surface temperature may be taken to be 0 oC. Hence, it is necessary to linearize only the air temperature term. This may be done by means of a
Taylor series, under the assumption:
Ta = To + ΔT
(20-21)
The 4th-power term is then linearized about the reference temperature, To:
Ta4 = (To + !T ) = To4 + !T " 4 "To3 + ... = To3 (4Ta # 3To
4
(20-22)
The reference temperature, To will be a constant in the equation and is chosen near the midpoint of the expected temperature range at the time of
evaluation of the heat budget. Substituting:
H rl = 0.97 ! " a ! # !To3 (4Ta $ 3To ) $ 0.97 ! # !Ts4
(20-23)
which is linear in Ta, in K. Later, temperatures are converted to oF for consistency.
Convective Heat Transfer, Hc
Equations for this process (and for condensation melt) vary according to the assumptions made about surface roughness, wind speed profiles and turbulent
transfer coefficients. A common equation is (Eagleson, 1970):
H c = 203.2 ! kc !
where
"1
ps
! ( za ! zb ) 6 !ub ! (Ta " Ts )
po
(20-24)
ps = surface atmospheric pressure (consistent units
with po),
po = sea level atmospheric pressure (consistent
units with ps),
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
433
za = height above surface of air temperature (and
humidity) measurement, ft,
zb = height above surface of wind speed measurement, ft,
ub = wind speed at height zb, mph,
Ta = air temperature, oF,
Ts = snow surface temperature, oF, and
Hc = heat transfer in ly/day.
The factor 203.2 converts inches to langleys and the coefficient kc has been
measured in the Sierra Nevada mountains as:
1
kc = 0.00629 !in ! ft 3 !
hr
day ! F o ! mi
(20-25)
Condensation Heat Transfer, He
Since this and convective heat transfer are diffusive processes, the same introductory remarks hold. A common equation is (Eagleson, 1970):
"1
H e = 203.2 ! 8.5 ! ke ! ( za ! zb ) 6 ! ub ! ( ea " es )
(20-26)
where
ea = vapor pressure of atmosphere at temperature
and relative humidity at height za, mb,
es = svp at the snow surface temperature, mb and
other variables are defined as before.
The coefficient ke has been measured for the Sierras as:
1
ke = 0.00635 !in ! ft 3 !
hr
day ! mb ! mile
(20-27)
The factor 8.5 accounts for the latent heat of condensation supplying the latent heat of fusion to melt ripe snow. Because the ratio of latent heats (600/80)
equals 7.5, one inch of condensate causes 7.5 + 1 = 8.5 in. of melt.
Heat Advection by Rain, Hp
Heat is advected by rain in proportion to the rainfall depth and temperature of
the rain (assumed to be equal to the air temperature). Then:
H p = 1.41! d ! (Ta " Ts )
where
(20-28)
Hp = heat advected in ly/day, and
d = daily rainfall depth, in./day, temp in oF.
Combined Equations
Substituting into the first two equations, all equations may be combined:
434
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
SMELT =
!H
0.97 " # a " $ " 4To3 %
5 (
=
" ' 265.2 + Ta *
203.2
203.2
9 )
&
+1
+ ( za " zb ) 6 ub " kc "
H + H g 0.97 " $ "Ts4 o
ps
"Ta + rs
+
K
po
203.2
203.2
,
k p / 0.97 " # a " $ " 3To4
+ ( za " zb ) ub .8.5ke ( ea + es ) + c s 1 +
poTs 0
203.2
1.41" d " (Ta + Ts )
+
203.2
+1
6
(20-29)
where terms have been defined previously, and temperature units are:
To = reference temperature, K,
Ts = snow surface temperature, ˚F, (except K in
term 4), and
Ta = air temperature, ˚F.
The units of SMELT are inches/day. The equation is linear in the air temperature, Ta, which will be the only variable when the others are assigned numerical
values. Note also the conversion from K to ˚F in term 1. A further refinement
would make saturation atmospheric vapor pressure a linear function of air temperature, which is valid over say, 10˚F ranges. Then:
ea = r ⋅ eas = r ⋅ f (Ta )
where
(20-30)
r = relative humidity, fraction, and
eas = saturation vapor pressure at air temperature,
Ta.
This modification would then add another term in Ta to the long equation it is
pursued no further here.
Numerical Example
The following meteorological parameters are assumed:
Hrs = 288 ly/day,
To = 35˚F = 274.7K
Ts = 32˚F = 273K
za = 6 ft
zb = 20 ft
ub = 9 mph
es = es(32˚F) = 6.11 mb
r = 0.6
ea = 0.6 x es(35˚F) = 0.6 x 6.87 = 4.12 mb
εa = 0.90
po = 1013.2 mb
ps = 950 mb (about 2000 ft elevation),
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
435
rainfall = zero
Hg = zero
Each of the terms in the long equation is now evaluated, with units of inches/day:
Term
1
2
3
4
5
6
Constant
+11.24
+ 1.24
+ 1.417
- 3.154
- 1.200
-8.729
-0.426
Temperature Term
+ 0.0235 Ta
+ 0.0239 Ta
+0.0474 Ta
When the degree-day or temperature-index equation becomes, with Ta in oF:
SME LT = DHM ⋅ (Ta − Tb )
(20-31)
in.
day
in.
= 0.0474(Ta − 8.99)
day
in.
= 0.00198 (Ta − 8.99)
hr
o
The low value of Tb of about 9 F implies sufficient energy input (via solar
radiation and condensation) to cause melt even at low temperatures. This is not
really true, however, since the melt equation was linearized about a temperature
of 35oF and should only be used in that range. The exercise serves to indicate the
range of values that may be found when substituting meteorological observations into the equations. Although seemingly wrong values may result, e.g. base
melt temperatures less than zero, the equation with such values is still valid for
the input parameters used and over the range of the linearization.
= 0.0474Ta − 0.426
20.3.5 Areal Extent of Snow Cover
Introduction
The snow pack on a catchment rarely melts uniformly over the total area. Rather, due to shading, drifting, topography, etc., certain portions of the catchment
will become bare before others, and only a fraction, ASC, will be snow covered.
This fraction must be known in order to compute the snow covered area available for heat exchange and melt, and to know how much rain falls on bare
ground. Because of year to year similarities in topography, vegetation, drift patterns, etc., the fraction, ASC, is primarily only a function of the amount of snow
on the catchment at a given time; this function, called an areal depletion curve,
436
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
is discussed below. These functions are used in SWMM to describe the seasonal
growth and recession of the snow pack.
Areal Depletion Curves
As used in most snowmelt models, it is assumed that there is a depth, SI, above
which there will always be 100% cover. In some models, the value of SI is adjusted during the simulation; in SWMM it remains constant. The amount of
snow present at any time is indicated by the parameter WSNOW, which is the
depth (water equivalent) over each of the three possible snow covered areas of
each subcatchment (see Figure 20-3). This depth is nondimensionalized by SI,
called AWESI, for use in calculating the fraction of the area that is snow covered, ASC. Thus, an areal depletion curve is a plot of WSNOW/SI versus ASC;
a typical ADC for a natural catchment is shown in Figure 20-6. For values of the
ratio AWESI = WSNOW/SI greater than 1.0, ASC = 1.0, that is, the area is
100% snow covered.
Temporary Curve for New Snow.
Figure 20-6 Typical Areal Depletion Curve for Natural Area (Anderson,
1973, P. 3-15) and Temporary Curve for New Snow
Some of the implications of different functional forms of the ADC may be
seen in Figure 20-7. Since the program maintains snow quantities, WSNOW, as
the depth over the total area, AT, the actual snow depth, WS, and actual area
covered, AS, are related by continuity:
WSNOW ! AT = WS ! AS
where
WSNOW = depth of snow over total area AT, ft water
equivalent,
AT = total area, ft2
WS = actual snow depth, ft water equivalent, and
AS = snow covered area, ft2.
(20-32)
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
437
In terms of parameters shown on the ADC, this equation may be rearranged to
read:
AWESI =
WSNOW ! WS $ ! AS
=#
&'#
SI
" SI % " AT
$ ! WS $
&=#
& ' ASC
% " SI %
(20-33)
This equation can be used to compute the actual snow depth, WS, from
known ADC parameters, if desired. It is unnecessary to do this in the program,
but it is helpful in understanding the curves of Figure 20-7. Thus:
! AWESI $
WS = #
& ' SI
" ASC %
(20-34)
Figure 20-7 Effect of Snow Cover on Areal Depletion Curves.
Consider the three ADC curves B, C and D. For curve B, AWESI is always
less than ASC; hence WS is always less than SI as shown in Figure 20-7d. For
curve C, AWESI = ASC, hence WS = SI, as shown in Figure 20-7e. Finally, for
curve D, AWESI is always greater than ASC; hence, WS is always greater than
SI, as shown in Figure 20-7f. Constant values of ASC at 100% cover and 40%
438
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
cover are illustrated in Figure 20-7c, curve A, and Figure 20-7g, curve E, respectively. At a given time (e.g. t1 in Figure 20-7), the area of each snow depth
versus area curve is the same and equal to AWESI . SI, (e.g. 0.8 SI for time t1).
Curve B on Figure 20-7a is the most common type of ADC occurring in nature, as shown in Figure 20-6.
The convex curve D requires some mechanism for raising snow levels above
their original depth, SI. In nature, drifting might provide such a mechanism; in
urban areas, plowing and windrowing could cause a similar effect. A complex
curve could be generated to represent specific snow removal practices in a city.
However, the program utilizes only one ADC curve for all impervious areas
(e.g. area A4 of Figure 20-3 for all subcatchments) and only one ADC curve for
all pervious areas (e.g. area A2 of Figure 20-3 for all subcatchments). This limitation should not hinder an adequate simulation since the effects of variations in
individual locations are averaged out in the city-wide scope of most continuous
simulations.
The two ADC curves for pervious and impervious areas are input by the user, as are values of SI for each subcatchment. The program does not require the
ADC curves to pass through the origin, AWESI = ASC = 0; they may intersect
the abscissa at a value of ASC > 0 in order to maintain some snow covered area
up until the instant that all snow disappears (see Figure 20-6). However, the
curves may not intersect the ordinate, AWESI > 0 when ASC=0.
The preceding paragraphs have centered on the situation where a depth of
snow greater than or equal to SI has fallen and is melting. (The ADC curves are
not employed until WSNOW becomes less than SI.) The situation when there is
new snow needs to be discussed, starting from both zero or non-zero initial cover. The SWMM procedure again follows Anderson's NWS method (1973).
When there is new snow and WSNOW is already greater than or equal to SI,
them ASC remains unchanged at 1.0. However, when there is new snow on bare
or partially bare ground, it is assumed that the total area is 100% covered for a
period of time, and a "temporary" ADC is established as shown in Figure 20-6.
This temporary curve returns to the same point on the ADC as the snow melts.
Let the depth of new snow be SNO, measured in equivalent feet of water. Then
the value of AWESI will be changed from an initial value of AWE to a new value of SNEW by:
SNEW = AWE +
SNO
SI
(20-35)
It is assumed that the areal snow cover remains at 100% until 25% of the
new snow melts. This defines the value of SBWS of Figure 20-6 as:
SBWS = AWE + 0.75 !
SNO
SI
(20-36)
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
439
Anderson (1973) reports low sensitivity of model results to the arbitrary 25%
assumption. When melt produces a value of AWESI between SBWS and AWE,
linear interpolation of the temporary curve is used to find ASC until the actual
ADC curve is again reached. When new snow has fallen, the program thus
maintains values of AWE, SBA and SBWS (Figure 20-6).
The interactive nature of melt and fraction of snow cover is not accounted for
during each time step. It is sufficient to use the value of ASC at the beginning of
each time step, especially with a short (e.g. one-hour) time step for the simulation.
Use of the Value of ASC
The fraction of area that is snow covered, ASC, is used to adjust both the volume of melt that occurs and the volume of cold content change, since it is
assumed that heat transfer occurs only over the snow covered area. The melt rate
is computed from either of the two equations for SMELT. The snow depth is
then reduced from its value at time step 1 to time step 2 as:
WSNOW = WSNOW ! SMELT " ASC
2
1
(20-37)
with variables as defined previously and including appropriate continuity checks
in the program to avoid melting more snow than is there.
Cold content changes are also adjusted by the value of ASC. Thus, using
equation 20-16, cold content at time step 2 is computed from the value at time
step 1 by:
COLDC2 = COLDC1 + RNM ! DHM ! ( ATI " TA ) ! DELT ! ASC
(20-38)
where variables are as previously defined. Again there are program checks for
negative values of COLDC, etc.
Liquid Water Routing in Snow Pack
Production of melt does not necessarily mean that there will be liquid runoff at a
given time step since a snow pack, acting as a porous medium with a porosity,
has a certain free water holding capacity at a given instant in time. Following
PR-JFM (1976a, 1976b), this capacity is taken to be a constant fraction,
FWFRAC, of the variable snow depth, WSNOW, at each time step. This volume
(depth) must be filled before runoff from the snow pack occurs. The program
maintains the depth of free water, FW, ft of water, for use in these computations.
When FW = FWFRAC x WSNOW, the snow pack is fully ripe. The procedure
is sketched in Figure 20-8 below.
The inclusion of the free water holding capacity via this simple reservoir-type routing, delays and somewhat attenuates the appearance of liquid
runoff. The value of FWFRAC will normally be less than 0.10 and usually between 0.02 - 0.05 for deep snow packs (SWNOW > 10 in. or 254 mm water
equivalent). However, Anderson (1973) reports that a value of 0.25 is not unrea-
440
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
sonable for shallow snow packs that may form a slush layer. When rainfall occurs, it is added to the melt rate entering storage as free water. No free water is
released when melt does not occur, but remains in storage, available for release
when the pack is again ripe. This re-frozen free water is not included in subsequent cold content or melt computations.
Figure 20-8 Schematic of Liquid Water Routing Through Snow Pack
Net Runoff
Melt from snow covered areas and rainfall on bare surfaces are area weighted
and combined to produce net runoff onto the surface as follows:
RI = ASC ! SMELT + (1.0 " ASC ) ! RINE
(20-39)
where
RI = net runoff onto surface, ft/sec,
ASC = fraction of area that is snow covered,
SMELT = melt rate, including effect of attenuation due
to free water holding capacity, ft/sec, and
RINE = rainfall intensity, ft/sec.
Thus, the net runoff acts just as rainfall would act alone in subsequent overland flow and infiltration calculations.
If immediate melt is produced through the use of the snow redistribution
fraction SFRAC(5) (see Figure 20-4), it is added to the last equation. Furthermore, all melt calculations are ended when the depth of snow water equivalent
becomes less than 0.001 in. (0.025 mm), and remaining snow and free water are
converted to immediate melt and added to equation 20-39.
Effect of Snow on Infiltration and Surface Parameters
A snow pack tends to insulate the surface beneath it. If ground has frozen prior
to snowfall, it will tend to remain so, even as the snow begins to melt. Converse-
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
441
ly, unfrozen ground is generally not frozen by subsequent snowfall. The infiltration characteristics of frozen versus unfrozen ground are not well understood
and depend upon the moisture content at the time of freezing. For these and other reasons, SWMM assumes that snow has no effect on infiltration or other
parameters, such as surface roughness or detention storage (although the latter is
altered in a sense through the use of the free water holding capacity of the
snow). In addition, all heat transfer calculations cease when the water becomes
net runoff. Thus, water in temporary surface storage during the overland flow
routing will not refreeze as the temperature drops and is also subject to evaporation beneath the snow pack.
20.3.6 Snowmelt Quality
Pollutant Accumulation
Introduction
A detailed review of literature related to snowmelt quality is given by PR-JFM
(1976a, 1976b). Among the various contaminants found in deposited snow and
melt water, chlorides and lead appear to be the most serious and potentially hazardous. Chloride concentrations in runoff along major highways can be higher
than 20,000 mg/L, with typical values of from 1 000 to 10 000 mg/L. Several
other studies also document chloride contamination and discuss street salting
practices (Field et al., 1973; Richardson et al., 1974; Ontario Ministry of the
Environment, 1974). Lead concentrations in snow windrows have been as high
as 100 mg/L with typical values of from 1 to 10 mg/L. However, most deposited
lead results from automobile combustion and is insoluble. Hence, melt runoff
concentrations are lower than snow pack values and are mostly associated with
suspended solids.
Pollutant Loadings
Mechanisms and modeling alternatives for pollutant buildup and washoff are
described extensively in the runoff part of this manual. Any parameter related to
snowmelt may be generated using linear or non-linear buildup, or else a rating
curve (load proportional to flow). Specifically, street salting chemicals may be
simulated, such as sodium chloride or calcium chloride.
Adjustments for Presence of Snow
As a user option, regeneration of any quality constituent may be performed only
when snow is present. This option is indicated by parameter LINKUP. Thus, if
chlorides are simulated, for example, they will not be regenerated from bare
ground, during the summer months for instance. However, regeneration when it
does occur is a function only of snow presence, not the actual amount (depth).
Possible Loading Rates
Pollutant loading rates are best determined from local data. The literature review
of PR-JFM (1976a, 1976b) may also be consulted for tables that may be used to
442
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
estimate loading rate parameters for snow-associated pollutants. Other references will also be useful (e.g. Field et al., 1973; Richardson et al., 1974; Ontario
Ministry of the Environment, 1974).
Table 20-4 (Richardson et al., 1974) below lists recommended de-icing
chemical application rates for roadways. In general, PR-JFM show that observed
loading rates are functions of population density with suburban rates lower than
arterial highway rates, as indicated in Table 20-5 below. This is also true for
other pollutants.
Table 20-4 Guidelines for Chemical Application Rates (Richardson et al.,
1974).
WEATHER CONDITIONS
Temp
Pavement
Condition
30°F and Wet
above
25-30°F
Wet
Precipitation
Snow
Sleet or Freezing Rain
Snow or Sleet
Freezing Rain
20-25°F
Wet
Snow or Sleet
Freezing Rain
15-20°F
Below
15°F
Dry
Dry Snow
Wet
Wet Snow or
Sleet
Dry
Dry Snow
APPLICATION RATE (Pounds of material per mile of 2-lane road or 2lanes of divided)
Low- and High- Two and Three- Two-Lane
Instructions
Speed Multilane Lane Primary
Secondary
Divided
300 salt
300 salt
300 salt
Wait at least 0.5
hour before plowing
200 salt
200 salt
200 salt
Reapply as necessary
Initial at 400
initial at 400
initial at 400
Wait at least 0.5
salt, repeat at
salt, repeat at
salt, repeat at
hour before plow200 salt
200 salt
200 salt
ing; repeat
Initial at 300
initial at 300
initial at 300
Repeat as necessalt, repeat at
salt, repeat at
salt, repeat at
sary
200 salt
200 salt
200 salt
Initial at 500
initial at 500
initial at 500
Wait about 0.75
salt, repeat at
salt, repeat at
salt, repeat at
hour before plow250 salt
250 salt
250 salt
ing; repeat
Initial at 400
initial at 400
initial at 400
Repeat as necessalt, repeat at
salt, repeat at
salt, repeat at
sary
300 salt
300 salt
300 salt
Plow
plow
Plow
Treat hazardous
areas with 1200 of
20:1 Sand/Salt
500 of 3:1
500 of 3:1
1200 of 5:1
Wait about 1 hour
Salt/Calcium
Salt/Calcium
Sand
before plowing;
Chloride
Chloride
continue plowing
until storm ends;
then repeat application
Plow
plow
Plow
Treat hazardous
area with 1200 of
20:1 Sand/Salt
Table 20-5 Salting Rates Used in Ontario. (Proctor and Redfern Ltd. and
James F. MacLaren, Ltd., Vol. II, 1976b)
Population Density
(person per sq mile)
Less than 1,000
1,000 to 5,000
More than 5,000
Salting Rate per Application
(lb per lane-mile)
75 – 800
350 - 1,800
400 - 1,200
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
443
Street Sweeping
The effect of snow is included in two minor ways. First, beginning and ending
dates may be input to indicate the interval during the year subject to street
sweeping. If sweeping normally is not done between, say, December 1 and
March 1, because of high snow volumes, this may be so indicated.
Second, the presence of snow can alter the street sweeping interval. These intervals are specified for each of the five land uses. Each subcatchment is swept
when the number of dry time steps for that subcatchment exceeds the interval
for the given land use. A dry time step is one in which there is no precipitation
and no water or snow on areas A1 and A3 (Figure 20-3). Thus subcatchments
will not be swept until there is no snow or water on normally bare impervious
areas.
Other Considerations
The snow itself is assumed to be pure and contain no pollutants. Thus, the redistribution or transfers of snow described earlier (Figure 20-4) will not remove
accumulated pollutants. This is partially justified on the basis of the assumption
that such transfers would occur soon after fresh snow has fallen. They occur
during the same time step in the model.
Although it is not well tested, it is assumed that the principal effect of inclusion of snowmelt upon runoff quality predictions will be to shift the season and
magnitude of pollutant washoff. There will tend to be fewer periods of washoff
during the winter. As snowmelt, equivalent melt rates are likely to be less than
the usual magnitude of rainfall intensities experienced. Hence, concentrations
may tend to be more uniform during the melt washoff events.
20.3.7 Data Requirements
Input Parameters
Input parameters include watershed elevation, free water holding capacities, air
temperatures and wind speeds, and for each subcatchment, snow covered fractions, initial snow and free water, melt coefficients and base temperatures.
Continuous simulation requires the same data as above, except that air temperatures are computed using other input parameters. In addition, it requires the
snow gage correction factor, negative heat exchange parameter, areal depletion
curves, and, for each subcatchment, the redistribution parameters. Of course, the
required parameters can be kept to a minimum by keeping the number of subcatchments used to a minimum. Also required are pollutant loading data that
may or may not be related to snow.
Sensitivity
It is expected that melt volumes will be most related to the precipitation record,
and to the gage correction factor, which influences the amount of snow that falls.
Melt rates will be influenced by the melt coefficients and base temperatures,
444
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
and, to some degree, by the areal depletion curves which simulate the relative
piling or stacking of the snow.
Snowmelt Output
Snowmelt output consists of temperatures synthesized from daily maximum and
minimum values, and hourly precipitation totals, in which snowfall is tagged as
a negative value.
Snowmelt data
General parameters
The watershed elevation is used only to compute average atmospheric pressure,
which in turn has only a minimal effect on results. Hence, it is not a sensitive
parameter. The free water holding capacity of a snow pack is the volume of water (as a depth, in inches) within the pack that can be held as liquid melt prior to
releasing runoff. In the model it simply acts as an intermediate reservoir; the
larger its volume, the greater the delay in the appearance of runoff following the
conversion of snow to liquid water. Unfortunately, as is the case for most
snowmelt parameters, very few data exist that permit estimation of this parameter in urban areas, let alone make distinctions among three types of
snow-covered areas. However, some available information is summarized in
Table 20-6.
Table 20-6 Snowpack Free Water Holding Capacity (Anderson, 1973; Corps
of Engineers, 1956)
Model input is
FWFRAC
Where
FWFRAC
FWmax
WSNOW
=
=
=
=
FWmax/WSNOW
free water holding capacity as a fraction of snowpack depth,
maximum depth of free water stored in pack, inches, and
snowpack depth, inches water equivalent
Snowpack Conditions
FWFRAC
Typical deep pack (WSNOW > 10 in.)
0.02-0.05
Typical shallow early winter pack
0.05-0.25
Typical shallow spring pack or with slush layer
0.20-0.30
FWFRAC increases as pack density increases, pack depth decreases, slush layer increases, ground
slope decreases.
In natural areas, a surface temperature (SNOTMP) of 34 °F to 35 °F (1 °C to
2 °C) provides the dividing line between equal probabilities of rain and snow
(Eagleson, 1970; Corps of Engineers, 1956). However, parameter SNOTMP
might need to be somewhat lower in urban areas due to warmer surface temperatures.
The snow gage correction factor accounts for the error in snow gage measurements. The value of SCF is usually greater than 1.0 (the gage tends to
underestimate the catch) and increases as a function of wind speed. In practice,
SCF can be used as a calibration factor to account for gains or losses of snow it
cannot be determined from available data.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
445
During non-melt periods (i.e. sub-freezing weather) the temperature of the
snow pack follows the air temperature, but with a delay, since temperature
changes cannot occur instantaneously. The weighting factor, TIPM, is an indicator of the thickness of the surface layer of the snow pack. Values of TIPM
≤0.1 give significant weight to temperatures over the past week or more and
would indicate a deeper layer (thus inhibiting heat transfer) than TIPM values
greater than about 0.5 which would essentially only give weight to temperatures
during the past day. In other words the pack will both warm and cool faster (i.e.
track the air temperatures) with higher values of TIPM. Anderson (1973) states
that TIPM = 0.5 has given reasonable results in natural catchments, although
there is some reason to believe that lower values may be appropriate. No data
exist for urban areas.
Heat transfer within the snow pack is less during non-melt periods than during melt periods due to the presence of liquid water in the pack for the latter
case. Parameter RNM simply multiplies melt coefficients to produce a lower
negative melt coefficient for use during non-melt periods. A typical value for
natural areas is 0.6, with values for urban areas likely to be somewhat higher
because of the higher density of urban packs. The higher the value of RNM, the
more rapid is the heat gain or loss of the pack in response to air temperature
changes.
The catchment latitude and the longitude correction are used only to compute
hours of daylight for the catchment. Computations are insensitive to moderate
errors in these values.
NCDC Temperature Data
Continuous SWMM requires a complete time history of daily maximum and
minimum temperatures, from which hourly temperatures are synthesized by sinusoidal interpolation as described later. These max-min temperatures are
supplied on CD-ROM (e.g. NCDC Cooperative Station Data) from the National
Climate Data Center in Asheville (http://www.ncdc.noaa.gov), and from commercial distributors like EarthInfo (http://www.sni.net/earthinfo) and
Hydrosphere (http://hydrosphere.com). Values are interpolated for missing
dates. The compatibility of data records is discussed on SWMM Q&A.
Wind data
Wind speeds are used only for melt calculations during periods of rainfall. The
higher the values of wind speed, the greater are the convective and condensation
melt terms. Of course, if the simulation covers a large city, the wind speeds can
only be considered gross estimates of what are in reality highly variable speeds.
Average monthly speeds are often available from climatological summaries (e.g.
NOAA, 1974). An alternate source of wind speed data is TD-3200 from NOAA.
Areal depletion curves
Areal depletion curves (ADC) account, as discussed in section 20.3.5, for the
variation in actual snow covered area that occurs following a snowfall.
446
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Ed. Note: Equation removed as duplicate of equation 20.32
Ed. Note: Equation removed as duplicate of equation 20.33
Ed. Note: Equation removed as duplicate of equation 20.34
(20-40)
(20-41)
(20-42)
You must input the two ADC curves for impervious and pervious areas.
Air Temperatures
Air temperatures to be input may be obtained from instrumentation at the
catchment or from the nearest NWS (United States) or AES (Canada) station.
The temperatures are constant over the time interval DTAIR.
Overview of Procedures
Since snowmelt computations are explained in detail earlier (see, e.g., section
20.3.1), only an outline is given here. Most techniques are drawn from Anderson's (1973) work for the National Weather Service. For continuous simulation,
daily maximum and minimum temperatures from the NWS are converted to
hourly values by sinusoidal interpolation, as explained earlier.
Urban snow removal practices may be simulated through redistribution fractions input for each subcatchment (discussed below), through alteration of the
melt coefficients and base temperatures for the regions of each subcatchment,
and through the areal depletion curves used for continuous simulation. Anderson's temperature-index and heat balance melt equations are used for melt
computations during dry and rainy periods, respectively. For continuous simulation, the cold content of the pack is maintained in order to ripen the snow before
melting. Routing of melt water through the snow pack is performed as a simple
reservoir routing procedure, as in the Canadian study.
The presence of a snow pack is assumed to have no effect on overland flow
processes beneath it. Melt is routed in the same manner as rainfall.
Subcatchment Schematization
When snowmelt is simulated, a fourth subarea is added to each subcatchment as
illustrated in Figure 20-3. The properties of each subarea are described in Table
20-2. The main purpose of the fourth subarea is to permit part of the impervious
area (subarea A4) to be continuously snow covered (e.g. due to windrowing or
dumping) and part (subareas A1 plus A3) to be normally bare (e.g. streets and
sidewalks that are plowed). However, during continuous simulation, the normally bare portion can also have snow cover up to an amount WEPLOW inches
water equivalent (in. w.e.). (All snow depths and calculations are in terms of the
equivalent depth of liquid water.) The snow covered and normally bare impervious areas are determined from fraction SNN1. During single event simulation,
subarea A4 retains 100% snow cover until it has all melted. During continuous
simulation, an areal depletion curve, discussed earlier, is used.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
447
Similarly, for single event simulation, a fraction SNN2 of the pervious area
remains 100% snow covered. During continuous simulation, the whole pervious
area is subject to areal depletion curve.
Initialization
Initial snow depths (inches water equivalent) may be entered. This is likely to be
the only source of snow for a single event simulation although snowfall values
may be entered as negative precipitation. During continuous simulation, the effect of initial conditions will die out, given a simulation of a few months.
No liquid runoff will leave the snow pack until its free water holding capacity (due to its porosity) has been exceeded. The available volume is a constant
fraction, FWFRAC of the snow depth, WSNOW. Hence, initial values of free
water FW should maintain the inequality:
FW ≤ FWFRAC ⋅ WSNOW
(20-43)
Melt Equations
During periods of no rainfall, snowmelt is computed by a degree-day or temperature index equation:
SMELT = DHM ⋅ ( TA − TBASE )
where
(20-44)
SMELT = snowmelt rate, in. w.e./hr,
DHM = melt coefficient, in w.e./hr-ºF,
TA = air temperature, ºF, and
TBASE = snowmelt base temperature, ºF.
There is no melt when TA ≤ TBASE. For single event simulation, the melt
coefficient, DHM, remains constant. For continuous simulation it is allowed to
vary sinusoidally from a minimum value on December 21 to a maximum value
on June 21 (see Figure 20-5) in order to reflect seasonal changes.
Melt coefficients and base melt temperatures may be determined both theoretically and experimentally. Considering the former, it is possible to first write
a snowmelt equation from a heat budget formulation that includes all relevant
terms: change in snow pack heat storage, net short wave radiation entering pack,
conduction of heat to the pack from underlying ground, net (incoming minus
outgoing) longwave radiation entering pack, convective transport of sensible
heat from air to pack, release of latent heat of vaporization by condensation of
atmospheric water vapor, and advection of heat to snow pack by rain. (It is assumed here that the pack is ripe, i.e. just at the melting point, so that rain will
not freeze and release its latent heat of fusion.) The equation may then be linearized about a reference air temperature and reduced to the form of equation 2044.
448
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Figure 20-9 Degree-day Equations for Snow Melt (after Corps of Engineers, 956, plate 6-4).
Alternatively, observed melt, in inches per time interval, may be plotted
against temperature for that time interval, and a linear relationship developed of
the form of equation 20-44. An often-cited such development for natural areas is
illustrated in Figure 20-9 taken from the Corps of Engineers (1956). Viessman et
al. (1977) also present a good discussion of degree-day equations.
In the highly desirable but unlikely event that snowmelt data are available,
the experimental procedure of Figure 20-9 is probably best for urban areas due
to the considerable variation of snow pack and meteorological conditions that
will be encountered, making reasonable theoretical assumptions more difficult.
For natural areas, considerable range in melt coefficients exits, on the order of
0.000 6 to 0.008 in./hr-ºF (0.03 to 0.4 mm/hr-ºC). Although base melt temperatures are nominally near the freezing point (i.e. 32 ºF or 0 ºC) they may be
considerably lower depending on the exposure of the site and meteorological
conditions. For instance, for the linearization performed in Appendix III a base
melt temperature of 9 ºF (-13 ºC) was computed, which is valid only over the
range of air temperatures used in the linearization (approximately 30 ºF to 40 ºF
or -1 ºC to 5 ºC).
If the effects of snow removal practices (e.g. street salting) and land surface
factors are known, different melt coefficients and base melt temperatures may be
entered for the different snow covered subareas of a subcatchment. For instance,
street salting lowers the freezing point in proportion to the concentration of the
chemical. Handbook values (Chemical Rubber Co., 1976, pp. D218-D267) for
freezing point depression are plotted versus concentration in Figure 20-10 for
several common roadway salting chemicals.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
449
Figure 20-10 Freezing Point Depression Versus Roadway Salting Chemical Concentration. Compiled from data from CRC (1976).
To illustrate, the base melt temperature computed for pure water might be
lowered by an amount taken from Figure 20-10 if an idea is know about the likely concentration on the roadway. The concentration will depend upon the
amount of chemical applied and the amount of snowfall and might not be easily
computed. An interesting alternative would be to let SWMM predict it!
During periods (i.e. time steps) with rainfall, good assumptions can be made
about relevant meteorological parameters for the complete heat balance melt
equation. It then replaces the degree-day equation for wet time steps. Melt during these time steps is linearly proportional to air temperature and wind speed.
Areal Depletion Parameters
In the earlier discussion of areal depletion curves it was noted that there would
be 100% cover above a depth of SI inches water equivalent.
For natural areas, Anderson (1973) recommends that a distinction be made
on the basis of areal homogeneity. For a very heterogeneous area there are likely
to be areas that receive little snow, or else it will quickly melt. The value of SI
for such areas might be about the maximum depth anticipated. For homogeneous areas a much lower value would be appropriate.
No specific information is available for urban areas; however, they are likely
to be quite heterogeneous, especially if large, aggregated subcatchments are being used for the continuous simulation. Hence, a high value is probably
450
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
indicated. Whichever values are used, they should be consistent with the form of
the areal depletion curves. In general (depending somewhat on the areal depletion curve), the higher the value of SI, the more stacked up on a catchment is the
snow, and snowmelt will occur at a lower rate over a longer time.
Snow Redistribution
The program allows snow that falls on the normally bare impervious areas to be
redistributed according to the fractions given as SFRAC. This is intended to
simulate plowing and other snow removal practices in urban areas. Snow depths
above WEPLOW inches water equivalent are thus redistributed according to
Figure 20-4.
The value of WEPLOW depends upon the level of service given the particular impervious area. That is, At what snow depth do removal practices start?
Some guidelines are provided by Richardson et al. (1974) in Table 20-3.
The five fractions SFRAC, should sum to 1.0 and are defined on the basis of
the ultimate fate of the removed snow. For instance, if snow is plowed from a
street onto an adjacent impervious or pervious area, fractions SFRAC(1) or
SFRAC(2) would be appropriate. It may also be transferred to the last subcatchment (e.g. a dumping ground) or removed from the simulation (i.e.
removed from the total catchment) altogether. Finally, it may be converted to
immediate melt. Should variations in snow removal practices need to be simulated, different subcatchments can be established for different purposes and the
fractions varied accordingly.
20.4 Evaporation
Evaporation is input for each month or as a time series. It is considered as a loss
off the top. That is, evaporation is subtracted from rainfall depths or ponded water prior to calculating infiltration. Thus, subsequent use of the symbol i for
rainfall intensity is really rainfall intensity less evaporation rate. Although evaporation and infiltration are summed to form one total loss for the subcatchment
runoff calculations, separate totals are maintained for the overall continuity
check.
20.4.1 Evaporation Data
An average monthly evaporation rate is required for the month being simulated
in the single event mode, or for all months in the continuous mode. This rate is
subtracted from rainfall and snowmelt intensities at each time step and is also
used to replenish surface depression storage and provide an upper bound for soil
moisture and groundwater evaporation. However, it is not used to account for
sublimation from snow. Evaporation data may usually be obtained from climatological summaries (NOAA, 1974) or NWS or other pan measurements (e.g.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
451
from NWS Climatological Data, or Farnsworth and Thompson, 1982). Single
event simulations are usually insensitive to the evaporation rate, but evaporation
can make up a significant component of the water budget during continuous
simulation.
20.5 Infiltration
The original infiltration section was prepared by Dr. Russell G. Mein, Monash
University, Clayton, Victoria, Australia. Infiltration-Inflow (Section 20.5.5) was
added by CDM.
20.5.1 Introduction
For pervious areas SWMM users have the option of specifying one of three alternative infiltration models: SCS, the Horton model or the modified
Green-Ampt model (Horton, 1940; Green and Ampt, 1911). Horton's model is
empirical and is applicable only to events for which the rainfall intensity always
exceeds the infiltration capacity, although the modified form used in SWMM is
intended to overcome this deficiency.
On the other hand the Green-Ampt equation is a physically-based model
which can give a good description of the infiltration process. The Mein-Larson
(1973) formulation is applicable also for the case of rainfall intensity being less
than the infiltration capacity at the beginning of the storm. New data have been
published to help users evaluate the parameter values (e.g. Carlisle et al., 1981).
20.5.2 Integrated Horton's Equation
Cumulative Infiltration
SWMM and many other hydrologic analysis techniques have used Horton's
equation (Horton, 1940) for computing infiltration capacity into the soil as a
function of time,
f p = f ∞ + ( f o − f ∞ )e − αt
where
fp = infiltration capacity into soil, ft/sec,
f∞ = minimum or ultimate value of fp (at t = infinity), ft/sec,
fo = maximum or initial value of fp (at t = 0),
ft/sec,
t = time from beginning of storm, sec, and
α = decay coefficient, sec-1.
See Figure 20-11 for a sketch of Horton's equation.
(20-45)
452
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Figure 20-11 Horton Infiltration Curve and Typical Hyetograph. For the
case illustrated, runoff would be intermittent.
In fact, infiltration is:
[
]
f (t ) = min f p (t ),i (t )
(20-46)
where
f = infiltration into the soil, ft/sec, and
i = rainfall intensity, ft/sec.
This equation simply states that infiltration will be the lesser of rainfall and
infiltration capacity.
Typical values for parameters fo and fp are often greater than typical rainfall
intensities. Thus, when Horton's equation is used such that fp is a function of
time only, fp will decrease even if rainfall intensities are very light, as sketched
in Figure 20-11. This results in a reduction in infiltration capacity regardless of
the amount of entry of water into the soil.
To correct this problem, the integrated form of Horton's equation may be
used:
( )
tp
F t p = ∫ f p dt = f ∞ t p +
where
0
( fo − f∞ ) (
α
1− e
− αt p
)
F = cumulative infiltration at time tp, ft.
(20-47)
453
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Figure 20-12 Cumulative Infiltration, F, is the Integral of f, i.e. the Area Under the Curve.
This is shown schematically in Figure 20-12 and assumes that actual infiltration has been equal to fp. In fact, this is seldom the case, as sketched in Figure
20-11. Thus, the true cumulative infiltration will be:
t
(20-48)
F (t ) = ∫ f (t )dt
0
The last two equations may be used to define the time tp. That is, cumulative
infiltration is equated to the area under the Horton curve, and the resulting equation is solved for tp and serves as its definition. Unfortunately, the equation:
F = f ∞t p +
( fo − f∞ ) ⋅ (1 − e−αt
α
p
)
(20-49)
cannot be solved explicitly for tp, and it must be done iteratively. Note that:
tp ≤ t
(20-50)
which states that the time tp on the cumulative Horton curve will be less than or
equal to actual elapsed time. This also implies that available infiltration capacity, fp(tp) in Figure 20-12, will be greater than or equal to that given by Horton's
equation. Thus, fp will be a function of water infiltrated and not just a function
of time that ignores other effects.
Summary of Procedure
Use of the cumulative Horton function in SWMM may be summarized as
follows. Note that average values over time intervals are used.
454
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
1. At each time step, the value of fp depends upon F, the infiltration up
to that time. This is known by maintaining the value of tp. Then the
average infiltration capacity, fp, available over the next time step is:
fp =
( )
F (t 1 ) − F t p
1 t1 =t p + Δt
∫ f p dt =
Δt t p
Δt
(20-51)
The second equation is then used:
f = fp
f =i
i ≥ fp
if
if
(20-52)
i < fp
where
f = average actual infiltration over the time step,
ft/sec, and
i = average rainfall intensity over the time step,
ft/sec.
1. Cumulative infiltration is then incremented:
F (t + Δt ) = F (t ) + ΔF = F (t ) + fΔt
(20-53)
where
∆F = f ∆t = addition cumulative infiltration, ft.
2. A new value of tp is then found, tp1, from the equation for F. If
∆F = fp ∆t, tp1 is found simply by tp1 = tp + ∆t. However, it is necessary
to solve the equation for F iteratively when the new tp1 is less than tp +
∆t, as sketched in Figure 20-12. This is done using the Newton-Raphson procedure:
FF = 0 = f ∞ t p +
( fo − f∞ ) (
α
1− e
− αt p
)− F
FF ′ = f p ( t p ) = f ∞ + ( f o − f ∞ )e
− αt p
(20-54)
(20-55)
An initial guess is made for tp1, say,
t p1 ( n ) = t p +
Δt
2
(20-56)
where n refers to the number of the iteration. Then a correction is made
to tp1 (n) using FF and FF':
(20-57)
t p ( n + 1 ) = t p ( n ) − FF / FF'
1
1
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
455
The convergence criterion is:
FF
< 0.001Δt
FF ′
(20-58)
and is achieved quite rapidly.
3. If tp ≥ 16/k, the Horton curve is essentially flat and fp = fm. Beyond this
point there is no need to iterate since fp will be constant at fm and independent of F.
Regeneration of Infiltration Capacity
Figure 20-13 Regeneration (Recovery) of Infiltration Capacity During Dry
Time Steps.
For continuous simulation, infiltration capacity will be regenerated (recovered)
during dry weather. SWMM performs this function whenever there are dry time
steps - no precipitation or surface water - according to the hypothetical drying
curve sketched in Figure 20-13:
f p = f o − ( f o − f ∞ )e − α d ( t −t w )
(20-59)
αd = decay coefficient for the recovery curve, sec-1,
tw = hypothetical projected time at which fp = fm
on the recovery curve, sec.
In the absence of better knowledge of αd, it is taken to be a constant fraction
or multiple of α:
(20-60)
α d = Rα
where
456
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
where
R = constant ratio, probably << 1.0 (implying a
longer drying curve than wetting curve).
New values of tp are then generated as indicated in Figure 20-13. Let
tpr = value of tp at beginning of recovery, sec,
fr = corresponding value of fp, ft/sec, and
Tw1 = tw1 - tw, Tw2 = tw2 - tw, etc.
Thus, along the recovery curve, for example,
f 1 = f p ( t w1 ) = f o − ( f o − f ∞ )e
− α d Tw1
(20-61)
Solving this equation for the initial time difference, Twr,
Twr = t pr − t w =
f − f∞
1
ln o
αd
fo − fr
(20-62)
then
Tw1 = Twr + Δt
(20-63)
and f1 in Figure 20-13 is found from the equation for f. Finally tp1 is found from
Horton's equation:
t p1 =
1 fo − f∞
ln
α f1 − f ∞
(20-64)
using the above four equations, the procedure may be summarized as follows:
1. Knowing tpr, find fr from Horton's equation,
2. Solve the equation for Twr,
3. Increment Twr according to the third equation above,
4. Solve the equation for f1,
5. Solve the equation for tp1.
All steps are combined in:
t p1 = −
[
(
1
− αt
ln 1 − e −α d Δt 1 − d pr
α
)]
(20.65)
On succeeding time steps, tp1 may be substituted for tpr, tp2 may be substituted for tp1, etc. Note that fp has reached its maximum value of fo when tp = 0.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
457
Program Variables
Correspondence of program variables to those of this subsection is as follows:
∆t = DELT
tp1 = TP1
fo = WLMAX
FF = FF
fm = WLMIN
FF' = DFF
k = DECAY
f = RLOSS (RLOSS is also the sum of
infiltration plus evaporation)
R = REGEN
i = RI
tp = TP
fp = RLOSS1
F = CUMINF = CUMI
Horton Infiltration input data:
Infiltration capacity as a function of time is given by Horton (1933, 1940) by
equation 20-45.
Ed Note: Equation removed, as duplicate of equation 20-45
(20-66)
It describes the familiar exponential decay of infiltration capacity evident
during heavy storms. However, the program does not use equation 20-45 directly; rather, the integrated form is used in order to avoid an unwarranted reduction
in fp during periods of light rainfall.
Required parameters are fo (WLMAX), f∞ (WLMIN) and α (DECAY). In
addition a parameter used to regenerate infiltration capacity (REGEN) is required for continuous simulation. Although the Horton infiltration equation is
probably the best-known of the several infiltration equations available, there is
little to help you select values of parameters fo and α for a particular application,
(fortunately, some guidance can be found for the value of f∞). Since the values
of fo and α (and often f∞) depend on the soil, vegetation, and initial moisture
content, ideally these parameters should be estimated using results from field
infiltrometer tests for a number of sites of the watershed and for a number of
antecedent wetness conditions. If it is not possible to use field data to find estimates of fo, f∞, α and for each subcatchment, the following guidelines should be
helpful.
The U.S. Soil Conservation Service (SCS) has classified most soils into Hydrologic Soil Groups, A, B, C and D, dependent on their limiting infiltration
capacities, f∞. (Well drained, sandy soils are A; poorly drained, clayey soils are
D.) A listing of the groupings for more than 4 000 soil types can be found in the
SCS Hydrology Handbook (1972, pp. 7.6-7.26); a similar listing is also given in
the Handbook of Applied Hydrology (Ogrosky and Mockus, 1964, pp.
21.12-21.25), but the former reference also gives alternative groupings for some
soil types depending on the degree of drainage of the subsoil. The soil type itself
may be found in the U.S. from county SCS Soil.
458
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Survey maps
The best source of information about a particular soil type is a publication entitled Soil Survey Interpretations available from a local SCS office in the United
States. Information on the soil profile, the soil properties, its suitability for a
variety of uses, its erosion and crop yield potential, and other data is included on
the sheet provided. Parameter f∞ is essentially equal to the saturated hydraulic
conductivity, Ks, which is called permeability on the soil survey interpretation
sheet. For Conestoga Silt Loam, a range of 0.63- 2.0 in/hr (16-51 mm/hr) is typical.
Alternatively, values for f∞ according to Musgrave (1955) are given in Table
20-7. To help select a value within the range given for each soil group, you
should consider the texture of the layer of least hydraulic conductivity in the
profile. Depending on whether that layer is sand, loam, or clay, the f∞ value
should be chosen near the top, middle, and bottom of the range respectively. For
example, the data sheet for Conestoga silt loam identifies it as being in Hydrology Group B which puts the estimate of f∞ into the range of 0.19-0.30 in/hr
(3.8-7.6 mm/hr), much lower than the Ks value discussed above. Examination of
the texture of the layers in the soil profile indicates that they are silty in nature,
suggesting that the estimate of the f∞ value should be in the low end of the
range, say 0.15-0.20 in/hr (3.8-5.1 mm/hr). A sensitivity test on the f∞ value will
indicate the importance of this parameter to the overall result.
Table 20-7 Values of f∞ for Hydrologic Soil Groups (Musgrave, 1955)
Hydrologic Soil Group
A
B
C
D
F∞ (in/hr)
0.45 - 0.30
0.30 - 0.15
0.15 - 0.05
0.05 – 0
Caution should be used in applying values from Table 20-7 to sandy soils
(group A) since reported Ks values are often much higher. For instance, sandy
soils in Florida have Ks values from 7 to 18 in/hr (180-450 mm/hr) (Carlisle et
al., 1981). Unless the water table rises to the surface, ultimate infiltration capacity will be very high, and rainfall rates will almost always be less than f∞, leading
to little or no overland flow from such soils.
For any field infiltration test the rate of decrease (or decay) of infiltration capacity, α, from the initial value, fo, depends on the initial moisture content. Thus
the α value determined for the same soil will vary from test to test.
It is postulated here that, if fo is always specified in relation to a particular
soil moisture condition (e.g. dry) and for moisture contents other than this the
time scale is changed accordingly (i.e. time 0 is adjusted to correspond with the
constant fo), then α can be considered a constant for the soil independent of initial moisture content. Put another way, this means that infiltration curves for the
459
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
same soil, but different antecedent conditions, can be made coincident if they are
moved along the time axis. Butler (1957) makes a similar assumption.
Values of α found in the literature (Viessman et al., 1977; Linsley et al.,
1975; Overton and Meadows, 1976; Wanielista, 1978) range from 0.67 to 49
hr.-1 Nevertheless most of the values cited appear to be in the range 3-6 hr- 1
(0.00083-0.00167 sec-1). The evidence is not clear as to whether there is any
relationship between soil texture and the α value although several published
curves seem to indicate a lower value for sandy soils. If no field data are available, an estimate of 0.001 15 sec-1 (4.14 hr-1) could be used. Use of such an
estimate implies that, under ponded conditions, the infiltration capacity will fall
98% of the way towards its minimum value in the first hour, a not uncommon
observation. Table 20-8 shows the rate of decay of infiltration for several values
of α.
Table 20-8 Rate of Decay of Infiltration Capacity for Different Values of α
α value
hr-1 (sec-1)
2
3
4
5
(0.00056)
(0.00083)
(0.00115)
(0.00139)
Percent of decline of infiltration capacity towards limiting value fc after 1
hour.
76
95
98
99
The initial infiltration capacity, fo depends primarily on soil type, initial
moisture content, and surface vegetation conditions. For example, Linsley et al.
(1982) present data which show, for a sandy loam soil, a 60% to 70% reduction
in the fo value due to wet initial conditions. They also show that lower fo values
apply for a loam soil than for a sandy loam soil. As to the effect of vegetation,
Jens and McPherson (1964, pp. 20.20 - 20.38) list data which show that dense
grass vegetation nearly doubles the infiltration capacities measured for bare soil
surfaces.
For the assumption to hold that the decay coefficient α is independent of initial moisture content, fo must be specified for the dry soil condition. The
continuous version of SWMM automatically calculates the fo value applicable
for wetter conditions as part of the moisture accounting routine. However, for
single-event simulation, you must specify the fo value for the storm in question,
which may be less than the value for dry soil conditions.
Published values of fo vary depending on the soil, moisture, and vegetation
conditions for the particular test measurement. The fo values listed in Table 20-9
can be used as a rough guide. Interpolation between the values may be required.
Ed. Note: Equation removed, as duplicate of equation 20-59
Ed. Note: Equation removed, as duplicate of equation 20-60
(20-67)
(20-68)
The parameter R in equation 20.60 is represented in the program by REGEN.
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Table 20-9 Representative Values for fo.
A.
DRY soils (with little or no vegetation):
Sandy soils: 5 in/hr
Loam soils: 3 in/hr
Clay soils: 1 in/hr
B.
DRY soils (with dense vegetation):
Multiply values given in A. by 2 (after Jens and McPherson, 1964)
C.
MOIST soils (change from dry fo value required for single event simulation only):
Soils which have drained but not dried out (i.e. field capacity): divide values from A and
B by 3.
Soils close to saturation: Choose value close to fc value.
Soils which have partially dried out: divide values from A and B by 1.5-2.5.
On well-drained porous soils (e.g. medium to coarse sands), recovery of infiltration capacity is quite rapid and could well be complete in a couple of days.
For heavier soils, the recovery rate is likely to be slower, say 7 to 14 days. The
choice of the value can also be related to the interval between a heavy storm and
wilting of vegetation. The value of α d is then,
α d = 0.02 / D
where
(20-69)
α d = R α = recovery curve decay coefficient, day-1,
and
D = number of days required for the soil to dry out
(recover).
The factor of 0.02 in equation 20-69 assumes 98% recovery of infiltration
capacity (i.e. e-0.02 = 0.98). The value of R may then be calculated from equation 20-60. For example, for α = 4.14 day-1 and drying times of 3, 7 and 14
days, values of R are 1.61 x 10-3, 6.9 x 10-4 and 3.45 x 10-4 respectively.
20.5.3 Green-Ampt Equation
Infiltration During Rainfall Events
The Green-Ampt equation (Green and Ampt, 1911) was developed for infiltration with excess water at the surface at all times. Mein and Larson (1973)
showed how it could be adapted to a steady rainfall input and proposed a way in
which the capillary suction parameter could be determined. More recently Chu
(1978) has shown the applicablity of the equation to the unsteady rainfall situation, using data for a field catchment.
The Mein-Larson formulation is a two-stage model. The first step predicts
the volume of water which will infiltrate before the surface becomes saturated.
From this point onward, infiltration capacity is predicted by the Green-Ampt
equation.
461
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Thus:
For F < Fs:
Fs =
S ⋅ IMD
i
−1
Ks
for i > K s
(20-70)
f =i
and
No calculatio n of Fs for i ≤ K s
For F ≥ Fs:
f = fp
and
S ⋅ IMD ⎞
⎛
f p = K s ⎜1 +
⎟
F ⎠
⎝
where
f
fp
i
F
Fs
(20-71)
=
=
=
=
=
infiltration rate, ft/sec,
infiltration capacity, ft/sec,
rainfall intensity, ft/sec,
cumulative infiltration volume, this event, ft,
cumulative infiltration volume required to
cause surface saturation, ft,
S = average capillary suction at the wetting front,
ft. water,
IMD = initial moisture deficit for this event, ft/ft, and
Ks = saturated hydraulic conductivity of soil, ft/sec.
The first equation shows that the volume of rainfall required to saturate the
surface depends on the current value of the rainfall intensity. Hence, at each time
step for which i > Ks, the value of fs is calculated and compared with the volume
of rainfall already infiltrated for this event. Only if F ≥ Fs does the surface saturate, and further calculations for this condition use the second equation.
When rainfall occurs at an intensity less than or equal to Ks, all rainfall infiltrates and is used only to update the initial moisture deficit, IMD. (The
mechanism for this is discussed in the next subsection.) The cumulative infiltration is not altered for this case of low rainfall intensity (relative to the saturated
hydraulic conductivity, Ks).
The second equation shows that the infiltration capacity after surface saturation depends on the infiltrated volume, which in turn depends on the infiltration
rates in previous time steps. To avoid numerical errors over long time steps, the
integrated form of the Green-Ampt equation is more suitable. That is, fp is replaced by dF/dt and integrated to obtain:
K s (t 2 − t 1 ) = F2 − C ⋅ ln(F2 + C ) − F1 + C ⋅ ln(F1 + C )
(20-72)
462
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
where
C = IMD . S, ft of water,
t = time, sec, and
1,2 = subscripts for start and end of time interval
respectively.
This equation must be solved iteratively for F2, the cumulative infiltration at
the end of the time step. A Newton-Raphson routine is used.
The infiltration volume during time step (t2 - t1) is thus (t2 - t1) x i if the surface does not saturate and (F2 - F1) if saturation has previously occurred and a
sufficient water supply is at the surface. If saturation occurs during the time interval, the infiltration volumes over each stage of the process within the time
steps are calculated and summed. When rainfall ends (or falls below infiltration
capacity) any water ponded on the surface is allowed to infiltrate and added to
the cumulative infiltration volume.
Recovery of Infiltration Capacity (Redistribution)
Evaporation, subsurface drainage, and moisture redistribution between rainfall
events decrease the soil moisture content in the upper soil zone and increase the
infiltration capacity of the soil. The processes involved are complex and depend
on many factors. In SWMM a simple empirical routine is used as outlined below; commonly used units are given in the equations to make the description
easier to understand.
Infiltration is usually dominated by conditions in the uppermost layer of the
soil. The thickness of this layer depends on the soil type; for a sandy soil it
could be several inches, for a heavy clay it could be less. The equation used to
determine the thickness of the layer is:
L = 4 ⋅ Ks
where
(20-73)
L = thickness of layer, in, and
Ks = saturated hydraulic conductivity, in/hr.
Thus for a high Ks of 0.5 in/hr (12.7 mm/hr) the thickness is 2.83 inches
(71.8 mm). For a soil with a low hydraulic conductivity, say Ks = 0.1 in/hr
(2.5 mm/hr), the computed thickness is 1.26 inches (32.1 mm).
A depletion factor is applied to the soil moisture during all time steps for
which there is no infiltration from rainfall or depression storage. This factor is
indirectly related again to the saturated hydraulic conductivity of the soil and is
calculated by:
DF =
where
L
300
DF = depletion factor, hr-1, and
(20-74)
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
463
L = depth of upper zone, in.
Hence, for Ks = 0.5 in/hr (12.7 mm/hr), DF = 0.9% per hour; for Ks = 0.1
in/hr (2.5 mm/hr) DF = 0.4% per hour. The depletion volume (DV) per time step
is then:
DV = DF ⋅ FU max ⋅ Δt
(20-75)
where
FUmax = L · IMDmax = saturated moisture content of the
upper zone, in,
IDMmax = maximum initial moisture deficit, in/in, and
∆t = time step, hr.
The computations used are:
FU = FU − DV
F = F − DV
for FU ≥ 0
for F ≥ 0
(20-76)
(20-77)
where
FU = current moisture content of upper zone, in,
and
F = cumulative infiltration volume for this event,
in.
To use the Green-Ampt infiltration model in continuous SWMM, it is necessary to choose a time interval after which further rainfall will be considered as
pn independent event. This time is computed as:
T=
6
100 ⋅ DF
(20-78)
where
T = time interval for independent event, hr.
For example, when Ks = 0.5 in/hr (12.7 mm/hr) the time between independent events as given in the last equation is 6.4 hr; when Ks = 0.1 in/hr (2.5 mm/hr)
the time is 14.3 hr. After time T has elapsed the variable F is set to zero, ready
for the next event. The moisture remaining in the upper zone of the soil is then
redistributed (diminished) at each time step by the two previous equations in
order to update the current moisture deficit (IMD). The deficit is allowed to increase up to its maximum value (IMDmax, an input parameter) over prolonged
dry periods. The equation used is
IMD =
FU max − FU
for IMD ≤ IMDmax
L
(20-79)
When light rainfall (i ≤ Ks) occurs during the redistribution period, the upper
zone moisture storage, FU, is increased by the infiltrated rainfall volume and
IMD is again updated using the last equation.
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Guidelines for estimating parameter values for the Green-Ampt model are
given elsewhere in this manual. As is also the case for the Horton equation, different soil types can be modelled for different subcatchments.
Program Variables
The infiltration computations are performed in subroutines WSHED and GAMP
in the RUNOFF Module. Correspondence of program variables to those of this
subsection is as follows:
S = SUCT(J)
L = UL(J)
IMDmax = SMDMAX (J)
DF = DF(J)
Ks = HYDCON(J)
i = RI
FUmax = FUMAX(J)
t = time
FU = FU(J)
∆t = DELT
IMD = SMD(J)
DV = DEP
F = F(J)
Fs = FS
20.5.4 Green-Ampt Infiltration Input Data
Although not as well known as the Horton equation, the Green-Ampt equation
(1911) has the advantage of physically based parameters that, in principle, can
be predicted a priori. The Mein-Larson (1973) formulation of the Green-Ampt
equation is a two-stage model. The first step predicts the volume of water, Fs
which will infiltrate before the surface becomes saturated. From this point onward, infiltration capacity, fp, is predicted directly by the Green-Ampt equation.
Thus,
For F < Fs : f = i and Fs =
S u IMD
for i > K s ;
i / Ks − 1
(20-80)
No calculation of Fs for i ≤ Ks.
For F ≥ Fs : f = f p and f p = K s ( 1 +
where
f
fp
i
F
Fs
=
=
=
=
=
S u IMD
)
F
infiltration rate, ft/sec,
infiltration capacity, ft/sec,
rainfall intensity, ft/sec,
cumulative infiltration volume, this event, ft,
cumulative infiltration volume required to
cause surface saturation, ft,
Su = average capillary suction at the wetting front
(SUCT), ft water,
IMD = initial moisture deficit for this event
(SMDMAX), ft/ft, and
(20-81)
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
465
Ks = saturated hydraulic conductivity of soil,
(HYDCON) ft/sec.
Infiltration is thus related to the volume of water infiltrated as well as to the
moisture conditions in the surface soil zone.
Like the Horton equation, the Green-Ampt infiltration equation has three parameters to be specified Su (SUCT), Ks (HYDCON) and IMD (SMDMAX).
Again, estimates based on any available field data should take precedence over
the following guidelines. No default values are provided.
The Soil Survey Interpretation sheets available for most soils from the SCS
show values of permeability (hydraulic conductivity) for the soil, Ks. However
these values are taken from data for disturbed samples and tend to be highly variable. For example, for Conestoga silt loam the values range from 0.63 to 2.0
in/hr (16 to 51 mm/hr). A better guide for the Ks values is as given for parameter fc for the Horton equation; theoretically these parameters (i.e. fc and Ks)
should be equal for the same soil. Note that, in general, the range of Ks values
encountered will be of the order of a few tenths of an inch per hour.
The moisture deficit, IMD, is defined as the fraction difference between soil
porosity and actual moisture content. Sandy soils tend to have lower porosities
than clay soils, but drain to lower moisture contents between storms because the
water is not held so strongly in the soil pores. Consequently, values of IMD for
dry antecedent conditions tend to be higher for sandy soils than for clay soils.
This parameter is the most sensitive of the three parameters for estimates of runoff from pervious areas (Brakensiek and Onstad, 1977); hence, some care should
be taken in determining the best IMD value to use. Table 20-10, derived from
Clapp and Hornberger (1973), gives typical values of IMD for various soil
types.
Table 20-10 Typical Values of IMD (SMDMAX) for Various Soil Types.
Soil Texture
Sand
Sandy Loam
Silt Loam
Loam
Sandy Clay Loam
Clay Loam
Clay
Typical IMD at Soil Wilting Point
0.34
0.33
0.32
0.31
0.26
0.24
0.21
These IMD values would be suitable for input to continuous SWMM; the
soil type selected should correspond to the surface layer for the particular subcatchment. For single event SWMM the values of Table 20-10 would apply only
to very dry antecedent conditions. For moist or wet antecedent conditions lower
values of IMD should be used. When estimating the particular value, remember
that sandy soils drain more quickly than clayey soils, i.e. for the same time since
the previous event, the IMD value for a sandy soil will be closer in value to that
of Table 20-10 than it would be for a clayey soil.
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
The average capillary suction, Su, is perhaps the most difficult parameter to
measure. It can be derived from soil moisture - conductivity data (Mein and
Larsen, 1973) but such data are rare for most soils. Chu (1978) gives average
values of the product of Su.IMD for a range of soils, but these are not based on
measurements. Fortunately the results obtained are not highly sensitive to the
estimate of Su (Brakensiek and Onstad, 1977). The approximate values which
follow result from a survey of the literature (Mein and Larsen, 1973; Brakensiek
and Onstad, 1977; Clapp and Hornberger, 1978; Chu, 1978). Published values
vary considerably and conflict; however, a range of 2 to 15 in (50 to 380 mm)
covers virtually all soil textures.
Table 20-11 Typical values of Su (SUCT) for Various Soil Types.
Soil Texture
Sand
Sandy Loam
Silt Loam
Loam
Clay Loam
Clay
Typical Values for Su (inches)
4
8
12
8
10
7
Table 20-11 summarizes the published values. An excellent local data source
can often be found in Soil Science departments at state universities. Tests are
run on a variety of soils found within the state, including soil moisture versus
soil tension data, with which to derive Su. For example, Carlisle et al. (1981)
provide such data for Florida soils along with information on Ks, bulk density
and other physical and chemical properties.
Generalized Green-Ampt parameters for United States locations are tabulated by Rawls et al. (1983). It is very difficult to give satisfactory estimates of
infiltration equation parameters that will apply to all soils encountered. Whichever infiltration equation is used, you should be prepared to adjust preliminary
estimates in the light of any available data such as infiltrometer tests, measurements of runoff volume, or local experience.
20.5.5 Rainfall Dependent Infiltration-Inflow (RDII or I/I)
Some information in this section is abstracted from the SWMM Q&A archive
(available at www.swmmkb.com), as well as from the input data template file
(RUNOFF.DOC, available at ftp://ftp.engr.orst.edu/pub/swmm/pc/). Please refer to both sources for further information.
Introduction
SWMM contains an I/I routine based on a unit hydrograph approach. Although
intended for combined sewers, there is no reason it cannot work for sanitary systems as well (just do not put any surface runoff into the pipe). Basically, the
rainfall data are run through a pre-processor in which a simple loss is calculated,
to simulate infiltration into the soil. Then the infiltrated water enters pipes as I/I
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
467
based on a combination of three triangular unit hydrographs, to simulate quick,
intermediate, and slow response.
Alternatively, one could use the transport routines to input constant or varying hydrographs. Another approach (the pseudo %I method) used successfully
by a contributor to SWMM Q&A was:
1. Input observed rainfall
2. Calibrate percent imperviousness and/or area to observed hydrographs (typical values should be 2.5% to 10% of the original values,
i.e., only 2.5% to 10% of the separate area, as compared to 100% of
a combined area, is contributing wet weather flow.
3. Run SWMM with calibrated parameters and observed or design
storms to generate I/I response from separate areas.
4. Limitation: one needs calibration rainfall and flow data.
For a fast response of extraneous flows (via direct hydraulic connections, i.e.
inflow through cross-connections), the above pseudo %I method effectively
treats the %Impervious parameter as %Directly-Connected-Combined-Area.
However, for a slow response (i.e. infiltration through cracked or broken pipes
or manholes, offset or open joints) it may be better to input a constant average
infiltration rate directly in the transport routine (or as a line hydrograph - triangular or whatever, depending on the duration and antecedent conditions). Not
only does this slow, infiltration-like response depend on the geometry and hydraulic capacity of defects in the sanitary sewer, but it also depends to a large
extent on the location of the sewer in relation to the groundwater level. However
the design storm to be used to estimate the 5-yr or 10-yr inflow response might
not be appropriate for the infiltration response (since groundwater or saturated
bedding materials are involved). One user witnessed an in-between, not-slow but
not-very-fast response (they called it a weeping-tile response) that was best
modelled using the groundwater routine of SWMM (where some of the water
that has infiltrated through the surface is allowed to be collected by the sewer
system, but they caution to beware of instability). For the pseudo %I method for
an existing collection system, it is best to determine dry weather infiltration during the calibration of the model by utilizing collected flow data. However for a
new sewer system, sanitary flows are best estimated by the development of the
drainage area, i.e. population, industry. Wet weather inflow for an existing system can be accounted for during calibration by adjusting the drainage area of the
separated subcatchments to account for that fraction of the total area that contributes wet weather flow. From experience, one user found that for well
constructed sewers, approximately 5% of the total drainage area produced wet
weather inflow. They reported that the tricky part is rain induced infiltration.
This is the sustained increased flow that often occurs following a rain event due
to percolation of rainfall into the soil followed by infiltration into the collection
system. Even for existing systems with flow monitoring data that user was unable to develop a consistent approach for simulating this behavior. It occurred in
both sanitary and combined sewers. And, finally, a word of caution was given
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
for the above method: the approach of adjusting the drainage area in pseudo %I
method ignores the continuity balance in the total volumes. A user felt that not
knowing where all the flows are going to or coming from can create new problems - one needs to be aware of the total volumes and maintain continuity.
The I/I routine in SWMM
Three data lines define triangular unit hydrographs (UH) to compute subcatchment I/I response from rainfall record. An initial abstraction is subtracted from
rainfall before computing rainfall excess at each time step. The initial abstraction is regenerated during dry weather. Up to five sets of three triangular UHs
may be input. Any subcatchment may use a fraction of flow produced from each
of three UHs selected from any of the up to five sets input.
The triangular hydrographs are defined by:
TP = time to peak [hr] and
K = ratio of recession limb to TP,
so that the time base = TP*(1+K).
Peak flow, Qp, is then calculated in the program so that the volume (area) of the
triangle =1 cfs/ac-in or 1 cms/ha-mm
Three triangles may be used (all starting at the same time) so that one may define a fast response, one a delayed response, and one a lengthy response, if
desired.
The time step is the duration of each of the three UHs.
Useful information from SWMM Q&A
Question 1 Typical inflow and infiltration rates for sanitary sewers:
In Nanaimo (east coast of Vancouver Island), British Columbia we noticed
25 000 to 35 000 l/ha/day (2 500 US gal/ac/day to 3 700 US gal/ac/day this winter. Should we believe our depth recorders?
Answers:
In Edmonton, the design standard for I/I in sewer systems is reportedly 0.28
L/s/ha (24 192 L/ha/day). The flow measurement data over the past 8 years has
only observed peak I/I rates less than 0.28 L/s/ha in the newest developed sewer
systems. That is systems with PVC pipe, weeping tiles connected to sump
pumps discharging to the lot, good lot grading. It is much more typical to observe in older sanitary systems constructed in the 1970s and 1980s I/I rates
reaching as high as 1.0 L/s/ha (86 400 L/ha/day). The Nanaimo numbers are
thus not very surprising, especially as Nanaimo has a much wetter climate than
Edmonton.
Another user recently completed a study of the rainfall derived infiltration
and inflow, and now has a wide range of RDII rates across the city depending on
the age of the system and the type of ground. For their 5-year design storm, the
rates vary from 300 (US gals/ac/day) to 27 000 (US gals/ac/day). The high rates
are from a primarily residential area with low imperviousness but steep slopes
and clay soils. From a simplified calculation (guess), that user estimated that the
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
469
sanitary system during the winter season would likely generate approximately 1
500 (US gals/ac/day) during a typical 1-year storm.
The Nanaimo rates seemed to another user to be very high: for British Columbia, the Rawn criteria recommends to use 11 000 L/ha/day to estimate I/I for
the design of sanitary sewers. Hence, it appears that the I/I rates for Nanaimo
must have been caused by some direct connections. It was not clear from the
initial question whether those I/I rates of 25 000 to 35 000 L/ha/day was wet
weather rates or dry weather rates, or overall mean. Is Nanaimo a separated sanitary sewer system? The Edmonton values are based on flow measurements in
the sanitary system and not the combined system. They did not use I/I measures
in the combined system, but used direct runoff relationships. They saw I/I rates
as high as 1.0 L/s/ha (86 400 L/ha/day) in their sanitary system. They see much
higher runoff rates in the combined system, in some areas greater than 50% of
the rainfall enters the system as runoff.
Question 2: Estimating peak infiltration / inflow (I/I)
Answers:
There are some good publications that discuss I/I in the analysis, design, and
operation stages. These include: Sewer System Infrastructure Analysis and Rehabilitation Handbook, U.S. Environmental Protection Agency, October 1991,
EPA/625/6-91/030. Combined Sewer Overflow Control Manual, U.S. Environmental Protection Agency, September 1993, EPA/625/R-93/007.
The City of Columbus, Ohio requires consultants to use an I/I value of 0.003
CFS per acre of total area tributary to the portion of the collection system under
analysis for all new sanitary sewer designs. This requires the engineer to determine the drainage area tributary to the sewer system. The City also requires
consultants to use an average sanitary flow of 0.000 2 CFS per capita multiplied
by the design density for the area under consideration. Consultants typically use
a design density of 8-12 people per acre.
A research project funded by Water Environment Research Foundation
(WERF) on quantification of Rainfall Derived Infiltration and Inflow (RDII)
was recently completed. The research reviewed a number of methods for developing an RDII hydrograph that can be used to characterize I/I in different
portions of collection systems; generate flow inputs for hydraulic models; and/or
use as basis for planning, analysis, and design. Methods were tested on data sets
from three distinct climactic and topographic regions (Portland, OR; Minneapolis–St.Paul, MN; and Montgomery, AL). The final report is available
exclusively through WERF.
There is a lot of variation in the methods that we have seen applied to estimate the time series. One user described a method developed and successfully
applied with a number of system models over the past 8 years. It is not an empirical approach and relies heavily on good flow metering data from basins sized
20 000 to 40 000 lineal feet for both wet and dry conditions. Average dry weather diurnal curves or time-series are developed for each site. Storm event curves
are then prepared for the specific storms that one has been fortunate enough to
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
measure. By subtraction one can then derive the time-series defect flow for a
specific basin, specific antecedent soil moisture conditions and a specific rainfall
event. This series provides one with the defect volume (area under the curve)
and the shape (time variations of defect flow). By considering these variables
and the actual hyetograph of the rainfall event (be careful here, as you need very
fine data for your catchment) one can derive a relationship for specific stormdefect flow responses. Up to this point most people agree with and use the same
methodology. Where there is still ardent discussion is on how to differentiate
between the fast response and slow response components of the defect flow,
traditionally called inflow and infiltration. Pure inflow (the dominant area of
concern for most capacity models) is considered to be an exact reflection of the
hyetograph. The residual Rainfall induced inflow and infiltration is considered
to be a triangular hydrograph with a specific start, max and end time. This level
of decomposition may not be required or even desired for a lot of applications.
The user used this technique to identify "defect dominance" to direct follow-on
physical inspection techniques (smoke and/or TV). Armed with this information
one can then compare the responses of the system to specific rainfall events.
20.6 Routing
20.6.1 Introduction
Overland Flow
The surface runoff routines form the origin of flow generation within SWMM,
and much of the emphasis in data preparation and user effort is aimed at their
successful execution. To understand better the conversion of rainfall excess
(rainfall or snowmelt less infiltration or evaporation) into runoff (overland
flow), the equations used are here briefly described.
Subcatchments are subdivided into three subareas that simulate impervious
areas, with and without depression (detention) storage, and pervious area (with
depression storage). These are areas A1, A3, and A2 respectively on Figure
20-14.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
471
Figure 20-14 Subcatchment Schematization for Overland Flow Calculations. Flow from each subarea is directly to an inlet (node) or gutter/pipe
(link). Flow from one subarea is not routed over another.
When snowmelt is included, a fourth subarea is added to account for the
presence or absence of snow cover, (see Figure 20-3) but that case will not be
considered further here. The depth of depression storage is an input parameter
for the impervious and pervious areas of each catchment. The impervious area
without depression storage is specified for all subcatchments by parameter
PCTZER (as a percent):
A3 =
PCTZER
⋅ ( A1 + A3)
100
(20-82)
Of course, any subcatchment may be assigned zero depression storage over
its entirety.
Overland flow is generated from each of the three subareas by approximating
them as non-linear reservoirs, as sketched in Figure 20-15 This is a spatially
lumped configuration and really assumes no special shape. However, if the subcatchment width, W, is assumed to represent a true prototype width of overland
flow, then the reservoir will behave as a rectangular catchment, as sketched in
Figure 20-14. Otherwise, the width (and the slope and roughness) may be considered calibration parameters and used to adjust predicted to measured
hydrographs.
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Figure 20-15 Non-linear Reservoir Model of Subcatchment.
The non-linear reservoir is established by coupling the continuity equation
with Manning's equation. Continuity may be written for a subarea as:
dV
dd
=A
= A ⋅ i * −Q
dt
dt
(20-83)
A · d = volume of water on the subarea, ft3,
water depth, ft,
time, sec,
surface area of subcatchment, ft2,
rainfall excess = rainfall/snowmelt intensity
minus evaporation/ infiltration rate, ft/sec,
and
Q = outflow rate, cfs.
The outflow is generated using Manning's equation:
where
V
d
t
A
i*
=
=
=
=
=
Q =W ⋅
1.49
( d − d p )5 / 3 S 1 / 2
n
(20-84)
where
W = subcatchment width, ft,
n = Manning's roughness coefficient,
dp = depth of depression storage, ft, and
S = subcatchment slope, ft/ft.
These two equations may be combined into one non-linear differential equation that may be solved for one unknown, the depth, d. This produces the
non- linear reservoir equation:
dd
1.49 ⋅ W
= i* −
( d − d p )5 / 3 S 1 / 2 = i* + WCON ⋅ ( d − d p )5 / 3
dt
A⋅n
where
(20-85)
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
WCON =
1.49 ⋅ W ⋅ S 1 / 2
A⋅n
(20-86)
Note the grouping of width, slope and roughness into only one parameter.
The equation dd/dt is solved at each time step by means of a simple finite
difference scheme. For this purpose, the net inflow and outflow on the right
hand side (RHS) of the equation must be averaged over the time step. The rainfall excess, i*, is given in the program as a time step average. The average
outflow is approximated by computing it using the average between the old and
new depths. That is, letting subscripts 1 and 2 denote the beginning and the end
of a time step, respectively, the equation is approximated by:
5
d 2 − d1
1
⎡
⎤3
= i* + WCON ⋅ ⎢d 1 + (d 2 − d 1 ) − d p ⎥
Δt
2
⎣
⎦
(20-87)
where
∆t = time step, sec.
This equation is then solved for d2 using a Newton-Raphson iteration.
Given d2, the instantaneous outflow at the end of a time step is computed using the Manning equation. The outflow is used in runoff quality calculations and
is the flow value that is input to inlets (nodes). The instantaneous outflow at a
given time is also the flow value transferred to subsequent SWMM modules.
Although the solution of the finite difference equation is straightforward and
simple (and in fact may be performed on programmable hand calculators), some
peculiarities exist in the way the parameters for individual subareas (A1, A2, A3
in Figure 20-14) are specified. In particular, only two values of WCON are
computed, one for the pervious and one for the total impervious subareas. Thus,
WCON is the same for calculating depths on subareas A1 ad A3 and is computed using the total impervious area, A1 plus A3, in the denominator. However,
the instantaneous flow is computed using the individual area of each subarea
(e.g. Al or A3). The net effect for subareas A1 and A3 is approximately to reduce the subcatchment width by the ratio A1/(A1 + A3) or A3/(A1 + A3) as
implied in Figure 20-14. Numerical tests of this scheme versus one that uses the
individual areas (and proportional widths) in parameter WCON indicate only
about a half percent difference between the two methods. Hence, it should be
satisfactory.
Prior to performing these calculations, a check is made to see if losses are
greater than the rainfall depth plus ponded water. If so, the losses (evaporation
plus infiltration) absorb all water and outflow is zero. Similarly, if losses alone
would be sufficient to lower the depth below the depression storage, the new
depth is computed on this basis only and the outflow is zero.
The computational scheme has proven quite stable. The only instance for
which non-convergence problems arise (or an attempt to compute a negative
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
depth) is when the subarea values are very small (e.g. a few square feet) coupled
with a large time step (e.g. ten minutes). Should a non-convergence message be
printed, the problem may usually be cured by increasing the appropriate area or
decreasing the time step.
Variable Time Step
SWMM hydrology has three time steps: a wet time step (WET), the transitional
time step(s) between wet and dry (WETDRY), and the dry (DRY) time step.
WET will normally be less than or equal to the rainfall interval entered. It can be
longer, but information is lost by averaging the rainfall over a longer time period. A wet time step is a time step with precipitation occurring on any
subcatchment. A transitional time step has no precipitation input on any subcatchment, but the subcatchment(s) still have water remaining in surface storage.
A dry time step has no precipitation input or surface storage. However, it can
have groundwater flow. The model is considered either globally wet, globally
transitional, or globally dry.
The time step should be smaller for periods of rapid change, i.e., during rainfall, and longer during periods of slower change (i.e. during transitional and dry
time steps). SWMM can use any time step from 1 second to 1 year. The solution
technique is stable and convergent for any length time step.
Typically the WET time step should be a fraction of the rainfall interval.
Five minute rainfall should have wet time steps of 1, 2.5 or 5.0 minutes for example. The rainfall intensity is constant over the wet time step when WET is a
fraction of the rainfall interval. A smaller wet time step would be desirable when
the subcatchment is small and the time of concentration is a fraction of the rainfall interval. When using one-hour rainfall from the NWS, wet time steps of 10
minutes, 15 minutes etc. can be used by the model.
The overland flow routing technique loses water through infiltration, evaporation, and surface water outflow during the transition periods. A subcatchment's
surface storage and surface flow always decrease during the transition from a
wet condition to a dry condition. A smooth curve or straight line is a good model
for the shape of the hydrograph. The transport routines usually have small time
steps and use linear or parabolic interpolation for input hydrographs with longer
time steps. The transition time step, WETDRY, can be substantially longer than
WET and generate a good overland flow hydrograph. For example, a WET of 5
minutes can be coupled with a WETDRY of 15 minutes or 30 minutes. When
using hourly rainfall input, a WET of 15 minutes can be coupled to a WETDRY
of 2 hours or 3 hours.
The dry time step should be one day to a week. The dry time step is used to
update the infiltration parameters, generate groundwater flow, and produce a
time step value for the interface file. The dry time step should be day(s) in wet
climates and days or week(s) in very dry climates. A synoptic analysis will be of
use in selecting the appropriate dry time step. Examine the average storm
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
475
interevent duration in the storm summary table. The average storm interevent
duration ranges from half a week to months depending on station location.
The model can achieve substantial time savings with judicious usage of
WET, DRY, and WETDRY for both short and long simulations. As an example
consider the time step saving using a WET of 15 minutes, a WETDRY of 2
hours, and a DRY of 1 day versus using a single time step of 1 hour for a year.
Using Florida rainfall as input (average annual rainfall between 50 and 60 inches) gives 300 wet hours per year, flow for approximately 60 days per year, and
205 dry days per year. This translates to 1975 time steps. A constant hourly time
step for one year requires 8 760 time steps. This is greater than a 400% savings
in time with a better representation of the flow hydrograph due to the 15 minute
wet time step.
Extrapolation Technique
The accuracy of the solution technique using variable time steps is enhanced
(aided) by a numerical technique called Richardson extrapolation (Press et al.,
1986). Richardson extrapolation is also called Richardson’s deferred approach to
the limit. The extrapolated value is the solution that would be obtained if an infinitely small time step was used in watershed, channel/pipe (link) or infiltration
routing.
The concept of extrapolation to the limit may be more familiar to the reader
in connection with Romberg integration. Romberg integration repeatedly calls a
trapezoidal rule integration subroutine in the sequence 1, 2, 4, 8, 16 panels etc.
to extrapolate a more accurate solution than that obtained by the trapezoidal rule
alone.
SWMM uses the same concept to extrapolate the watershed depth at the end
of a time step. SWMM uses the iterative techniques described earlier in this appendix to solve for the infiltration volume and watershed depth at the end of a
time step. The WET, DRY, and WETDRY time steps are broken up into smaller
and smaller steps using the relationships: WET/n, DRY/n, and WETDRY/n
where n is the number of subintervals used by WSHED. The sequence of subintervals n used by WSHED is
n = 1, 2, 4, 6, 8, 12, 24, 32, 48, 64
Experience has shown that time steps smaller than 5 minutes do not have to
be broken into subintervals. The integrated depth or infiltration volume for one
subinterval is almost equal to the extrapolated depth or infiltration volume obtained from using more subintervals. For time steps longer than 5 minutes the
extrapolated answer obtained from using one and two subintervals usually has a
small estimated error. The exceptions are due to large rainfall intensities over
long time periods (i.e., 15 minute to 1 hour rainfall). It may be necessary for the
time step to be broken up into more than 32 subintervals during these conditions.
The extrapolation to an infinitely small time step is illustrated in Figure 20-16. In this figure, note that a large interval is spanned by different
sequences of finer and finer substeps. Their results are extrapolated to an answer
476
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
that corresponds to an infinitely small time step. SWMM uses a NewtonRaphson iteration solution for the y values at each time step, and a rational function extrapoloation to calculate the extrapolated y value.
Figure 20-16 Richardson Extrapolation as used in the RUNOFF Block
(adapted from Press et all, 1986).
A rational function, which is an analytical function dependent on the step
size h, is fit to the various estimates of the integrated watershed depth or infiltration volume. The rational function (a function with polynomial numerator and
denominator) is then evaluated at h = 0. The evaluated depth or volume is the
extrapolated value.
SWMM treats overland flow, infiltration, and groundwater flow as coupled
processes. The extrapolated value is actually a vector of estimates.
20.6.2 Surface Quantity Data
Subcatchment Aggregation and Lumping
It is desirable to represent the total catchment by as few subcatchments as possible, consistent with the needs for hydraulic detail within the catchment. The
number of subcatchments needed is a function of the amount of hydraulic detail
(e.g. backwater, surcharging, routing, storage) that must be modeled. In addition, enough detail must be simulated to allow non-point source controls to be
evaluated (e.g. detention, street sweeping). Finally multiple subcatchments are
the only means by which a moving (kinematic) storm may be simulated. Coupled spatial and temporal variations in rainfall can significantly alter predicted
hydrographs (Yen and Chow, 1968; Surkan, 1974; James and Drake, 1980;
James and Shtifter, 1981).
Clearly, the required volume of input data (and personal time) decreases as
the number of subcatchments decreases. How then, can subcatchments be aggregated or lumped to provide hydrographs and pollutographs that are
equivalent to more detailed simulations?
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
477
A study of this question is contained in the Canadian SWMM report (Proctor
and Redfern and J.F. MacLaren, 1976a) in which the effect of lumping is compared on real and hypothetical catchments. Similar work has been performed
independently by Smith (1975). In both studies it is shown that a single equivalent lumped catchment can be formulated by proper adjustment of the
subcatchment width.
In SWMM, simulation of the drainage network (i.e. conduits (links) and
channels (links)) adds storage to the system and thus attenuates and somewhat
delays the hydrograph peaks. When the drainage network is removed from the
simulation, subcatchment runoff feeds instantaneously into inlets (nodes), with
consequent higher and earlier hydrograph peaks. The key to aggregation of subcatchments is thus the replacement of the lost storage. This is best accomplished
through variation of the subcatchment width, although the same effect could be
achieved through variation of the slope or roughness (see discussion of equation
20-88). However, it is assumed that reasonable average values of the latter two
parameters for the total catchment may be obtained by weighing individual subcatchment values by their respective areas. (For the roughness an area-weighted
harmonic mean may be used, although it is probably an unnecessary refinement). Hence, the sub-catchment width is a more logical parameter to be
adjusted.
Reducing subcatchment width increases storage on the subcatchment. Hence,
as subcatchments are aggregated and drainage network storage lost, the total
catchments width (i.e. the sum of the subcatchment widths, must be reduced
accordingly). Experience indicates (Smith, 1975; Proctor and Redfern and J.F.
MacLaren, 1976a) that good results can be obtained with no channel/conduit
(link) network. However, the Canadian study (Proctor and Redfern and J.F.
MacLaren, 1976a) does illustrate the routing effect of an equivalent pipe. Note
that if the storm duration is long compared to the catchment time of concentration, and if the rainfall intensity is constant, the peak flows obtained for either a
lumped or detailed simulation will be about the same, since equilibrium outflow
must ultimately result.
Several examples of lumping using real rainfall data on real catchments are
shown by Proctor and Redfern and James F. MacLaren (1976a) and Smith
(1975). An instructive example for the 2 330 ac (943 ha) West Toronto area is
taken from the former reference.
A SWMM simulation using 45 subcatchments and including the drainage
network is compared with three hydrology-only simulations with no drainage
network. The best agreement, in terms of matching of peak flows, between the
detailed and lumped simulations occurred for a single subcatchment width of 60
000 ft (18 000 m) which is about 1.7 times the length of the main trunk conduit
(link) in the actual system. Even if a factor of two had been used (i.e. a width of
70 600 ft or 21 500 m) as a first guess, agreement would not be bad. The timing
of the peaks for the single subcatchment representation is somewhat early, but
478
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
adequate for most purposes. Recall that it is difficult to change the timing of
subcatchment hydrograph peaks by changing only the width.
It is assumed that when subcatchments are aggregated, other parameters required are simply areally weighted. When this is done, very little difference in
runoff volume occurs between the aggregate and detailed representations. Differences that do result are usually from water that remains in storage and has not
yet drained off of the lumped catchment, or from very slightly increased infiltration on the lumped catchment, again due to the longer presence of standing
water on pervious areas (because of the reduced width).
To summarize, many subcatchments may be aggregated into a single lumped
or equivalent subcatchment by using areally weighted subcatchment parameters
and by adjustment of the subcatchment width. The lumped subcatchment width
should be approximately twice the length of the main drainage channel (e.g. the
trunk sewer) through the catchment in order to match hydrograph peaks. The
effect on runoff volume should be minimal.
SWMM quality predictions are affected by aggregation of subcatchments to
the extent that hydrographs and surface loadings are changed. When areal
weighted averages of the latter are used for a lumped catchment, total storm
loads are essentially the same as for a detailed simulation. Pollutographs of concentration versus time then vary only because of hydrograph variations.
20.6.3 Subcatchment Surface Data
Subcatchment Schematization
Many hydrologic models account for spatial variations by subdividing the overall catchment into subcatchments, predicting runoff from the subcatchments on
the basis of their individual averaged properties, and combining their outflows
using a flow routing scheme. This procedure is followed in SWMM, in which
subcatchments are idealized mathematically as rectangular, spatially-lumped,
non-linear reservoirs, and their outflows are routed to the subcatchment outlet.
Each subcatchment is schematized as in Figure 20-3, in which three or four
subareas (depending on whether snowmelt is simulated) are used to represent
different surface properties as enumerated in Table 20-2 (in section 20.3.3). The
slope of the idealized subcatchment is in the direction perpendicular to the
width. Flow from each subarea moves directly to an outlet, which often is a gutter or pipe inlet (node) and may pass over another subarea. Thus, it is possible to
route runoff from roofs over lawn surfaces, for instance.
The width of the pervious subarea, A2, is the entire subcatchment width,
whereas the widths of the impervious subareas, A1, A3, A4, are in proportion to
the ratio of their area to the total impervious area, as implied in Figure 20-3. If
desired, any subcatchment may consist entirely of any one (or more) types of
subareas.
Of course, real subcatchments seldom exhibit the uniform rectangular geometries shown in Figure 20-3. In terms of the flow routing, all geometrical
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
479
properties are merely parameters (as explained below) and no inherent shape can
be assumed in the non-linear reservoir technique. However, in terms of parameter selection, the conceptual geometry of Figure 20-3 is useful because it aids in
explaining the flow routing.
Routing and Time Step Considerations
The routing is performed separately for each of the three of four subareas of the
subcatchment. Convergence problems are rarely encountered during subcatchment routing because total subcatchment volumes (area times depth) are usually
large compared to outflow volumes.
Parameter selection is aided with reference to Figure 20-15 in which the subcatchment reservoir is shown in relation to inflows and outflows (or losses). The
outflow to channel or pipes (links) and inlets (nodes) is computed as the product
of velocity (from Manning's equation based on the difference between total
depth and depression storage), depth and width,
Q =W
1.49
(d ! d p )5/3 S1/2
n
(20-88)
where
Q = subcatchment (or subarea) outflow, cfs (cms),
W = subcatchment width, ft (m),
n = Manning's roughness coefficient,
d = water depth, ft (m),
dp = depth of depression (retention) storage, ft (m),
S = slope, ft/ft (m/m).
When combined with the continuity equation and divided by the surface area, a new routing parameter is defined for the pervious and total impervious
subcatchment areas and used in all subsequent calculations:
WCON = !
where
1.49W 1/2
S
A"n
(20-89)
WCON = routing parameter, ft-s (m-s) units, and
A = surface area of pervious or total impervious
subarea, ft2 (m2)
Note that the width, slope and roughness parameters are combined into one
parameter. Thus, equivalent changes may be caused by appropriate alteration of
any of the three parameters. Note also that the width and slope are the same for
both pervious and impervious areas. Manning’s roughness and relative area are
the only parameters available to the modeler to characterize the relative contributions of pervious and impervious areas to the outlet hydrograph. (However,
see further comments below on the subcatchment width.) Flows are instantaneous values at the end of a time step.
480
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Subcatchment Width
If overland flow is visualized (Figure 20-3) as running down-slope off an idealized, rectangular catchment, then the width of the subcatchment is the physical
width of overland flow. This may be further seen when the lateral flow per unit
width, qL, is computed and multiplied by the width to obtain the total inflow into
the channel. (SWMM channel/pipes can only receive a concentrated inflow,
however, and do not receive a distributed inflow in a specific fashion.) .
Since real subcatchments will not be rectangular with properties of symmetry
and uniformity, it is necessary to adopt other procedures to obtain the width for
more general cases. This is of special importance, because if the slope and
roughness are fixed (see equation 20-89), the width can be used to alter the hydrograph shape.
For example, consider the five different subcatchment shapes shown on Figure 20-19.
Figure 20-19 Different Subcatchment Shapes to Illustrate Effect of Subcatchment Width.
Catchment hydraulic properties, routing parameters and time of concentration are also given. The latter is calculated using the kinematic wave formulation
Eagleson, 1970, p. 340),
1/m
# L &
tc = %
*m"1 (
$ a !i
'
where
tc = time of concentration, s,
(20-90)
481
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
L = subcatchment length ,ft (m),
i* = rainfall excess (rainfall minus losses), ft/s
(m/s), and
a,m = kinematic wave parameters.
The kinematic wave formulation assumes that the runoff per unit width (velocity times depth) from the subcatchment is
qL = a d m
(20-91)
qL = flow per unit width, ft2/s (m2/s), and
d = depth of flow, ft (m).
Parameters a and m depend upon the uniform flow equation used for normal
flow. For Manning's equation,
where
a = (1.49 / n)! S1/2
(20-92)
and
m = 5/3
(20-93)
Note that the units of a depend upon the value of m, and for Manning’s equation above, feet-second units are used. The subcatchment length may be
computed for the assumed rectangular shape simply by dividing the area by the
width.
Finally, note the dependence of time of concentration upon the rainfall intensity. As i* increases, tc decreases. The calculation using equation 20-90 is
consistent with the definition of tc given earlier: tc is the time to equilibrium, at
which inflow equals outflow (for an impervious catchment). Equivalently, tc is
the time taken for the most remote portion of the catchment to contribute to flow
at the outlet (node), which is the time taken by a wave (not a parcel of water) to
travel from the remote point to the outlet (node).
Figure 20-20 Subcatchment Hydrographs for Different Shapes of Figure
20-19.
482
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Outflow hydrographs for continuous rainfall and for rainfall of duration 20
min are shown on Figure 20-20. These were computed by the RUNOFF Module
non- linear reservoir equations using a time step of 5 min.
Clearly, as the subcatchment width is narrowed (i.e. the outlet (node) is constricted), the time to equilibrium increases. Thus, it is achieved quite rapidly for
cases A and B and more slowly for cases C, D and E. The kinematic wave computation of tc (Figure 20-19) is not particularly accurate for the non-linear
reservoirs for which the asymptotic value of equilibrium outflow is approached
exponentially. However, it may be used for guidance.
Two routing effects may be observed. A storage effect is very noticeable, especially when comparing hydrographs A and E for a duration of 20 min. The
subcatchment thus behaves in the familiar manner of a reservoir. For case E, the
outflow is constricted (narrow); hence, for the same amount of inflow (rainfall)
more water is stored and less released. For case A, on the other hand, water is
released rapidly and little is stored. Thus case A has both the fastest rising and
recession limbs of the hydrographs.
A shape effect is also evident. Theoretically, all the hydrographs peak simultaneously (at the cessation of rainfall). However, a large width (e.g. case A) will
cause equilibrium outflow to be achieved rapidly, producing a flat-topped hydrograph for the remainder of the (constant) rainfall. Thus, for a catchment
schematized with several subcatchments and subject to variable rainfall, increasing the widths tends to cause peak flows to occur sooner. In general, however,
shifting hydrograph peaks in time is difficult to achieve through adjustment of
the flow routing parameters. The time distribution of runoff is far and away the
most sensitive to the time distribution of rainfall. Further discussion of the effect
of subcatchment width on hydro-graph shapes may be found under Subcatchment Aggregation and Lumping.
What is the best estimate of subcatchment width? Most real subcatchments
will be irregular in shape and have a drainage channel which is off center. This
is especially true of rural or undeveloped catchments. A good estimate for the
width can be obtained by first determining a representative (e.g. the maximum)
length of overland flow and dividing the area by this length.
Subcatchment Area
In principle, the catchment and subcatchment area can be defined by constructing drainage divides on topographic maps. In practice, this may or may not be
easy because of groundwater and the presence of unknown inflows and outflows. This may be most noticeably brought to the modeler's attention when the
measured runoff volume exceeds the measured rainfall volume, if the latter is
correct. Actually storm rainfall is seldom accurately measured over all subcatchments.
From the modeling standpoint, there are no upper or lower bounds on subcatchment area (other than to avoid convergence problems, as discussed earlier).
Subcatchments are usually chosen to coincide with different land uses, with
483
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
drainage divides, and to ease parameter estimation (i.e. homogeneous slopes,
soils) Further guidance is given later under subcatchment aggregation.
Imperviousness
The percent imperviousness of a subcatchment is another parameter that can, in
principle, be measured accurately from aerial photos or land use maps. In practice, such work tends to be tedious, and it is common to make careful
measurements for only a few representative areas and extrapolate to the rest.
Care must be taken to ensure that impervious areas are hydraulically (directly) connected to the drainage system. For instance, if rooftops drain onto
adjacent pervious areas, they should not be treated as a hydraulically effective
impervious area. Such areas are noneffective impervious areas (Doyle and Miller, 1980). On the other hand, if a driveway drains to a street and thence to a
stormwater inlet, the driveway would be considered to be directly connected.
Rooftops with downspouts connected directly to a sewer are definitely hydraulically connected.
Should rooftops be treated as pervious, the real surrounding pervious area is
subject to more incoming water than rainfall alone and thus might produce runoff sooner than if rainfall alone were considered. In the unlikely event that this
effect is important (a judgment based on infiltration parameters) it could be
modeled by altering the infiltration parameters or by treating such pervious areas
as separate subcatchments, and increasing their rainfall by the ratio of roof area
plus pervious to pervious alone. Since the roof areas would then not be simulated, continuity would be maintained.
Another method of estimating the effective impervious area given measured
data is to plot the runoff (in. or mm) vs. rainfall (in. or mm) for small storms.
The slope of the regression line is a good estimate of the effective impervious
area (Doyle and Miller, 1980). Further information on the concept of hydraulically connected (or hydraulically effective) impervious areas is contained in
USGS studies (Jennings and Doyle, 1978) and documentation of the ILLUDAS
model (Terstriep and Stall, 1974).
For continuous simulation in which very large subcatchments are being used,
even spot calculations of imperviousness may be impractical. Instead, regression
formulations have been developed in several studies (Graham et al., 1974;
Stankowski, 1974; Manning et al., 1977; Sullivan et al., 1978). These typically
relate percent imperviousness to population density, and are compared in Figure
20-21 (Heaney et al., 1977). The New Jersey equation (Stankowski, 1974) is
perhaps the most representative:
I = 9.6PDd(0.53!0.0391 log10 PDd )
where
(20-94)
I =
WW(3) = imperviousness, percent, and
PDd = population density in developed portion of the
urbanized area, person per acre (Ha).
484
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
The developed portion excludes large segments of undeveloped (i.e. natural
or agricultural) lands that may lie within the area being simulated. Also note that
the relationships shown in Figure 20-21 were all developed for large (city-wide)
urban areas as a whole. Their use may be tenuous for smaller sub- basins.
Figure 20-21 Percent Imperviousness vs Developed Population Density for
Large Urban Areas. (After Heaney et al., 1977, p. 105).
Slope
The subcatchment slope should reflect the average along the pathway of overland flow to inlet (node) locations. For a simple geometry (e.g. Figure 20-19) the
calculation is simply the elevation difference divided by the length of flow. For
more complex geometries, several overland flow pathways may be delineated,
their slopes determined, and a weighted slope computed using a path-length
weighted average. Such a procedure is described by DiGiano et al., 1977, pp.
101-102). Alternatively it may be sufficient to simulate what you consider to be
the hydrologically dominant slope for the conditions being simulated. Choose
the appropriate overland flow length, slope, and roughness for this equivalent
plane.
Manning's Roughness Coefficient, n
Values of Manning's roughness coefficient, n, are not as well known for overland flow as for channel flow because of the considerable variability in ground
cover for the former, transitions between laminar and turbulent flow, very small
depths, etc. Most studies indicate that for a given surface cover, n varies inversely in proportion to depth, discharge or Reynold's number. Such studies may be
485
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
consulted for guidance (e.g. Petryk and Bosmajian, 1975; Chen, 1976; Christensen, 1976; Graf and Chun, 1976; Turner et al., 1978; Emmett, 1978), or
generalized values used (e.g. Chow, 1959; Crawford and Linsley, 1966; Huggins
and Burney, 1982; Engman, 1986). Roughness values used in the Stanford Watershed Model (Crawford and Linsley, 1966) are given in Table 20-13 along
with more recent values from Engman (1986). Engman also provides values for
other agricultural land uses and a good literature review.
Table 20-13 Estimates of Manning's Roughness Coefficients for Overland
Flow
Source
Crawford and Linsley (1966)a
Engman (1986)b
a
Ground Cover
Smooth Asphalt
Asphalt of concrete paving
Packed clay
Light turf
Dense turf
Dense shrubbery and forest litter
Concrete or asphalt
Bare sand
Graveled surface
Bare clay-loam (eroded)
Range (natural)
Bluegrass sod
Short grass prairie
Bermuda grass
n
0.012
0.014
0.03
0.20
0.35
0.4
0.011
0.01
0.02
0.02
0.13
0.45
0.15
0.41
Range
0.01-0.013
0.01-0.016
0.012-0.03
0.012-0.033
0.01-0.32
0.39-0.63
0.10-0.20
0.30-0.48
Obtained by calibration of Stanford Watershed Model.
Computed by Engman (1986) by kinematic wave and storage analysis of measured rainfall-runoff data.
b
Depression Storage
Depression (retention) storage is a volume that must be filled prior to the occurrence of runoff on both pervious and impervious areas (see Figure 20-15); a
good discussion is presented by Viessman et al. (1977). It represents a loss or
initial abstraction caused by such phenomena as surface ponding, surface wetting, interception and evaporation. In some models, depression storage also
includes infiltration in pervious areas. In SWMM, water stored as depression
storage on pervious areas is subject to infiltration (and evaporation), so that it is
continuously and rapidly replenished. Water stored in depression storage on impervious areas is depleted only by evaporation. Hence, replenishment typically
takes much longer.
As described earlier (e.g. Table 20-2), a percentage PCTZER of the impervious area is assigned zero depression storage in order to promote immediate
runoff.
Depression storage may be derived from rainfall runoff data for impervious
areas by plotting runoff volume (depth) as the ordinate against rainfall volume
as the abscissa for several storms. The rainfall intercept at zero runoff is the depression storage. Data obtained in this manner from 18 urban European
catchments (Falk and Niemczynowicz, 1978, Kidd, 1978a, Van den Berg, 1978)
are summarized in Table 20-14. The very small catchments (e.g. less than 1 ac
486
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
or 0.40 ha) were primarily roadway tributaries to stormwater inlets and catchbasins.
Table 20-14 Recent European Depression Storage Data (Kidd, 1978b)
Catchment Name
Country
Area
(ac)
Imperviousness (%)
Slope
(%)
Depression
Storage (in)
No. of
Events
4.94
Paved
Area
(ac)
2.17
Lelystad Housing
Area
Lelystad Parking
Lot
Ennerdale Two
Ennerdale Three
Bishopdale Two
Hyde Green One
Hyde Green Two
School Close One
School Close Two
Lund 1:75
Klostergarden
1:76
Klostergarden
1:77
Klostergarden
2:76
Klostergarden
2:77
Klostergarden
3:76
Klostergarden
3:77
Klostergarden
4:76
Klostergarden
4:77
Netherlands
44
0.5
0.059
10
Netherlands
1.73
1.73
100
0.5
0.035
10
U.K.
U.K.
U.K.
U.K.
U.K.
U.K.
U.K.
Sweden
Sweden
0.088
0.022
0.146
0.120
0.209
0.133
0.177
0.072
0.081
0.079
0.022
0.111
0.085
0.103
0.070
0.097
0.072
0.081
89
100
76
71
49
62
55
100
100
3.1
3.0
2.4
2.2
2.0
1.7
0.9
2.1
0.9
0.020
0.016
0.018
0.019
0.020
0.009
0.026
0.005
0.041
6
9
11
7
8
11
11
11
11
Sweden
0.083
0.083
100
2.3
0.020
13
Sweden
0.020
0.020
100
3.3
0.019
11
Sweden
0.019
0.019
100
4.1
0.013
12
Sweden
0.076
0.076
100
3.1
0.022
11
Sweden
0.102
0.102
100
2.3
0.022
13
Sweden
0.068
0.068
100
1.6
0.020
10
Sweden
0.069
0.069
100
1.9
0.022
13
The data were aggregated and a regression of depression storage versus slope
performed as part of a workshop (Kidd, 1978b). The data are plotted in Figure
20-22 along with the relationship developed by the workshop,
d p = 0.0303! S "0.49 ,
where
(r = "0.85)
(20-95)
dp = WSTORE = depression storage, in (mm), and
S = WSLOPE = catchment slope, percent.
Viessman et al. (1977, p. 69) illustrate a similar but linear plot, in which depression storage values for four small impervious areas near Baltimore,
Maryland range from 0.06 in. to 0.11 in. (1.5 mm to 2.8 mm), considerably
higher than the European values shown in Figure 20-22. The reason for this discrepancy is not known, but it appears that the recent European data may be
better suited to provide depression storage estimates, mainly because of their
extent.
Separate values of depression storage for pervious and impervious areas are
required for input. Representative values for the latter can probably be obtained
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
487
from the European data just discussed. Pervious area measurements are lacking;
most reported values are derived from successful simulation of measured runoff
hydrographs. Although pervious area values are expected to exceed those for
impervious areas, it must be remembered that the infiltration loss, often included
as an initial abstraction in simpler models, is computed explicitly in SWMM.
Hence, pervious area depression storage might best be represented as an interception loss, based on the type of surface vegetation. Many interception
estimates are available for natural and agricultural areas (Viessman et al., 1977,
Linsley et al., 1949). For grassed urban surfaces a value of 0.10 in (2.5 mm) may
be appropriate.
Figure 20-22 Depression Storage vs. Catchment Slope (after Kidd, 1978b).
(See Table 20-30 for catchment data.)
As mentioned earlier, several studies have determined depression storage
values in order to achieve successful modeling results. For instance, Hicks
(1944) in Los Angeles used values of 0.20, 0.15 and 0.10 in (5.1, 3.8, 2.5 mm)
for sand, loam and clay soils, respectively, in the urban area. Tholin and Keifer
(1960) used values of 0.25 and 0.0625 in (6.4 and 1.6 mm) for pervious and impervious areas, respectively, for their Chicago hydrograph method. Brater
(1968) found a value of 0.2 in (5.1 mm) for three basins in metropolitan Detroit.
488
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Miller and Viessman (1972) give an initial abstraction (depression storage) of
between 0.10 and 0.15 in (2.5 and 3.8 mm) for four composite urban catchments.
In SWMM, depression storage may be treated as a calibration parameter,
particularly to adjust runoff volumes. If so, extensive preliminary work to obtain
an accurate a priori value may be pointless since the value will be changed during calibration anyway.
The invert slope is usually given on drainage maps or may easily be calculated from invert elevations and conduit lengths. Tables of Manning's roughness
coefficient are given in many references; see for instance Chow (1959) or
ASCE-WPCF (1969).
20.7 Groundwater
20.7.1 Introduction
Because SWMM was originally developed to simulate combined sewer overflows in urban catchments, infiltrated water was originally considered to be
irrelevant. Since its development, however, SWMM has been used on areas
ranging from highly urban to relatively undeveloped. Many of the undeveloped
and even some of the developed areas, especially in areas like south Florida, are
very flat with high water tables, and their primary drainage pathway is through
the surficial groundwater aquifer and the unsaturated zone above it, rather than
by overland flow. In these areas a storm will cause a rise in the water table and
subsequent slow release of groundwater back to the receiving water (Capece et
al., 1984). For this case,the infiltrated water is highly significant. By assuming
that the infiltration is lost from the system, an important part of the
high-water-table system is not being properly described (Gagliardo, 1986).
It is known that groundwater discharge accounts for the time-delayed recession curve that is prevalent in certain watersheds (Fetter, 1980). This process has
not, however, been satisfactorily modeled by surface runoff methods alone. By
modifying infiltration parameters to account for subsurface storage, attempts
have been made to overcome the fact that SWMM assumes infiltration is lost
from the system (Downs et al., 1986). Although the modeled and measured peak
flows matched well, the volumes did not match well, and the values of the infiltration parameters were unrealistic. Some research on the nature of the soil
storage capacity has been done in South Florida (SFWMD, 1984). However, it
was directed towards determining an initial storage capacity for the start of a
storm. There remains no standard, widely-used method for combining the
groundwater discharge hydrograph with the surface runoff hydrograph and determining when the water table will rise to the surface. For instance, HSPF
(Johansen et al., 1980) performs extensive subsurface moisture accounting and
works well during average conditions. However, the model never permits the
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
489
soil to become saturated so that no more infiltration is permitted, limiting its
usefulness during times of surface saturation and flooding. Another difficulty
with HSPF occurs during drought conditions, since there is no threshold saturated zone water storage (corresponding to the bottom of a stream channel) below
which no saturated zone outflow will occur. These difficulties have limited
HSPF usefulness for application to extreme hydrologic conditions in Florida
(Heaney et al., 1986).
In order to incorporate subsurface processes into the simulation of a watershed and overcome previously mentioned shortcomings, SWMM has been
equipped with a simple groundwater subroutine. The remainder of this section
describes the theory, use, and some limitations of the subroutine.
20.7.2 Theory
Introduction
An effort was made to utilize existing theoretical formulations for as many processes as possible. The purpose was to maintain semblance to the real world
while enabling determination of parameter values that have meaning to the soil
scientist. Also, in the following discussion the term flow will refer to water that
is passed on to another part of the system, and the term loss will refer to water
that is passed out of the system. In addition, in the groundwater subroutines,
flows and losses have internal units of velocity (flow per unit area).
The groundwater subroutine simulates two zones: an upper (unsaturated)
zone and a lower (saturated) zone. This configuration is similar to Dawdy and
O’Donnell (1965) for the USGS. The flow from the unsaturated to the saturated
zone is controlled by a percolation equation for which parameters may either be
estimated or calibrated, depending on the availability of the necessary soil data.
Upper zone evapotranspiration is the only loss from the unsaturated zone. The
only inflow to groundwater is the calculated infiltration from surface runoff.
Losses and outflow from the lower zone can be via deep percolation, saturated
zone evapotranspiration, and groundwater flow. Groundwater flow is a user-defined power function of water table stage and, if chosen, depth of water in
the discharge channel.
Continuity
The physical processes occurring within each zone are accounted for by individual mass balances in order to determine end-of-time-step stage, groundwater
flow, deep percolation, and upper zone moisture. Parameters are shown in Figure 20-23 and defined below.
490
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Figure 20-23 GROUND Parameters
Mass balance in the upper (unsaturated) zone is given by,
)' #( ENFIL ! ETU ) " PAREA ! PERC %& " DELT )+
TH 2 = ( $
, / ( DTOT ! D2 )
*)+ ( D1! D2 ) "TH 2 + TH " DWT1
-)
(20-96)
In the lower (saturated) zone, for rising water tables,
#[PERC ! ETD " PAREA ! 0.5 "(GWFLW +
'
%
%
B1
% A1"(D2 ! BC) + A3" D2 "TW + DEPPRC + %
D2 = $
( / (PR ! TH 2) + D1
% DP " D2 / DTOT ) ! TWFLW ]" DELT +
%
%(D2 ! D1)"(TH ! TH 2)
%
&
)
(20-97)
and for falling water tables,
#[PERC ! ETD " PAREA ! 0.5 "(GWFLW + '
%
%
D2 = $ A1"(D2 ! BC)B1 + A3" D2"TW + DEPPRC + ( / (PR ! TH 2) + D1
% DP " D2 / DTOT ) ! TWFLW ]" DELT
%
&
)
where
(20-98)
TH2 = end-of-time-step upper zone moisture content
(fraction),
ENFIL = infiltration rate calculated in subroutine
WSHED,
ETU = upper zone evapotranspiration rate,
PERC = percolation rate,
PAREA = pervious area divided by total area,
DELT = time step value,
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
491
D1 = beginning-of-time-step lower zone depth (elevation above a datum),
D2 = end-of-time-step lower zone depth,
TH = beginning-of-time-step upper zone moisture
content,
DWT1 = beginning-of-time-step upper zone depth,
DTOT = total depth of upper and lower zone =
D1+DWT1,
ETD = lower zone evapotranspiration rate,
GWFLW = beginning-of-time-step groundwater flow rate,
A1 = groundwater flow coefficient,
BC = bottom of channel depth (elevation above datum),
B1 = groundwater flow exponent,
DEPPRC = beginning-of-time-step deep percolation rate,
DP = a recession coefficient derived from interevent
declines in the water table,
PR = porosity, and
TWFLW = channel water influence rate,
A3 = groundwater flow coefficient, and
TW = depth of water in channel (elevation above
datum).
Moisture content (a fraction) is defined as the volume of moisture divided by
the volume of solids plus voids. The maximum possible moisture content is the
porosity; the minimum is the wilting point (discussed below). Solving equation
20-96 for TH2 and using DWT1 = DTOT-D1, yields a much simpler form
which is not a function of the unknown D2,
TH 2 =
[(ENFIL − ETU ) ⋅ PAREA − PERC ]⋅ DELT
(20-99)
DWT 1 + TH
Equation 20-99 is solved first, followed by a Newton-Raphson solution of
equation 20-97 or 20-98. The sequencing will be described in more detail in a
subsequent section, following a description of the various simulated processes.
Infiltration
Infiltration enters groundwater as the calculated infiltration from surface runoff.
The Horton or Green-Ampt equation (or in SWMM 5 an approximation from
SCS hydrology) can be used to describe infiltration. For time steps where the
water table has risen to the surface, the amount of infiltration that cannot be accepted is subtracted from RLOSS (infiltration plus surface evaporation). In the
event that the infiltrated water is greater than the amount of storage available for
that time step, the following equation is used to calculate the amount of infiltration that is not able to be accepted by the soil.
492
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
XSINFIL = ENFIL ! DELT "
AVLVOL
PAREA
(20-100)
where
XSINFL = excess infiltration over pervious area, and
AVLVOL = initial void volume in the upper zone plus total losses and outflows from the system for the
time step.
The second condition exists because of the algebra in equations 20-97, 20-98
and 20-99. As the water table approaches the surface, the end-of-time-step moisture value, TH2, approaches the value of porosity, which makes the denominator
in equations 20-97 and 20-98 go towards zero. Since a denominator close to zero
could result in an unrealistic value of D2, a different way of handling the calculations had to be implemented. When the initial available volume in the upper
zone plus the volume of total outflows and losses from the system minus the
infiltration volume is between 0 and an arbitrary value of 0.000 1 ft
(0.000 03 m), several assumptions are made. First, end-of-time-step groundwater flow and deep percolation, which are normally found by iteration, are
assumed to be equal to their respective beginning-of-time-step values. This step
is taken to ensure that the final available volume remains in the previously mentioned range. Second, TH2 is set equal to an arbitrary value of 90% of porosity.
It is believed that this will allow the TH2 value in this special case to be reasonably consistent with the TH2 values juxtaposed to it in the time series. Third, D2
is set close to the total depth -- the value of D2 depends on the value of porosity.
Fourth, the amount of infiltration that causes the final available volume to exceed 0.000 1 ft (0.000 03 m) is calculated in the following equation and sent
back to the surface in the form of a reduction in the term RLOSS.
XSINFL = ENFIL ⋅ DELT +
(0.0001 − AVLVOL)
PAREA
(20-101)
Because of the way this special case is handled, it is possible for a falling
water table to have the calculated excess infiltration be greater than the actual
amount of infiltration. It is not desirable for the ground to pump water back onto
the surface! Hence, the difference between the calculated excess infiltration and
the actual infiltration is added to the infiltration value of the next time step. The
number of occurrences of this situation in a typical run is very small, as is the
computed difference that is passed to the next time step, so no problems should
occur because of this solution.
Upper Zone Evapotranspiration
Evapotranspiration from the upper zone (ETU) represents soil moisture lost via
cover vegetation and by direct evaporation from the pervious area of the subcatchment. No effort was made to derive a complex formulation of this process.
The hierarchy of losses by evapotranspiration is as follows: 1. surface evapora-
493
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
tion, 2. upper zone evapotranspiration, and 3. lower zone transpiration. Upper
zone evapotranspiration is represented by the following equations,
ETMAX = VAP(MONTH )
(20-102)
ETAVLB = ETMAX ! EVAPO
(20-103)
ETU = CET ! ETMAX
(20-104)
IF (TH .LT .WP.OR.ENFIL.G.0.) ETU = 0
(20-105)
IF ( ETU.GT .ETAVLB ) ETU = ETAVLB
(20-106)
where
ETMAX = maximum total evapotranspiration rate (input
on card F1),
VAP(MONTH) = input maximum evapotranspiration rate for
month MONTH,
ETAVLB = maximum upper zone evapotranspiration rate,
EVAPO = portion of ETMAX used by surface water
evaporation,
CET = fraction of evapotranspiration apportioned to
upper zone, and
WP = wilting point of soil.
The two conditions that make ETU equal to zero in equation 20-105 are believed to simulate the processes occurring in the natural system. The first
condition (moisture content less than wilting point) relates to the soil science
interpretation of wilting point -- the point at which plants can no longer extract
moisture from the soil. The second condition (infiltration greater than zero) assumes that vapor pressure will be high enough to prevent additional
evapotranspiration from the unsaturated zone.
Lower Zone Evapotranspiration
Lower zone evapotranspiration, ETD, represents evapotranspiration from the
saturated zone over the pervious area. ETD is the last evapotranspiration removed, and is determined by the following depth-dependent equation and
conditions.
where
ETD = ( DET ! DWT1) " ETMAX " (1! CET ) / DET
(20-107)
IF(ETD.GT .(ETAVLB ! ETU )) ETD = ETAVLB ! ETU
(20-108)
IF ( ETD.LT .O.) ETD = 0.
(20-109)
ETD = lower zone evapotranspiration rate, and
DET = depth over which evapotranspiration can occur.
494
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Since ETD is typically very small compared to other terms and has to be
checked for certain conditions, it is assumed constant over the time step and not
solved for in the iterative process.
Percolation
Percolation (PERC) represents the flow of water from the unsaturated zone to
the saturated zone, and is the only inflow for the saturated zone. The percolation
equation in the subroutine was formulated from Darcy's Law for unsaturated
flow, in which the hydraulic conductivity, K, is a function of the moisture content, TH. For one-dimensional, vertical flow, Darcy's Law may be written:
v = !K (TH ) "
where
dh
dz
(20-110)
v = velocity (specific discharge) in the direction
of z,
z = vertical coordinate, positive upward,
K(TH) = hydraulic conductivity,
TH = moisture content, and
h = hydraulic potential.
The hydraulic potential is the sum of the elevation (gravity) and pressure heads,
h = z + PSI
(20-111)
where
PSI = soil water tension (negative pressure head) in
the unsaturated zone.
Equating vertical velocity to percolation, and differentiating the hydraulic
potential, h, yields
# dPSI &
Percolation = !K (TH ) " % 1+
(
dz '
$
(20-112)
A choice is customarily made between using the tension, PSI, or the moisture
content, TH, as parameters in equations for unsaturated zone water flow. Since
the quantity of water in the unsaturated zone is identified by TH in previous
equations, it is the choice here. PSI can be related to TH if the characteristics of
the unsaturated soil are known. Thus, for use in equation 20-112, the derivative
is
dPSI dPSI dTH
=
!
dz
dTH dz
(20-113)
The slope of the PSI versus TH curve should be obtained from data for the
particular soil under consideration. Relationships for a sand, sandy loam and
silty loam are shown in Figures 20-24, 20-25 and 20-26 (Laliberte et al., 1966).
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Figure 20-24 Tension, PSI (squares, in. of water) and hydraulic conductivity, K (crosses, in/hr, K multiplied by 100) versus moisture content. (Porosity
o
= 0.485, temp. = 25.1 C, saturated hyd. Conductivity = .60 in/hr.)
Figure 20-25 Tension, PSI (squares, in. of water) and hydraulic conductivity, K (crosses, in/hr, K multiplied by log-10) versus moisture content.
o
(Porosity = 0.452, temp. = 25.1 C, saturated hyd. Conductivity = 91.5-in/hr.)
495
496
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Figure 20-26 Tension, PSI (squares, in. of water) and hydraulic conductivity, K (crosses, in/hr, K multiplied by 200) versus moisture content. (Porosity
o
= 0.503, temp. = 26.5 C, saturated hyd. Conductivity = 0.53 in/hr).
The figures also show the relationship between the hydraulic conductivity of
unsaturated soils and the moisture content. In some cases (e.g. sand), K(TH)
may range through several orders of magnitude. Soils data of this type are becoming more readily available; for example, soil science departments at
universities often publish such information (e.g. Carlisle et al., 1981). The data
illustrated in Figures 20-24, 20-25 and 20-26 are also useful for extraction of
parameters for the Green-Ampt infiltration equations.
Equation 20-112 may be approximated by finite differences as:
* $ #TH ' $ #PSI 'Percolation = !K (TH ) " ,1+ &
)"&
)/
+ % #z ( % #TH (.
(20-114)
For calculation of percolation, it is assumed that the gradient, TH/ z, is the
difference between moisture content TH in the upper zone and field capacity at
the boundary with the lower zone, divided by the average depth of the upper
zone, DWT1/2. Thus,
2 &
) #
,
Percolation = !K (TH ) " *1+ %(TH ! FC ) "
" PCO (
DWT1 '
+ $
.
where
(20-115)
FC = field capacity, and
PCO = PSI/ TH in the region between TH and FD.
PCO is obtained from data of the type of Figures 20-24, 20-25 and 20-26.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
497
Finally, the hydraulic conductivity as a function of moisture content is approximated functionally in the moisture zone of interest as
K (TH ) = HKTH = HKSAT ! EXP #$(TH " PR ) ! HCO %& (20-116)
where
HKTH = hydraulic conductivity as a function of moisture content,
HKSAT = saturated hydraulic conductivity, and
HCO = calibration parameter.
HCO can be estimated by fitting the HKTH versus TH curve to the hydraulic
conductivity versus moisture content curve, if such data are available (e.g. Figures 20-24, 20-25, 20-26); three fits are shown in Figure 20-27. The fits are not
optimal over the entire data range because the fit is only performed for the high
moisture content region between field capacity and porosity. If soils data are not
available, HCO can be estimated by model calibration.
Combining equations 20-115 and 20-116 gives the resulting percolation
equation for the model,
#
(TH " FC ) &(
PERC = HKTH ! %1+ PCO !
DWT1 (
%
$
2 '
where
(20-117)
PERC = percolation rate (positive downward) and is
only nonzero when TH is greater than FC.
If data sources for parameters PCO and HCO are lacking, they may be estimated through the calibration process. On the basis of preliminary runs, the
groundwater subroutine is relatively insensitive to changes in PCO and HCO, so
a lack of extensive soils data should not discourage one from using the model.
If moisture content is less than or equal to field capacity, percolation becomes zero. This limit is in accordance with the concept of field capacity as the
drainable soil water that cannot be removed by gravity alone (Hillel, 1982, p.
243). Once TH drops below field capacity, it can only be further reduced by upper zone evapotranspiration (to a lower bound of the wilting point).
The percolation rate calculated by equation 20-117 will be reduced by the
program if it is high enough to drain the upper zone below field capacity or
make the iterations for D2 converge to an unallowable value. Also, since checks
must be made on PERC, it is assumed to be constant over the time step and
therefore not determined through an iterative process.
498
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Figure 20-27 Model Representation and Measured Hydraulic Conductivity
Curves for Three Types of Soil.
Field Capacity and Wilting Point
These parameters are used for demarcations for percolation and ET. Field capacity, FC, is usually considered to be the amount of water a well-drained soil holds
after free water has drained off, or the maximum amount it can hold against
gravity (SCS, 1964; Linsley et al., 1982). This occurs at soil moisture tensions
(see further discussion below) of from 0.1 to 0.7 atmospheres, depending on soil
texture. Moisture content at a tension of 1/3 atmosphere is often used. The wilting point (or permanent wilting point), WP, is the soil moisture content at which
plants can no longer obtain enough moisture to meet transpiration requirements;
they wilt and die unless water is added to the soil. The moisture content at a tension of 15 atmospheres is accepted as a good estimate of the wilting point (SCS,
1964; Linsley et al., 1982). The general relationship among soil moisture parameters is shown in Figure 20-28.
Data for FC and WP are available from the SCS, agricultural extension offices and university soil science departments. Generalized data are shown in Table
20-6, as derived from Linsley et al. (1982, p. 179).
499
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Figure 20-28 Kinds of Water in Soil (SCS, 1964). Note: Silt Loam Contains
more than Twice as Much Readily Available Water than Sandy Load.
Table 20-15 Volumetric Moisture Content at Field Capacity and Wilting
Point (Derived* from Linsley et al., 1982, Table 6-1.)
Soil Type
Field Capacity
Wilting Point
Sand
0.08
0.03
Sandy loam
0.17
0.07
Loam
0.26
0.14
Silt Loam
0.28
0.17
Clay loam
0.31
0.19
Clay
0.36
0.26
Peat
0.56
0.30
*Fraction moisture content = fraction dry weight x dry density / density of water.
Deep Percolation
Deep percolation represents a lumped sink term for unquantified losses from the
saturated zone. The two primary losses are assumed to be percolation through
the confining layer and lateral outflow to somewhere other than the receiving
water. The arbitrarily chosen equation for deep percolation is:
DEPPRC = DP !
where
D1
DTOT
(20-118)
DEPPRC = beginning-of-time-step deep percolation rate,
and
DP = a recession coefficient derived from interevent
water table recession curves.
500
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
The ratio of D1 to DTOT allows DEPPRC to be a function of the static pressure head above the confining layer. Although DEPPRC will be very small in
most cases, it is included in the iterative process so that an average over the time
step can be used. By doing this, large continuity errors will be avoided should
DEPPRC be set at a larger value.
Groundwater Discharge
Functional Form
Groundwater discharge represents lateral flow from the saturated zone to the
receiving water. The flow equation takes on the following general form:
GWFLW = A1! ( D1" BC ) " TWFLW + A3! D1!TW (20-119)
B1
and
TWFLW = A2 ⋅ (TW − BC )B 2
where
(20-120)
GWFLW = beginning-of-time-step groundwater flow rate
(per subcatchment area,
TWFLW = channel water influence flow rate (per subcatchment area),
A1,A2 = groundwater and channel water influence flow
coefficients,
A3 = coefficient for cross-product,
B1,B2 = groundwater and tailwater influence flow exponents,
BC = elevation of bottom of channel, and
TW = elevation of water in channel.
If D1 is less than BC or TW, GWFLW is set equal to zero. In addition, if TW
= BC and B2 = 0, then the indeterminant form of zero raised to the zero power
in equation 20-120 is set equal to 1.0 by the program. The functional form of
equations 20-119 and 20-120 was selected in order to be able to approximate
various horizontal flow conditions, as will be illustrated below.
Since groundwater flow can be a significant volume, an average flow each
time step is found by iteration using equation 20-97 or 20-98. Groundwater
flows can be routed to any previously defined inlet (node), trapezoidal channel
(link), or pipe (link), allowing isolation of the various components of the total
hydrograph, as shown in Figure 20-29. That is, the groundwater flow does not
have to be routed to the same destination as the overland flow from the subcatchment.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
501
Figure 20-29 Hydrograph of total flow and its two major components.
The effects of channel water on groundwater flow can be dealt with in two
different ways. The first option entails setting TW (elevation of water surface in
the channel) to a constant value greater than or equal to BC (bottom-of-channel
elevation) and A2, B2 and/or A3 to values greater than zero. If this method is
chosen, one is specifying an average tailwater influence over the entire run to be
used at each time step.
The second option makes the channel water elevation, TW, equal to the elevation of water in a trapezoidal channel or circular pipe. For this option, the
groundwater must be routed to a trapezoidal channel or pipe -- not an inlet. The
depth of water in the channel (TW - BC) at each time step is then determined as
the depth in the channel or pipe from the previous time step. (It is assumed that
the bottom of the channel is at the elevation BC.) The beginning-of-time-step
depth must be used to avoid complex and time-consuming iterations with the
coupled channel discharge equations. Unfortunately, because of this compromise the groundwater flow may pulsate as D1 oscillates between just above and
just below elevation TW. This pulsing may introduce errors in continuity and is,
of course, unrepresentative of the actual system. Shorter time steps and larger or
less steep channels (reducing the response of the channel) can reduce the pulses.
Also, caution must be taken when selecting A1, B1, A2, B2 and A3 so that
GWFLW cannot be negative. Although this may occur in the actual system and
represent recharge from the channel, there is currently no means of representing
this reverse flow and subtracting it from the channel. One way of assuring that
502
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
this cannot happen is to make A1 greater than or equal to A2 and B1 greater
than or equal to B2, and A3 equal to zero.
Because of the general nature of the equation, it can take on a variety of
functional forms. For example, a linear reservoir can be selected by setting B1
equal to one and A2 and A3 equal to zero. Two drainage examples are illustrated below.
Example: Infiltration and Drainage to Adjacent Channel
Under the assumption of uniform infiltration and horizontal flow by the
Dupuit-Forcheimer approximation, the relationship between water table elevation and infiltration for the configuration shown in Figure 20-30 is (Bouwer,
1978, p. 51).
Figure 20-30 Definition sketch for Dupuit-Forcheimer approximation for
drainage to adjacent channel.
(
)
K ( h12 ! h22 ) = L2 f
K h1 2 − h2 2 = L2 f
(20-121)
where
f = infiltration rate,
K = hydraulic conductivity, and other parameters
are as shown on Figure 20-31.
Before matching coefficients of equations 20-119 and 20-120 to equation 20121, it should be recognized that the water table elevation in SWMM, D1, represents an average over the catchment, not the maximum at the upstream end that
is needed for h1 in equation 20-121. Let D1 be the average head,
D1 =
h1 − h2
2
(20-122)
substituting h1 = 2 D1 - h2
into equation 20-121 gives, after algebra:
( D1
2
! D1" h2 ) "
4K
=f
L2
(20-123)
503
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
from which a comparison with equations 20-119 and 20-120 yields A1 = A3 =
4K/L2, A2 = 0, and B1 = 2. Note that GWFLW has units of flow per unit area, or
length per time, which are the units of infiltration, f, in equation 20-123.
Example: Hooghoudt’s Equation for Tile Drainage
The geometry of a tile drainage installation is illustrated in Figure 20-31.
Figure 20-31 Definition sketch for Hooghoudt’s Method for flow to circular
drains.
Hooghoudt's relationship (Bouwer, 1978, p. 295) among the indicated parameters is
f = ( 2De + m ) !
4Km
L2
(20-124)
where De = effective depth of impermeable layer below drain center, and other
parameters are defined in Figure 20-31. De is less than or equal to bo in Figure
20-31 and is a function of bo, drain diameter, and drain spacing, L; the complicated relationship is given by Bear (1972, p. 412) and graphed by Bouwer
(1978, p. 296). The maximum rise of the water table, m = h1 - bo. Once again
approximating the average water table depth above the impermeable layer by D1
= 2h1 - bo, equation 20-124 can be manipulated to
4K
2
f = "#( h1 ! bo ) + 2De ( h1 ! bo ) $% & 2
L
16K
2
= "#( D1! bo ) + De D1! De bo $% & 2
L
(20-125)
Comparing equation 20-125 with equations 20-119 and 20-120 yields
A1 = 16K/L2,
B1 = 2,
A2 = 16KDebo/L2,
B2 = 0,
504
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
A3 = 16KDe / TW L2, and
TW = BC = bo = constant during the simulation.
The equivalent depth, De, must be obtained from the sources indicated above.
The mathematics of drainage to ditches or circular drains is complex; several
alternative formulations are described by van Schilfgaarde (1974).
20.7.3 Limitations
Since the moisture content of the unsaturated zone is taken to be an average over
the entire zone, the shape of the moisture profile is totally obscured. Therefore,
infiltrated water cannot be modeled as a diffusing slug moving down the unsaturated zone, as is the case in the real system. Furthermore, water from the
capillary fringe of the saturated zone cannot move upward by diffusion or suction into the unsaturated zone.
The simplistic representation of subsurface storage by one unsaturated tank
and one saturated tank limits our ability to match non- uniform soil columns.
Another limitation is the assumption that the infiltrated water is spread uniformly over the entire catchment area, not just over the pervious area. In addition,
groundwater may not be routed from one subcatchment to another. The tendency
of the tailwater influence to cause pulses if TW-BC is equated to the dynamic
water depth in the adjacent channel is a limitation that will remain until the
channel flow and subsurface flow are solved simultaneously using a set of coupled equations. Such a solution would also permit reverse flow or recharge from
the channel to be simulated.
Finally, water quality is not simulated in any of the subsurface routines. If
water quality is simulated in surface runoff and the subsurface flow routines
activated, any loads entering the soil will disappear, as if the soil provides 100
percent treatment.
20.7.4 Computation sequence
A flowchart of the computation is presented in Figure 20-32 below.
The procedure first initializes pertinent parameters, then calculates fluxes
that are constant over the time step. Beginning-of-time-step fluxes are calculated
next, and the value of percolation is checked to ensure that it will not raise the
water table above the ground surface.
After other constants are calculated and TH2 is determined from equation
20-99, the program branches to one of four areas. The first and second areas are
for rising and falling water tables, equations 20-97 and 20-98, respectively. In
both cases, Newton-Raphson iteration is used to solve simultaneously for the
final groundwater flow, depth of lower zone, and deep percolation. Each iteration checks whether or not groundwater flow is possible (D1 greater than or
equal to TW and BC). After the iterations converge, final conditions are set as
the next time step's initial conditions.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
505
Figure 20-32 Flowchart of Subsurface and Directly-connected Surface Calculations.
In the event of saturation (D1 = DTOT), the third area sets D2 equal to
DTOT, sets final groundwater flow equal to the maximum possible (D2 =
DTOT), and assumes DEPPRC remains constant over the time step. Any excess
infiltration is then routed back to the surface for overland flow calculations, and
final conditions are set for the next initial conditions. However, if the maximum
groundwater flow and DEPPRC rates permit some infiltration into the subsurface zone, the initial and final groundwater flow are averaged to be used
averaged to be used as the new initial groundwater flow, and the program
branches back to iterate for the solution. This pathway will rarely, if ever, be
taken, but must be included to minimize possible continuity errors.
In the event the available storage in the unsaturated zone is less than 0.000 1
ft (0.000 03 m), the fourth area sets TH2 equal to 90% of porosity and D2 close
to DTOT, and returns any infiltration to the surface that causes the final unfilled
506
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
upper zone volume to be greater than 0.000 1 ft (0.000 03 m). This is to avoid
oscillations as the water table hovers near the ground surface. Again, final conditions are then set as the next time step's initial conditions.
20.7.5 Examples
Cypress Creek Calibration and Verification
Two examples illustrate the use of the new subroutine. The first example is a
year-long simulation of a 47 mi2 portion of the 117 mi2 Cypress Creek Watershed in Pasco County, Florida, about 30 miles north of Tampa. The region was
studied in relation to the interaction of surface water and ground water under the
stress of heavy pumping and drainage activities in the area (Heaney et al., 1986).
The watershed is characterized by sandy soils in which most water movement
follows subsurface pathways. For this example, only a single 47 mi2 area above
State Road 52 and tributary to the USGS gage at San Antonio was simulated.
Twenty-four parameters were required for each subsurface subcatchment.
(Many of these can be ignored or set to zero during most runs; not all parameters
are required for all runs.) In addition to the output just mentioned, a subsurface
continuity check is provided in addition to the existing surface continuity check.
The simulation was divided into two six-month runs: the first six months for
calibration, and the second six months for verification. Since Cypress Creek is a
very flat, pervious area with well-drained soils and very little surface flow, it
was modeled in a manner that would allow groundwater flow to account for
most of the flow in the channel. In other words, the groundwater parameters represented by far the most critical part of the calibration. The only complete
rainfall data for the calibration period are for the gage at St. Leo, out of the
catchment to the east. Although these data are in daily increments, the calibration process was relatively simple because of the existence of both flow and
shallow-well stage data. In addition, only one subcatchment (surface and subsurface) was used, since the purpose of this example was only to illustrate the use
of the groundwater routines, not to provide a thorough simulation.
Hypothetical Catchment with High Water Table
The second example is a 100 ac hypothetical subcatchment with the same soil
properties as Cypress Creek and a water table that is initially one foot from the
surface. The 10-yr SCS Type II design storm for Tallahassee, Florida was used
for the rainfall input. This storm is characterized by very high rainfall between
hours 11 and 12.
In order to illustrate the influence of a high water table, runs were made with
and without the groundwater subroutine. Table 20-16 shows the disposition of
the rainfall when a high water table is simulated as opposed to when it is ignored. Note that evaporation is about the same, and the difference in the amount
of infiltrated water shows up as a direct difference in surface runoff. (The runs
were halted before all water had run off). A larger difference in peak flows
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
507
would have resulted if the flows had not been routed to a very large channel.
Also, note that the two hydrographs are identical until about hour eleven into the
simulation, when the simulated water table rises to the surface.
Table 20-16 Fate of Runoff With and Without High Water Table Simulation
Water Budget Component
Precipitation
Infiltration
Evaporation
Channel flow at inlet
Water remaining in channel
Water remaining on surface
Continuity error
Inches over Total Basin
With Water Table SimulaWithout Water Table Simution
lation
8.399
8.399
6.637
1.731
0.103
0.104
1.495
2.407
0.015
0.038
0.150
4.124
0.001
0.005
20.7.6 Conclusions
Although the subroutine is fairly simple in design and has several limitations,
the new groundwater subroutine should increase the applicability of SWMM.
Preliminary test runs have determined it to be accurate in the simulation of water
table stage and groundwater flow. Further calibration and verification tests need
to be done on other areas to confirm these preliminary results. Also, estimation
of parameters, although fairly numerous, appears to be relatively uncomplicated.
In addition, parameters are physically-based and should be able to be estimated
from soils data. The flexible structure of the algorithm should permit a more
realistic simulation of catchments in which a major hydrograph component is
via subsurface pathways.
20.7.7 Subsurface Flow Routing
Introduction
Briefly, infiltration by either the Horton or Green-Ampt methods (or a simplified
SCS method in SWMM 5) may be routed through an unsaturated zone lumped
storage, followed by routing through a saturated zone lumped storage. Outflow
may occur from the saturated zone to channel or pipes or may be lost (from the
simulation) to deep groundwater. Evapotranspiration (ET) from both the upper
and lower zone may also be simulated, and the groundwater table is dynamic: if
it rises to the surface, the upper zone disappears and infiltration will be stopped;
if it drops below the elevation of the bottom of the effluent channel or pipe,
groundwater outflow will cease. The processes are illustrated schematically in
Figure 20-23. If quality simulation is included, any water routed through the
subsurface zones will be clean and act to dilute concentrations in downstream
channels or pipes.
Data needs closely reflect soil properties. That is, data for subsurface flow
routing involves parameters such as porosity, field capacity, hydraulic conductivity, water table elevation. These data must be obtained from SCS or other
508
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
sources. As mentioned previously in regard to infiltration parameters, state university Soil Science departments can often provide such information (e.g.
Carlisle et al., 1981).
Groundwater outflow may be routed to a channel or pipe. If no channel or
pipe number is indicated, groundwater outflow will be lost from the simulation,
although it will be accounted for in the continuity check.
Groundwater Flow and Soil Parameters
Groundwater outflow parameters A1, A2, A3, B1 and B2 are defined by equations 20-119 and 20-120. Because of the general nature of the two equations, a
variety of functional forms can be approximated. For example, a linear reservoir
can be selected by setting B1 equal to one and A2 and A3 equal to zero. The
Dupuit approximation can be selected, within its usual limitations (Todd, 1980),
as illustrated in the example earlier.
Two methods can be used to simulate the effect of channel or pipe tailwater
elevations on groundwater outflow. The first method involves setting TW greater than BC and A2, B2 greater than zero. It is also desirable to route the flow to
a channel or pipe (otherwise, water will be lost from the simulation but accounted for in the continuity check), but this is not absolutely necessary. When this
method is chosen, the user is in fact supplying the average channel flow influence over the entire run; that is, parameter TW in equation 20-120 will be
constant for all time steps. This method is most applicable when the depth of the
water in the channel is thought to remain fairly constant for the length of the run.
For the second method, TW must be less than zero, which makes it simply an
indicator parameter. In addition, A2 and B2 must be greater than zero, and the
groundwater flow must be routed to a previously defined trapezoidal channel or
circular pipe. If this method is chosen, the program will use the elevation of the
water surface in the channel or pipe at the end of the previous time step as the
current time-step value for the variable TW (elevation of water surface in channel or pipe). The invert elevation of the channel or pipe is assumed to equal BC.
Because of the fact that flow routing in the subsurface zone is not coupled with
the channel or pipe routing, oscillations can occur in the groundwater flow as
elevation D1 hovers near the variable tailwater elevation TW. This can usually
be cured by reducing the simulation time step, WET or WETDRY. See the discussion earlier.
Under-drains can be simulated as shown in the example in the previous section. However, since groundwater flow from each subsurface subcatchment can
only be routed to one pipe, a network of under-drain pipes must be replaced by
one equivalent pipe for simulation purposes.
One very important rule to remember, regardless of the functional form chosen, is that groundwater flow should never be allowed to be negative. Although
negative flow may be true for the real system (i.e. bank recharge), it should not
be allowed to happen in the model because there is currently no means of subtracting flow from the channel (since the channel flow routing is not coupled to
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
509
the groundwater flow routing). An easy way to assure that groundwater flow
remains positive is by making A1 greater than or equal to A2 and B1 greater
than or equal to B2.
Saturated hydraulic conductivity, porosity, wilting point, and field capacity
are all measurable but difficult-to-obtain values. A discussion regarding saturated hydraulic conductivity was presented previously for the infiltration
parameters. WP and FC are usually related to specific suction pressures. Table
20-16 contains typical values for wilting point and field capacity (Linsley et al.,
1982). SCS and university sources, especially agricultural extension offices in
the U.S., often have these data.
For these groundwater routines, actual porosity and apparent porosity are
considered to be equal, since no mechanism exists for adjusting for entrapped air
and the difference is usually minor. Porosity is critical to this formulation because of its role in determining moisture storage. WP and FC are less important
because they act only as threshold values at which processes change.
Percolation and Evapotranspiration Parameters
Water percolates from the unsaturated upper zone to the saturated lower zone.
Parameters HCO and PCO are defined by equations 20-116 and 20-117, respectively. HCO can be estimated from an exponential fit of hydraulic conductivity
to soil moisture, if such data are available. Fitted or not, HCO is a sensitive calibration parameter for movement of unsaturated zone water into the saturated
zone. PCO is the slope, PSI/ TH, of the soil tension versus moisture content
curve. An average value can be used from data of the form of Figures 20-24, 2025 and 20-26. It can also be used for calibration, although it is likely that a better
estimate of PCO can be obtained than for HCO.
The model includes a deep percolation term which is intended to account for
losses through a confining layer, if they could be quantified. Parameter DP is
defined by equation 20-118. The functional form provides for a first order decay, typical of water table recession curves. Because of the uncertainty
associated with this term, it is reasonable to use it for other saturated zone losses
that can be quantified by calibration but less than adequately explained physically.
Potential evaporation available for subsurface water loss is the difference between monthly (or other time interval) evaporation input and evaporation used
by the surface routing. Upper zone ET is a fraction CET of this difference, by
equation 20-104. Lower zone ET removes the remaining fraction linearly as a
function of depth to the water table according to equation 20-107. Parameter
DET is the maximum depth to the water table for which ET can occur. Subsurface ET can be turned off by setting CET = 0 and DET = 0.
Infiltration-Inflow
See section 20.5.5 above.
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
20.8 Water Quality
20.8.1 Introduction
Simulation of urban runoff quality is very inexact. The many difficulties of simulation of urban runoff quality are discussed by Huber (1985, 1986). Very large
uncertainties arise both in the representation of the physical, chemical and biological processes and in the acquisition of data and parameters for model
algorithms. For instance, subsequent sections discuss the concept of buildup of
pollutants on land surfaces and washoff during storm events. The true mechanisms of buildup involve factors such as wind, traffic, atmospheric fallout, land
surface activities, erosion, street cleaning and other imponderables. Although
efforts have been made to include such factors in physically-based equations
(James and Boregowda, 1985), it is unrealistic to assume that they can be represented with enough accuracy to determine a priori the amount of pollutants on
the surface at the beginning of the storm. Equally naive is the idea that empirical
washoff equations truly represent the complex hydrodynamic (and chemical and
biological) processes that occur while overland flow moves in random patterns
over the land surface.
Such uncertainties can be dealt with in two ways. The first option is to collect enough calibration and verification data to calibrate the model equations
used for quality simulation. Given sufficient data, the equations used in SWMM
can usually be manipulated to reproduce observed concentrations and loads.
This is essentially the option discussed at length in the following sections. The
second option is to abandon the notion of detailed quality simulation altogether
and use either (a) a constant concentration applied to quantity predictions (i.e.
obtain storm loads by multiplying predicted volumes by an assumed concentration) (Johansen et al., 1984) or (b) a statistical method (Hydroscience, 1979;
Driscoll and Assoc., 1981; EPA, 1983b; DiToro, 1984). Two ways in which
constant concentrations can be simulated in SWMM are by using a rating curve
(equation 20-109) with an exponent of 1.0 or by assigning a concentration to
rainfall. Statistical methods are based in part upon strong evidence that storm
event mean concentrations (EMCs) are lognormally distributed (Driscoll, 1986).
The statistical methods recognize the frustrations of physically-based modeling
and move directly to a stochastic result (e.g. a frequency distribution of EMCs),
but they are even more dependent on available data than methods such as those
found in SWMM. That is, statistical parameters such as mean, median and variance must be available from other studies in order to use the statistical methods.
Furthermore, it is harder to study the effect of controls and catchment modifications using statistical methods.
The main point is that there are alternatives to the approaches used in
SWMM; the latter can involve extensive effort at parameter estimation and
model calibration to produce quality predictions that may vary greatly from an
unknown reality. Before delving into the arcane methods incorporated in
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
511
SWMM and other urban runoff quality simulation models, you should try to
determine whether or not the effort will be worth it in view of the uncertainties
of the process and whether or not simpler alternative methods might suffice. The
discussions that follow provide a comprehensive view of the options available in
SWMM, which are more than in almost any other comparable model in the public domain, but the extent of the discussion should not be interpreted as a
guarantee of success in applying the methods.
Overview of Quality Procedures
For most SWMM applications, surface runoff is the origin of water quality constituents. Methods for prediction of urban runoff quality constituents are
reviewed extensively by Huber (1985, 1986). Several mechanisms constitute the
genesis of stormwater quality, most notably buildup and washoff. In an impervious urban area, it is usually assumed that a supply of constituents is built up on
the land surface during dry weather preceding a storm. Such a buildup may or
may not be a function of time and factors such as traffic flow, dry fallout and
street sweeping (James and Boregowda, 1985). With the storm the material is
then washed off into the drainage system. The physics of the washoff may involve rainfall energy, as in some erosion calculations, or may be a function of
bottom shear stress in the flow as in sediment transport theory. Most often, however, washoff is treated by an empirical equation with slight physical
justification. As an alternative to the use of a buildup-washoff formulation, quality loads (i.e., mass/time) may be generated by a rating curve approach in which
loads are proportional to flow raised to some power.
A final source of constituents is in the precipitation itself. Much more monitoring exists of precipitation quality at present than in the past, and precipitation
can contain surprisingly high concentrations of many parameters. This is treated
in SWMM by permitting a constant concentration of constituents in precipitation.
Many constituents can appear in either dissolved or solid forms (e.g. BOD,
nitrogen, phosphorus) and may be adsorbed onto other constituents (e.g. pesticides onto solids) and thus be generated as a portion of such other constituents.
To treat this situation, any constituent may be computed as a fraction (potency
factor) of another. For instance, five percent of the suspended solids load could
be added to the (soluble) BOD load. Or several particle size - specific gravity
ranges could be generated, with other constituents consisting of fractions of
each.
Water quality constituents may be simulated in surface runoff. All are usersupplied, with appropriate parameters for each. Up to five user-supplied land
uses may be entered to characterize different subcatchments. Street sweeping is
a function of land use, and individual constituents. Constituent buildup may be a
function of land use or else fixed for each constituent. Considerable flexibility
thus exists.
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Output consists of pollutographs (concentrations versus time) at desired locations along with total loads, and flow-weighted concentration means and
standard deviations. In addition, summaries are printed for each constituent describing its overall mass balance for the simulation for the total catchment, i.e.,
sources, removals, etc. These summaries are the most useful output for continuous simulation runs.
In the following material, the processes described above are discussed in
more detail.
Quality Simulation Credibility
Although the conceptualization of the quality processes is not difficult, the reliability and credibility of quality parameter simulation is very difficult to
establish. In fact, quality predictions by SWMM or almost any other surface
runoff model are almost useless without local data for calibration and validation.
If such data are lacking, results may still be used to compare relative effects of
changes, but parameter magnitudes (e.g. predicted concentrations) will forever
be in doubt. This is in marked contrast to quantity prediction for which reasonable estimates of hydrographs may be made in advance of calibration.
Moreover, there is disagreement in the literature as to what are the important
and appropriate physical and chemical mechanisms that should be included in a
model to generate surface runoff quality. The objective in SWMM has been to
provide flexibility in mechanisms and the opportunity for calibration. But this
places a considerable burden on the user to obtain adequate data for model usage
and to be familiar with quality mechanisms that may apply to the catchment being studied. This burden is all too often ignored, leading ultimately to model
results being discredited.
In the end then, there is no substitute for local data, that is, observed rain,
flow and concentrations, with which to calibrate and verify the quality predictions. Without such data, little reliability can be placed in the predicted
magnitudes of quality parameters.
Required Degree of Temporal Detail
Early quality modeling efforts with SWMM emphasized generation of detailed
pollutographs, in which concentrations versus time were generated for short
time increments during a storm event (e.g. Metcalf and Eddy et al., 1971b). In
most applications, such detail is entirely unnecessary because the receiving waters cannot respond to such rapid changes in concentration or loads. Instead,
only the total storm event load is necessary for most studies of receiving water
quality. Time scales for the response of various receiving waters are presented in
Table 20-17 (Driscoll, 1979; Hydroscience, 1979). Concentration transients occurring within a storm event are unlikely to affect any common quality
parameter within the receiving water, with the possible exception of bacteria.
The only time that detailed temporal concentration variations might be needed
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
513
within a storm event is when they will affect control alternatives. For example, a
storage device may need to trap the first flush of pollutants.
Table 20-17 Required Temporal Detail for Receiving Water Analysis. (after
Driscoll, 1979 and Hydroscience, 1979)
Type of Receiving Water
Lakes, Bays
Estuaries
Large Rivers
Streams
Ponds
Beaches
Key Constituents
Nutrients
Nutrients, DO(?)
DO, Nitrogen
DO, Nitrogen
Bacteria
DO, Nutrients
Bacteria
Response Time
Weeks – Years
Days – Weeks
Days
Hours – Days
Hours
Hours – Weeks
Hours
The significant point is that calibration and verification ordinarily need only
be performed on total storm event loads, or on event mean concentrations. This
is a much easier task than trying to match detailed concentration transients within a storm event.
Quality Constituents
The number and choice of constituents to be simulated must reflect the modeller’s needs, potential for treatment and receiving water impacts, etc. Almost any
constituent measured by common laboratory or field tests can be included. The
name and concentration units entered will be passed to subsequent modules and
used as column headings for tabular output of concentrations.
Options for concentration units are reasonably broad and broken into three
categories. Most constituents are measurable in units of milligrams per liter,
mg/l. Although parameters such as metals, phosphorus or trace organics are often given as micrograms per liter, µg/l, the output of concentrations for is
expected to be compatible with reported values of such parameters. Thus, the
use of mg/l should suffice for all parameters for which the quantity of the parameter is measured as a mass (e.g. mg).
A notable exception to the use of mass units is for bacteria, for which constituents such as coliforms, fecal strep etc. are given as a number or count per
volume, e.g. MPN/l.
A third category covers parameters with specialized concentration-type units
such as pH, conductivity (umho), turbidity (JTU), color (PCU), temperature
(ºC). For these parameters, interpretation of concentration results is straightforward, but total mass or buildup is mostly conceptual. Since loads (e.g.
mass/time) are transmitted in terms of concentration times flow rate, whichever
concentration units are used, proper continuity of parameters is readily maintained. Of course, simulation of a parameter such as temperature could only be
done to the zeroeth approximation in any event since all surface runoff constituents are assumed to be conservative.
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Land Use Data
Each subcatchment must be assigned only one of up to five user-supplied land
uses. Street sweeping is a function of land use and constituent (discussed subsequently). Constituent buildup may be a function of land use depending on the
type of buildup calculation specified. The buildup parameters are used only
when constituent buildup will be a function of dust and dirt buildup. This is discussed in detail below. The land use types are completely arbitrary, but they
could reflect those for which data are available and, of course, those found in the
catchment, or an aggregate thereof.
20.8.2 Buildup
Background
One of the most influential of the early studies of stormwater pollution was
conducted in Chicago by the American Public Works Association (1969). As
part of this project, street surface accumulation of dust and dirt (DD) (anything
passing through a quarter inch mesh screen) was measured by sweeping with
brooms and vacuum cleaners. The accumulations were measured for different
land uses and curb length, and the data were normalized in terms of pounds of
dust and dirt per dry day per 100 ft of curb or gutter. These well-known results
are shown in Table 20-18 and imply that dust and dirt buildup is a linear function of time. The dust and dirt samples were analyzed chemically, and the
fraction of sample consisting of various constituents for each of four land uses
was determined, leading to the results shown in Table 20-19.
Table 20-18 Measured Dust and Dirt Accumulation in Chicago (APWA,
1969).
Type
1
2
3
4
5
Land Use
Single Family Residential
Multi-Family Residential
Commercial
Industrial
Undeveloped or Park
Pounds DD/dry day
per 100 ft-curb
0.7
2.3
3.3
4.6
1.5
Table 20-19 Milligrams of Pollutant Per Gram of Dust and Dirt (Parts Per
Thousand By Mass) For Four Chicago Land Uses. (APWA, 1969).
Parameter
Single Family
Residential
5.0
40.0
1.3 x 106
0.48
0.05
BOD5
COD
Total Coliformsa
Total N
Total PO4 (as
PO4)
a
Units for coliforms are MPN/gram.
Land Use Type
Multi-Family
Residential
3.6
40.0
2.7 x 106
0.61
0.05
Commercial
Industrial
Industrial
7.7
39.0
1.7 x 106
0.41
0.07
3.0
40.0
1.0 x 106
0.43
0.03
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
515
From the values shown in Tables 20-18 and 20-19, the buildup of each constituent (also linear with time) can be computed simply by multiplying dust and
dirt by the appropriate fraction. Since the APWA study was published during the
original SWMM project (1968-1971), it represented the state of the art at the
time and was used extensively in the development of the surface quality routines
(Metcalf and Eddy et al., 1971a, Section 11). In fact, the formulation and data
may still be used in SWMM should one wish to rely upon highly site specific
results for Chicago. Needless to say, unless the application is in Chicago this is
not recommended. Several useful studies have been conducted since the pioneering APWA work which permit much more selectivity.
Of course, the whole buildup idea essentially ignores the physics of generation of pollutants from sources such as street pavement, vehicles, atmospheric
fallout, vegetation, land surfaces, litter, spills, anti-skid compounds and chemicals, construction, and drainage networks. Lager et al. (1977a) and James and
Boregowda (1985) consider each source in turn and give guidance on buildup
rates. But the rates that are (optionally) entered into SWMM only reflect the
aggregate of all sources.
Available Studies
The 1969 APWA study (APWA, 1969) was followed by several more efforts,
notably AVCO (1970) reporting extensive data from Tulsa, Sartor and Boyd
(1972) reporting a cross section of data from ten US cities, and Shaheen (1975)
reporting data for highways in the Washington, D.C. area. Pitt and Amy (1973)
followed the Sartor and Boyd (1972) study with an analysis of heavy metals on
street surfaces from the same ten US cities. More recently, Pitt (1979) reports on
extensive data gathered both on the street surface and in runoff for San Jose. A
drawback of the earlier studies is that it is difficult to draw conclusions from
them on the relationship between street surface accumulation and stormwater
concentrations since the two were seldom measured simultaneously.
Amy et al. (1975) provide a summary of data available in 1974 while Lager
et al. (1977a) provide a similar function as of 1977 without the extensive data
tabulations given by Amy et al. Perhaps the most comprehensive summary of
surface accumulation and pollutant fraction data is provided by Manning et al.
(1977) in which the many problems and facets of sampling and measurements
are also discussed. For instance, some data are obtained by sweeping, others by
flushing; the particle size characteristics and degree of removal from the street
surface differ for each method. Some results of Manning et al. (1977) will be
illustrated later. Surface accumulation data may be gleaned, somewhat less directly, from references on loading functions that include McElroy et al. (1976),
Heaney et al. (1977) and Huber et al. (1981a).
Ammon (1979) summarized many of these and other studies, specifically in
regard to application to SWMM. For instance, there is evidence to suggest several buildup relationships as alternatives to the linear one, and these
relationships may change with the constituent being considered. Upper limits for
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
buildup are also likely. Several options for both buildup and washoff are investigated by Ammon, and his results are partially the basis for formulations in this
version of SWMM. Jewell et al. (1980) also provide a useful critique of methods
available for simulation of surface runoff quality and ultimately suggest statistical analysis as the proper alternative. Many of the problems and weakness with
extensive data and present modeling formulations are pointed out by Sonnen
(1980) along with guidelines for future research.
To summarize, many studies and voluminous data exist with which to formulate buildup relationships, most of which are purely empirical and data-based,
ignoring the underlying physics and chemistry of the generation processes.
Nonetheless, they represent what is available, and modeling techniques in
SWMM are designed to accommodate them in their heuristic form.
Buildup Formulations
Most data, as will be seen, imply linear buildup since they are given in units
such as lb/ac-day or lb/100 ft curb-day. As stated earlier, the Chicago data that
were used in the original SWMM formulation assumed a linear buildup. However, there is ample evidence that buildup can be nonlinear; Sartor and Boyd's
(1972) data are most often cited as examples (Figure 20-33, below).
Figure 20-33 Non-linear buildup of street solids. (After Sartor and Boyd,
1972, p. 206.)
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
517
More recent data from Pitt (Figure 20-34) for San Jose indicate almost linear
accumulation, although some of the best fit lines indicated in the figure had very
poor correlation coefficients, ranging from 0.35 ≤ r ≤ 0.9. Even in data collected
as carefully as in the San Jose study, the scatter (not shown in the report) is considerable. Thus, the choice of the best functional form is not obvious. Whipple et
al. (1977) have criticized the linear buildup formulation included in the original
SWMM, although it is somewhat irrelevant since users may insert their own
desired initial loads, calculated by whatever procedure desired. However, this is
a useful option only for single-event simulation.
Figure 20-34 Buildup of street solids in San Jose. (After Pitt, 1979, p. 29.)
The proper choice of the proper functional form must ultimately be the user’s
responsibility. The program provides three options for dust and dirt buildup (Table 20-20) and three for individual constituents (Table 20-21): power-linear,
exponential or Michaelis-Menton.
Linear buildup is simply a subset of a power function buildup. The shapes of
the three functions are compared in Figure 20-35 using the dust and dirt parameters as examples, and a strictly arbitrary assignment of numerical values to the
parameters. Exponential and Michaelis-Menton functions have clearly defined
asymptotes or upper limits. Upper limits for linear or power function buildup
may be imposed if desired. Instantaneous buildup may be easily achieved using
any of the formulation with appropriate parameter choices. For instance, if it
were desired to always have a fixed amount of dust and dirt available, DDLIM,
at the beginning of any storm event (i.e. after any dry time step during continuous simulation), then linear buildup could be used with DDPOW = 1.0 and
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Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
DDFACT equal to a large number ≥ DDLIM/DELT. Linear buildup is fastest in
terms of computer time.
Table 20-20 Buildup Equations and Units for Dust and Dirt.
For metric input substitute kg for lb, ha for ac and km for 100-ft.
DD = Dust and Dirt, lb.
t = time, days.
METHOD
Type
0
Power-Linear
1
2
Exponential
Michaelis-Menton
Equation
DD = DDFACT . tDDPOW
DD <= DDLIM
DD = DDLIM . (1 – e-DDPOW . t)
DD = DDLIM . t / (DDFACT + t)
Units for Card Input of:
JACGUT
DDLIM
DDPOW
DDFACT
0
lb . (100 ft curb)-1
Dimensionless
Lb . (100 ft-curb)-1 . day-DDPOW
1
lb . ac-1
Dimensionless
Lb . ac-1 . day-DDPOW
2
Lb
Dimensionless
Lb . day-DDPOW
1
0
lb . (100 ft curb)-1
day-1
Not Used
1
lb . ac-1
day-1
Not Used
-1
2
Lb
day
Not Used
-1
2
0
lb . (100 ft curb)
Not Used
Day
-1
1
lb . ac
Not Used
Day
2
Lb
Not Used
Day
Parameters DDLIM, DDPOW, and DDFACT are single subscripted by land use, J.
METHOD
0
Table 20-21 Buildup Equations for Constituents.
PSHED = Constituent quantity.
t = time, days.
For parameter units, see Table 5-10.
KALC
1
Type
Power-Linear
Equation
PSHED = QFACT(3) . tQFACT(2)
PSHED <= QFACT (1)
2
Exponential
PSHED = QFACT(1) . (1 – e-QFACT(2) . t)
3
Michaelis-Menton
PSHED = QFACT(1) . t / (QFACT(3) + t)
Parameters QFACT are doubly suscripted. Second subscript is consituent number, K.
Figure 20-35 Comparison of linear and three non-linear buildup equations.
Dust and dirt, DD is used as an example. Numerical values have been chosen arbitrarily.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
519
It is apparent in Figure 20-35 that different options may be used to accomplish the same objective (e.g. nonlinear buildup); the choice may well be made
on the basis of available data to which one of the other functional forms have
been fit. If an asymptotic form is desired, either the exponential or Michaelis-Menton option may be used depending upon ease of comprehension of the
parameters. For instance, for exponential buildup the exponent (i.e. DDPOW for
dust and dirt of QFACT(2,K) for a constituent) is the familiar exponential decay
constant. It may be obtained from the slope of a semi-log plot of buildup versus
time. As a numerical example, if its value were 0.4 day-1, then it would take 5.76
days to reach 90 percent of the maximum buildup (see Figure 20-36).
For Michaelis-Menton buildup the parameter DDFACT for dust and dirt (or
QFACT(3,K) for a constituent) has the interpretation of the half-time constant,
that is, the time at which buildup is half of the maximum (asymptotic) value. For
instance, DD = 50 lb at t = 0.9 days for curve 4 in Figure 20-35. If the asymptotic value is known or estimated, the half-time constant may be obtained from
buildup data from the slope of a plot of DD versus t . (DDLIM- DD), using dust
and dirt as an example. Generally, the Michaelis-Menton formulation will rise
steeply (in fact, linearly for small t) and then approach the asymptote slowly.
The power function may be easily adjusted to resemble asymptotic behavior,
but it must always ultimately exceed the maximum value (if used). The parameters are readily found from a log-log plot of buildup versus time. This is a
common way of analyzing data, (e.g. Miller et al., 1978; Ammon, 1979; Smolenyak, 1979; Jewell et al., 1980; Wallace, 1980).
Prior to the beginning of the simulation, buildup occurs over DRYDAY days
for both single event and continuous simulation. During the simulation, buildup
will occur during dry time steps (runoff less than 0.0005 in./hr or 0.013 mm/hr)
only for continuous simulation.
For a given constituent, buildup may be computed either as a fraction of dust
and dirt or individually for the constituent. If the first option is used (KALC = 0)
then the rate of buildup will depend upon the fraction and the functional form
used for a given land use. In other words, the functional form could vary with
land use for a given constituent. If the second option is used (1 ≤ KALC ≤ 3) the
buildup function will be the same for all land uses (and subcatchments) for a
given constituent. Of course, each constituent may use any of the options.
Catchment characteristics (i.e. area or gutter length) may be included through
the use of parameters JACGUT or KACGUT, as described in Tables 20-20 and
20-22.
Units for dust and dirt buildup parameters are reasonably straightforward and
explained in Table 20-20. For example, if linear buildup was assumed using the
Chicago APWA data (APWA, 1969), values for DDFACT could be taken directly from Table 20-17 for different land uses. Parameters JACGUT would
equal zero. A limiting buildup (DDLIM) of so many lb/100 ft-curb could be entered if desired, and for linear buildup, DDPOW = 1.0.
520
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Units for constituent buildup parameters depend upon parameter NDIM, that
is, the units for the buildup parameters depend upon the units of the constituent.
When NDIM = 0 and the constituent concentration is simply mg/l (mass per
volume), then buildup units are straightforward and given as pounds. When
NDIM = 1, concentrations are given as some other quantity per volume, usually
a bacteria count such as MPN/l. In this case buildup is simply in millions of
MPN. The scaling is included to facilitate entry of large numbers.
Table 20-22 Units for Input of Constituent Parameters
Define Q1 and Q2 ≡ Constituent quantity as follows:
NDIM
Q
0
Q1 = lb, Q2 = mg
1
Q1 = Q2 = 106 . other quantity, e.g. 106 .
For metric input substitute kg for
MPN
lb, m3 for ft3, ha for ac and km for
2
Q1 = Q2 = Concentration x ft3, e.g. JTU
100-ft
. ft3
For KALC = 4, buildup parameters are not required.
For KALC = 0, QFACT (J,K) = Q2 / gdd for J = 1 to JLAND and gDD = grams dust and dirt. (E.g. see
Table 20-10). Otherwise:
KAL
KACGUT
QFACT (1,K)
QFACT (2,K)
QFACT (3,K)
C
1
0
Q1 . (100 ftDimensionless Q1 . (100 ft-curb)-1 . day-QFACT
-1
(2,K)
curb)
1
Q1 . ac-1
Dimensionless Q1 . ac-1 . day-QFACT (2,K)
2
Q1
Dimensionless Q1 . day-QFACT (2,K)
2
0
Q1 . (100 ftday-1
Not Used
curb)-1
1
Q1 . ac-1
day-1
Not Used
2
Q1
day-1
Not Used
3
0
Q1 . (100 ftNot Used
Day
curb)-1
-1
1
Q1 . ac
Not Used
Day
2
Q1
Not Used
Day
QFACT (4,K) and QFACT (5,K) are not required for KALC ≠ 0.
When NDIM = 2, constituent concentrations are given in specialized units
such as pH, JTU, PCU, ºC. Buildup of such parameters is rarely referred to; instead, a much more viable option is the use of a rating curve that gives load (i.e.
concentration times flow) directly as a function of flow (discussed subsequently). However, the buildup option may be used with such constituents if desired.
Within the RUNOFF Module, concentrations are ultimately computed in subroutine GUTTER by dividing a load (quantity per second) by a flow rate (cubic
feet per second). Thus, if the quantity has units of concentration times cubic feet,
the proper conversion will be made. This is the reason for the peculiar units requested in Table 20-22. Such an analysis is straightforward and analogous to
computations of total mass in pounds (obtained by summing flow rate times
concentration) for constituents measured in mg/l.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
521
Buildup Data
Data with which to evaluate buildup parameters are available in most of the
references cited earlier under available studies. Manning et al. (1977) have perhaps the best summary of linear buildup rates; these are presented in Table 2023. It may be noted that dust and dirt buildup varies considerably among three
different studies. Individual constituent buildup may be taken conveniently as a
fraction of dust and dirt from the entries in Table 20-22, or they may be computed explicitly. It is apparent that although a large number of constituents have
been sampled, little distinction can be made on the basis of land uses for most of
them.
As an example, suppose options METHOD = 0 and KALC = 0 are chosen
and all data are used from Table 20-23 to compute dust and dirt parameters.
Since the data are given as lb x curb-mile-1 x day-1, linear buildup is assumed
and commercial land use DD buildup (average for all data) would be DDFACT
= 2.2 lb / (100-ft curb - day) (i.e. 2.2 = 116/52.8, where 52.8 is the number of
hundreds of feet in a mile). DDPOW would equal 1.0 and no data are available
to set an upper limit, DDLIM. Parameter JACGUT = 0 so that the loading rate
will be multiplied by the curb length for each subcatchment. Constituent fractions are available from the table.
For instance, QFACT values for commercial land use would be 7.19 mg/g
for BOD5, 0.06 mg/g for total phosphorus, 0.000 02 mg/g for Hg, and
0.036 910 6 MPN/g for fecal coliforms. Direct loading rates could be computed
for each constituent as an alternative. For example, with KALC = 1 for BOD5
and KACGUT = 0, parameter QFACT(3,K) would equal 2.2 x 0.007 19 or
0.015 8 lb/(100-ft curb - day).
It must be stressed once again that the generalized buildup data of Table 20-23 are merely informational and are never a substitute for local sampling
or even a calibration using measured concentrations. They may serve as a first
trial value for a calibration, however.
522
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Table 20-23a Nationwide Data on Linear Dust and Dirt Buildup Rates and
on Pollutant Fractions (after Manning et al., 1977, pp. 138-140.)
Pollutant
Single Family Residential
Multiple
Family
Residential
Commercial
Industrial
Mean
Range
35 (10)
19-96 (5-27)
181 (51)
72-326 (80-151)
No. of Obs
Mean
60
--
109 (31)
62-153 (1743)
93
--
126
134 (38)
325 (92)
284-536
(80-151)
55
--
Range
No. of Obs
Mean
--182 (51)
--154 (44)
35-365 (10-103)
22
45 (13)
--288 (81)
Range
8-770
(2-217)
8
113 (32)
8-770
(2-217)
101
3,370
3-260
(1-73)
10
116 (47)
3-365 (1-103)
No. of Obs
Mean
3-950
(1-268)
14
62 (17)
3-950
(1-268)
74
5,260
158
7,190
4-1,500
(1-423)
12
319 (90)
4-1,500
(1-423)
67
2,920
Range
No. of Obs
Mean
1,720-9,430
59
39,250
2,030-6,320
93
41,970
1,280-14,540
102
61,730
2,820-2,950
56
25,080
Range
18,30072,800
59
460
325-525
59
------------49
20-109
59
-----
24,60061,300
93
550
356-961
93
------------58
20-73
93
-----
24,800-498,410
23,00031,800
38
430
410-431
38
------------26
14-30
38
-----
--
--
Dust & Dirt
Accumul’n
lb/curbmi/day
kg/curbkm/day
Chicago(1)
Washington(2)
MultiCity(3)
All Data
BOD
mg/kg
COD
mg/kg
No. of Obs
Mean
Range
Asbestos
No. of
Mean
Range
No. of
Mean
Range
No. of
Mean
Range
No. of
Mean
Range
No. of
Mean
Range
No. of
Mean
Range
No. of
Mean
Range
No. of
Mean
Fibers/lb
Range
Total N-N
(mg/kg)
Kjeldahl N
(mg/kg)
NO3
(mg/kg)
NO2-N
(mg/kg)
Total PO4
(mg/kg)
PO4-P
(mg/kg)
Chlorides
(mg/kg)
Obs
Obs
Obs
Obs
Obs
Obs
Obs
Obs
102
420
323-480
80
640
230-1,790
22
24
10-35
21
0
0
15
170
90-340
21
60
0-142
101
220
100-370
22
57.2x106
(126x100)
0-172.5x106
--
523
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
(fibers/kg)
Ag
(mg/kg)
As
(mg/kg)
Ba
(mg/kg)
CD
(mg/kg)
Cr
(mg/kg)
Cu
(mg/kg)
Fe
(mg/kg)
No. of
Mean
Range
No. of
Mean
Range
No. of
Mean
Range
No. of
Mean
Range
No. of
Mean
Range
No. of
Mean
Range
No. of
Mean
Range
Obs
Obs
Obs
Obs
Obs
Obs
Obs
Fecal Coli
No./gram
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Geo.Mean
Range
No. of Obs
Geo.Mean
Range
Total Coli
No./gram
No. of Obs
Geo.Mean
Range
Mg
(mg/kg)
Mn
(mg/kg)
Ni
(mg/kg)
Pb
(mg/kg)
Sb
(mg/kg)
Se
(mg/kg)
Sn
(mg/kg)
Sr
(mg/kg)
Zn
(mg/kg)
Fecal Strep
No./gram
No. of Obs
----------3.3
0-8.8
14
200
111-325
14
91
33-150
14
21,280
11,00048,000
14
---450
250-700
14
38
0-120
14
1,570
220-5,700
14
---------32
5-110
14
310
110-810
14
---82,500
26-130,000
65
891,000
25,0003,000,000
65
--
------2.7
0.3-6.0
8
180
75-325
8
73
34-170
8
18,500
11,00025,000
8
---340
230-450
8
18
0-80
8
1,980
470-3,700
8
---------18
12-24
8
280
210—490
8
---38,800
1,5001,000,000
96
1,900,000
80,0005,600,000
97
(0-380x106)
16
200
0-600
3
0
0
3
38
0-80
8
3.9
0-9.3
22
140
10-430
30
95
25-810
30
21,580
5,000-44,000
10
0.02
0-0.1
6
380
160-540
10
94
6-170
30
2,330
0-7,600
29
54
50-60
3
0
0
3
17
0-50
3
17
7-38
10
690
90-3,040
30
370
44-2,420
17
36,900
140-970,000
84
1,000,000
18,000-3,500,000
85
----------3.6
0.3-11.0
13
240
159-335
13
87
32-170
13
22,540
14,00043,000
13
---430
240-620
13
44
1-120
13
1,590
260-3,500
13
---------13
0-24
13
280
140-450
13
---30,700
67-530,000
42
419,000
27,0002,600,000
43
524
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Table 20-23b
Pollutant
Dust and Dirt Accumulation
lb/curb-mi/day (kg/curb-km/day)
Chicago(1)
Washington(2)
Multi-City(3)
All Data
BOD mg/kg
COD mg/kg
Total N-N
(mg/kg)
Kjeldahl N
(mg/kg)
NO3
(mg/kg)
NO2-N
(mg/kg)
Total PO4
(mg/kg)
PO4-P
(mg/kg)
Chlorides
(mg/kg)
Asbestos
Fibers/lb (fibers/kg)
Ag
(mg/kg)
As
(mg/kg)
Ba
(mg/kg)
All Data
Pollutant
CD
All Data
3.1
158 (44)
19-536 (5-15)
334
134 (38)
35-365 (10-103)
22
175 (49)
3-1,500 (1-423)
44
159 (45)
3-1,500 (1-423)
400
5,030
1,288-14,540
292
46,120
18,300-498,410
292
480
323-480
270
640
230-1,790
22
24
10-35
21
15
0
15
170
90-340
21
53
0-142
291
220
100-370
22
57.2x106 (126x106)
0-172.5x106 (0-380x106)
16
200
0-600
3
0
0
3
38
0-80
(mg/kg)
0-11.0
57
180
10-430
65
90
25-810
65
21,220
5,000-48,000
45
0.02
0-0.1
6
410
160-700
45
62
1-170
65
1,970
0-7,600
64
54
50-60
3
0
0
3
17
0-50
3
21
1-110
45
470
90-3,040
65
370
44-2,420
17
94,700
26-1,000,000
287
1,070,000
18,000-5,600,000
290
Cr
(mg/kg)
Cu
(mg/kg)
Fe
(mg/kg)
Mg
(mg/kg)
Mn
(mg/kg)
Ni
(mg/kg)
Pb
(mg/kg)
Sb
(mg/kg)
Se
(mg/kg)
Sn
(mg/kg)
Sr
(mg/kg)
Zn
(mg/kg)
Fecal Strep
No./gram
Fecal Coli
No./gram
Total Coli
No./gram
In this respect it is important to point out that concentrations and loads computed by SWMM are usually linearly proportional to buildup rates. If twice the
quantity is available at the beginning of a storm, the concentrations and loads
will be doubled. Calibration is probably easiest with linear buildup parameters,
but it depends on the rate at which the limiting buildup (i.e. DDLIM or
QFACT(1,K), is approached). If the limiting value is reached during the interval
between most storms, then calibration using it will also have almost a linear effect on concentrations and loads. If is apparent that the interaction between the
interevent time of storms (i.e. dry days) and the effect of buildup is accomplished using the rate constants DDPOW and DDFACT for dust and dirt and
525
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
QFACT(2,K) and QFACT(3,K) for constituents. This is discussed further subsequently under Overall Sensitivity to Quality Parameters.
Almost all of the above loading data are from samples of storm water, not
combined sewage. Although some loadings may be inferred from concentration
measurements of combined sewage (e.g. Huber et al., 1981a; Wallace, 1980),
they are not directly related to most surface accumulation measurements. Thus,
if buildup data alone are used in combined sewer areas, buildup rates will probably be multiples of the values listed, for example in Table 20-22. The proper
factor will most easily be found by calibration with local concentration measurements.
When snowmelt is simulated, some constituents may be used to represent deicing chemicals; several common roadway salts are listed in Figure 20-10.
Applications of such chemicals varies depending upon depth of snowfall and
local practice. Loading rates are discussed in SWMM Snowmelt Routines and in
other references (Proctor and Redfern and J.F. MacLaren, 1976a, 1976b; Field et
al., 1973; Richardson et al., 1974; Ontario Ministry of the Environment, 1974).
For instance, guidelines of the type proposed by Richardson et al. (1974) are
used in many cities and are given in Table 20-24. Summaries are also given by
Manning et al. (1977) and Lager et al. (1977a).
Table 20-24 Guidelines for Chemical Application Rates for Snow Control.
(Richardson et al., 1974.)
WEATHER CONDITIONS
Temp.
Pavement
Condition
Precipitation
30°F and
above
Wet
Snow
25-30°F
20-25°F
15-20°F
Below
15°F
APPLICATION RATE (Pounds of material per mile of 2-lane road or 2lanes of divided)
Low- and High- Two and Three- Two-Lane
Instructions
Speed Multilane Lane Primary
Secondary
Divided
300 salt
300 salt
300 salt
Wait at least 0.5 hour
before plowing
200 salt
200 salt
200 salt
Reapply as necessary
Sleet or
Freezing Rain
Snow or Sleet initial at 400
salt, repeat at
200 salt
Freezing Rain initial at 300
salt, repeat at
200 salt
Snow or Sleet initial at 500
salt, repeat at
250 salt
Freezing Rain initial at 400
salt, repeat at
300 salt
Dry Snow
plow
Initial at 400
salt, repeat at
200 salt
Initial at 300
salt, repeat at
200 salt
Initial at 500
salt, repeat at
250 salt
Initial at 400
salt, repeat at
300 salt
Plow
initial at 400
salt, repeat at
200 salt
initial at 300
salt, repeat at
200 salt
initial at 500
salt, repeat at
250 salt
initial at 400
salt, repeat at
300 salt
Plow
Wet
Wet Snow or 500 of 3:1
Sleet
Salt/Calcium
Chloride
500 of 3:1
Salt/Calcium
Chloride
1200 of 5:1
Sand
dry
Dry Snow
Plow
Plow
Wet
Wet
Dry
plow
Wait at least 0.5 hour
before plowing; repeat
Repeat as necessary
Wait about 0.75 hour
before plowing; repeat
Repeat as necessary
Treat hazardous areas
with 1200 of 20:1
Sand/Salt
Wait about one hour
before plowing; continue plowing until
storm ends; then repeat
application
Treat hazardous area
with 1200 of 20:1
Sand/Salt
526
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Since for most deicing chemicals the principal source is direct application
during snow events, there is little or no buildup during snow-free periods.
20.8.3 Washoff
Definition
Washoff is the process of erosion or solution of constituents from a subcatchment surface during a period of runoff. If the water depth is more than a few
millimeters, processes of erosion may be described by sediment transport theory
in which the mass flow rate of sediment is proportional to flow and bottom shear
stress, and a critical shear stress can be used to determine incipient motion of a
particle resting on the bottom of a stream channel, e.g. Graf (1971), Vanoni
(1975). Such a mechanism might apply over pervious areas and in street gutters
and larger channels. For thin overland flow, however, rainfall energy can also
cause particle detachment and motion. This effect is often incorporated into predictive methods for erosion from pervious areas (Wischmeier and Smith, 1958)
and may also apply to washoff from impervious surfaces, although in this latter
case, the effect of a limited supply (buildup) of the material must be considered.
Washoff Formulation
Ammon (1979) reviews several theoretical approaches for urban runoff washoff
and concludes that although the sediment transport based theory is attractive, it
is often insufficient in practice because of lack of data for parameter (e.g. shear
stress) evaluation, sensitivity to time step and discretization and because simpler
methods usually work as well (still with some theoretical basis) and are usually
able to duplicate observed washoff phenomena. Among the latter, the most often
cited results are those of Sartor and Boyd (1972), in which constituents were
flushed from streets using a sprinkler system.
Related Buildup-Washoff Studies
Several studies are directly related to the preceding discussions of the SWMM
water quality routines. Some of these have been mentioned previously in the
text, but it is worthwhile pointing out those that are particularly relevant to
SWMM modeling as opposed to data collection and analysis (although most of
the studies do, of course, utilize data as well). The following discussion is by no
means exhaustive but does include several studies that have simulated water
quality using buildup-washoff mechanisms, rating curves or both.
The U.S. Geological Survey (USGS) has performed comprehensive urban
hydrologic studies from both a data collection and modeling point of view. For
example, their South Florida urban runoff data are described and referenced in
the EPA Urban Rainfall-Runoff Quality Data Base (Huber et al., 1981a). Urban
rainfall-runoff quantity may be simulated with the USGS distributed Routing
Rainfall-Runoff Model (Dawdy et al., 1978; Alley et al., 1980a) which includes
simulation of water quality. This is accomplished using a separate program that
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
527
uses the quantity model results as input. These efforts are described by Alley
(1980) and Alley et al. (1980b). Alley (1981) also provides a method for optimal
estimation of washoff parameters using measured data. The USGS procedures
are based in part upon earlier work of Ellis and Sutherland (1979). These four
references all discuss the use of the original SWMM buildup-washoff equations.
An application of SWMM to two Denver catchments during which buildupwashoff parameters were calibrated is described by Ellis (1978) and Alley and
Ellis (1979).
Work at the University of Massachusetts has developed procedures for calibration of SWMM quality (Jewell et al., 1978a) and for determination of
appropriate washoff relationships (Jewell et al., 1978b). Jewell et al. (1980) and
Jewell and Adrian (1981) reviewed the supporting data for buildup-washoff relationships and advocate using local data to develop site specific equations for
buildup and washoff. Most of their suggested forms could be simulated using
the available functional forms in SWMM.
Since several other models use quality formulations similar to those of
SWMM, their documentation provides insight into choosing proper SWMM
parameters. In particular, most of the STORM calibration procedures (Roesner
et al., 1974, HEC, 1977a,b) can be applied also to SWMM. Inclusion of water
quality simulation in ILLUDAS (Terstriep et al., 1978; Han and Delleur, 1979)
also is based on SWMM procedures. Finally, modified SWMM routines have
been used to simulate water quality in Houston (Diniz, 1978; Bedient et al.,
1978).
Rating Curve
As discussed above, the washoff calculations may be avoided and load rates
computed for each subcatchment at each time step by a rating curve method.
POFF = RCOEF ⋅ WFLOW WASHPO
(20-126)
WFLOW = subcatchment runoff, cfs, (or m3/sec for metric input),
POFF = constituent load washed off at time, t, quantity/sec
(e.g. mg/sec),
RCOEF = coefficient that includes correct units conversion, and
WASHPO = exponent.
Parameters RCOEF and WASHPO are entered for a particular constituent.
where
20.8.4 Street Cleaning
Street cleaning is performed in most urban areas for control of solids and trash
deposited along street gutters. Although it has long been assumed that street
cleaning has a beneficial effect upon the quality of urban runoff, until recently,
few data have been available to quantify this effect. Unless performed on a daily
528
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
basis, EPA Nationwide Urban Runoff Program (NURP) studies generally found
little improvement of runoff quality by street sweeping (EPA, 1983b).
The most elaborate studies are probably those of Pitt (1979, 1985) in which
street surface loadings were carefully monitored along with runoff quality in
order to determine the effectiveness of street cleaning. In San Jose, California
(Pitt, 1979) frequent street cleaning on smooth asphalt surfaces (once or twice
per day) can remove up to 50% of the total solids and heavy metal yields of urban runoff. Under more typical cleaning programs (once or twice a month), less
than 5% of the total solids and heavy metals in the runoff are removed. Organics
and nutrients in the runoff cannot be effectively controlled by intensive street
cleaning (typically much less than 10% removal, even for daily cleaning). This
is because the latter originate primarily in runoff and erosion from off-street areas during storms. In Bellevue, Washington (Pitt, 1985) similar conclusions were
reached, with a maximum projected effectiveness for pollutant removal from
runoff of about 10%.
The removal effectiveness of street cleaning depends upon many factors such
as the type of sweeper, whether flushing is included, the presence of parked cars,
the quantity of total solids, the constituent being considered, and the relative
frequency of rainfall events. Obviously, if street sweeping is performed infrequently in relation to rainfall events, it will not be effective. Removal
efficiencies for several constituents are shown in Table 20-25 (Pitt, 1979).
Clearly, efficiencies are greater for constituents that behave as particulates.
Within the SWMM, street cleaning (usually assumed to be sweeping) is performed (if desired) prior to the beginning of the first storm event and between
storm events (for continuous simulation). Unless initial constituent loads are
input (or unless a rating curve is used) a mini simulation is performed for each
constituent during the dry days prior to a storm during which buildup and
sweeping are modeled. Starting with zero initial load, buildup occurs according
to the method chosen. Street sweeping occurs at intervals of CLFREQ days.
(During continuous simulation, sweeping occurs between storms based on intervals calculated using dry time steps only. A dry time step does not have runoff
greater than 0.0005 in./h (0.013 mm/hr), nor is snow present on the impervious
area of the catchment. Removal occurs such that the fraction of constituent surface load, PSHED, remaining on the surface is
REMAIN = 1.0 ! AVSWP(J )" REFF(K )
where
(20-127)
REMAIN = fraction of constituent (or dust and dirt) load
remaining on catchment surface,
AVSWP = availability factor (fraction) for land use J, and
REFF = removal efficiency (fraction) for constituent
K.
529
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
Table 20-26 Removal Efficiencies from Street Cleaner Path for Various
Street Cleaning Programs.* (Pitt, 1979)
Street Cleaning Program
Total BOD5 COD
and Street Surface Loading Solids
Conditions
Vacuum Street Cleaner
31
24
16
1 pass; 20-200
lb/curb mile total solids
2 passes
45
35
22
3 passes
53
41
27
Vacuum Street Cleaner
37
29
21
1 pass; 200-1,000
lb/curb mile total solids
2 passes
51
42
29
3 passes
58
47
35
Vacuum Street Cleaner
48
38
33
1 pass; 1000-10,000
lb/curb mile total solids
2 passes
60
50
42
3 passes
63
52
44
Mechanical Street Cleaner
54
40
31
1 pass; 180-1800
lb/curb mile total solids
2 passes
75
58
48
3 passes
85
69
59
Flusher
30
(a)
(a)
Mechanical Street Cleaner
80
(b)
(b)
followed by a flusher
Street Cleaning Program
and Street Surface
Loading Conditions
Vacuum Street Cleaner
1 pass; 20-200
lb/curb mile total solids
2 passes
3 passes
Vacuum Street Cleaner
1 pass; 200-1,000
lb/curb mile total solids
2 passes
3 passes
Vacuum Street Cleaner
1 pass; 1000-10,000
lb/curb mile total solids
2 passes
3 passes
Mechanical Street
Cleaner
1 pass; 180-1800
lb/curb mile total solids
2 passes
3 passes
Flusher
Mechanical Street
Cleaner followed by a
flusher
(a)
(b)
KN
PO4
Pesticides
Cd
Sr
Cu
Ni
Cr
26
8
33
23
27
30
37
34
37
45
31
12
14
12
50
59
40
34
40
30
35
48
34
45
52
36
54
63
43
53
60
42
46
51
43
17
20
20
59
67
57
43
50
45
48
53
44
49
59
49
59
68
55
60
66
53
54
57
40
25
26
20
72
75
40
57
60
28
55
58
40
63
66
38
70
73
45
68
72
44
58
69
(a)
(b)
35
46
(a)
(b)
60
72
(a)
(b)
45
57
(a)
(b)
59
70
(a)
(b)
58
69
(a)
(b)
65
76
(a)
(b)
64
75
(a)
(b)
Zn
Mn
Pb
Fe
34
37
40
40
52
59
41
56
65
45
59
70
49
59
68
59
59
67
55
63
70
58
68
76
62
68
75
63
69
73
43
72
76
47
79
83
44
77
82
49
64
75
(a)
(b)
64
79
(a)
(b)
65
77
(a)
(b)
71
82
(a)
(b)
15-40% estimated
35-100% estimated
*These removal values assume all the pollutants would lie within the cleaner path (0 to 8 ft. from the
curb)
530
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
The removal efficiency differs for each constituent as seen in Table 20-26,
from which estimates of REFF may be obtained. The effect of multiple passes
must be included in the value of REFF. During the mini simulation that occurs
prior to the initial storm or start of simulation dust and dirt is also removed during sweeping using an efficiency REFFDD. It is probably reasonable to assume
that dust and dirt is removed similarly to the total solids of Table 20-26. A
non-linear effect is exhibited in Table 20-26, in which efficiencies tend to increase as the total solids on the street surface increase. The SWMMalgorithm
does not duplicate this effect. Rather, the same fraction is removed during each
sweeping.
The availability factor, AVSWP, is intended to account for the fraction of the
catchment area that is actually sweepable. For instance, Heaney and Nix (1977)
demonstrate that total imperviousness increases faster as a function of population density than does imperviousness due to streets only. Thus, the ratio of
street surface to total imperviousness is one measure of the availability factor,
and their relationship is
AVSWP = 0.6 ⋅ PDd −0.2 , Pd > 0.1
where
(20-128)
AVSWP = availability factor, fraction, and
PDd = population density over developed area,
persons/ac [persons/ha].
Such a relationship is reasonably a function of land use. Although a value of
AVSWP must be entered for each land use, the equation of Heaney and Nix
(1977) was developed only for an overall urban area. Thus, extrapolation to specific land uses should be done only with caution, but equation 20-128 is
probably suitable for use on a large, aggregated catchment, such as might be
used for continuous simulation.
An alternative approach may be found in Pitt (1979) in which the issue of
parked cars is dealt with directly. Pitt shows that the percentage of curb left uncleaned is essentially equal to the percentage of curb occupied by parked cars.
Thus, if typically 40% of the curb (length) is occupied by parked cars, the availability factor would be about 0.60. In many cities, parking restrictions on street
cleaning days limit the length of curb occupied during sweeping.
Parameter DSLCL merely establishes the proper time sequence for the mini
simulation prior to the start of the storm (or continuous simulation). A hypothetical sequence of linear buildup and street sweeping prior to a storm is sketched
in Figure 20-36.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
531
Figure 20-36 Hypothetical time sequence of linear buildup and street
sweeping.
Eventually an equilibrium between buildup and sweeping will occur. For the
example shown in Figure 20-36, this is when the removal, 0.32.PSHED, equals
the weekly buildup, 0.3 x 106.7, or PSHED = 6.56 x 106 mg. If sweeping is
scheduled for the day of the start of the storm (DSCL = CLFREQ) it does not
occur. (An exception would be when the first day of a continuous simulation is a
dry day. Sweeping would then occur during the first time step.)
The SWMM user should bear in mind that although the model assumes constituents to build up over the entire subcatchment surface, the surface load is
simply a lumped total in, say, mg and there are no spatial effects on buildup or
washoff. Hence, if it is assumed that a particular constituent originates only on
the impervious portion of the catchment, loading rates and parameters can be
scaled accordingly. Likewise, AVSWP can be determined based on the characterization of only the impervious areas described above. However, if a
constituent originates over both the pervious and impervious area of the subcatchment (e.g. nutrients and organics) the removal efficiency, REFF, should be
reduced by the average ratio of impervious to total area since it is independent of
land type. The availability factor, AVSWP, differs for individual land uses but
has the same effect on all constituents.
532
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
20.8.5 Catchbasins
Background
Catchbasins are found in a large number of cities. They were originally installed
at stormwater inlets to combined sewers to prevent sewer clogging by trapping
coarse debris and solids and to prevent emanation of odors from the sewer by
providing a water seal. There is no standard design for catchbasins; representative designs are shown in Figure 20-37.
Figure 20-37 Representative catchbasin designs. (After Lager et al.,
1977b, p.12.)
The purpose of the deep well or sump is to trap solids by sedimentation prior
to stormwater entry into the sewer, which distinguishes catchbasins from
stormwater inlets. The volume of the sump varies considerably with design,
ranging from 2.8 to 78 ft3 (0.08 - 2.21 m3). The volume is typically reduced by a
large quantity of solids trapped in the sump, often by more than 50%.
A comprehensive examination of catchbasins and their effectiveness for pollutant control is presented by Lager et al. (1977b). They conclude that:
Existing catchbasins exhibit mixed performance with respect to pollutant
control. The trapped liquid purged from catchbasins to the sewers during
each storm generally has a high pollution content that contributes to the intensification of first-flush load-ings. Countering this negative impact is the
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
533
removal of pollutants associated with the solids retained in, and subsequently
cleaned from, the basin.
In fact according to their data, there is unlikely to be much removal (treatment) at all in most cities because of infrequent maintenance; the median
cleaning frequency in 1973 was once per year. Without such maintenance, solids
accumulate in the sump until there is little removal effectiveness, even for large
particles. Lager et al. (1977b) conclude that, with the possible exception of total
solids and heavy metals, catchbasins are of limited usefulness for pollution
abatement, both because of their ineffectiveness and because of their high
maintenance costs. More recently, Pitt (1985) found that semi-annual catchbasin
cleaning could reduce solids loads by up to 25%. However, their treatment potential is not modeled in SWMM. (If it is significant in a given city, surface
loadings could be correspondingly reduced.)
Modeling Approach
The potential for a first flush of catchbasin material is simulated by assuming
that the sump contains at the beginning of a storm a constituent load (e.g. mass,
in mg, for NDIM = 0) given by:
PBASIN = CBVOL ! BASINS !CBFACT ! FACT 3
where
(20-129)
PBASIN = subcatchment constituent load in catchbasins
at beginning of storm, mg for NDIM = 0,
CBVOL = individual catchbasin volume of sump, reduced by quantity of stored solids, if known,
ft3,
BASINS = number of basins in subcatchment,
CBFACT = constituent concentration in basin at beginning of storm, mg/l for NDIM = 0, and
FACT3 = conversion factor, equals 28.3 l/ft3 for NDIM
= 0.
Parameter CBVOL is entered as an average for the entire catchment. The
number of basins in each subcatchment, BASINS, is entered. Numbers can be
obtained knowing the general basin density for the catchment in lieu of the more
tedious method of counting every one. Constituent concentrations, CBFACT,
are entered and should, of course, be measured in the catchment under study.
Literature values are few. Samples from twelve San Francisco catchbasins (Sartor and Boyd, 1972) were characterized by Lager et al. (1977b) by “casting out
the extremes and averaging,” resulting in the values shown in Table 20-27. Concentrations from ten catchbasins in a residential catchment in Bellevue,
Washington are also shown (Pitt, 1985). The values for COD and Total-N are
consistent with a few samples reported by Sartor and Boyd (1972) for Baltimore
and Milwaukee, although the phosphates concentration in those two cities was
somewhat higher, 1.1 - 2.2 mg/l. The concentration of BOD5 in seven Chicago
catchbasins was measured by APWA (1969). The average concentration for five
534
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
commercial area basins was 126 mg/l, ranging from 35 to 225 mg/l. Two residential area basins yielded BOD5 concentrations of 50 and 85 mg/l.
Table 20-27. Constituent Concentrations in Catchbasins
City Constituent
City
San Francisco
(Sartor and Boyd,
1972)
Bellevue (Pitt,
1985)
Constituent
COD
BOD5
Total-N
Total-P
COD
Total Solids
TKN
Total-P
Pb
Zn
Average
6,400
110
8
0.2
59
67
2.1
0.95
0.14
0.19
Range
153 – 143,000
5 - 1,500
0.5 – 33
< 0.2 - 0.3
20 – 244
34 – 272
< 0.5 - 5.6
0.078 - 6.9
0.05 - 0.45
0.033 - 1.19
Suspended solids (SS) concentrations can be expected to be high for particle
sizes less than about 0.25 mm, on the basis of flushing tests (Sartor and Boyd,
1972; Lager et al., 1977b). Initial suspended and total solids concentrations of
several thousand mg/l are probably justified, although measurements by Waller
(1971) during storms in four residential catchbasins in Halifax indicate SS concentrations in a range of 42 to 305 mg/l. Pitt (1985) provides a particle size
distribution for the constituents listed in Table 20-27.
Flushing of stored constituents from catchbasin sumps is based on tests conducted by APWA (1969) in which salt was used as a tracer and its rate of
flushing observed. Data and fitted equations are shown in Figure 20-38. The
basin behaves approximately as a completely mixed tank in which
dPBASIN
WFLOW
=!
" PBASIN
dt
k " BASINS
(20-130)
where
PBASIN = constituent load remaining in the catchbasin
as a function of time, e.g. mg for NDIM = 0,
WFLOW = flow through the basin (runoff from the subcatchment), cfs,
BASINS = volume of catchbasin sump, ft3, and
k = constant to be determined from flushing tests.
When the flow rate is constant, equation 20-130 integrates to
PBASIN = PBASIN o ! e
"
WFLOW
!t
k!BASINS
(20-131)
where
PBASINo = initial catchbasin load.
If complete mixing occurs, k = 1. For the Chicago tests this did not quite occur, as seen in Figure 20-38. The original SWMM version (Metcalf and Eddy et
al., 19761a) used k = 1.6, but this does not give the best-fit line. Rather, a k value of 1.3 is consistent with a least squares fit through the data points and is used
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
535
in this version of SWMM. (However, the difference is probably undetectable in
a simulation.)
Figure 20-38 Catchbasin flushing characteristics. Data are from APWA
(1969).
During a runoff event, equation 20-130 is used to calculate the load rate,
dPBASIN/dt, at each time step. (Parameter BASINS represents the total catchbasin volume for the subcatchment.) The remaining catchbasin load is then
computed by multiplying the load rate by DELT and subtracting from PBASIN.
This crude Euler integrations is justified because of: the weakness of field data
and mixing assumptions; the necessity for an additional array and computation
time for a more sophisticated approximation; and the insensitivity of most simulations to catchbasin flushing. The latter point will be discussed further
subsequently.
Regeneration of Catchbasin Loads
During continuous simulation, catchbasin loads are regenerated to their original
values, PBASINo, at a rate PBASINo/DRYBSN (e.g. mg/day) where DRYBSN
is the time required for complete regeneration from a zero load. No data are
available herein to establish a value for DRYBSN, but it is likely that catchbasins are at full strength after only a few days of dry weather.
Effect on Simulation
It is the experience of the authors of this report that catchbasins have a negligible effect on most simulation results. Typical drainage areas served by
catchbasins range from 2.15 to 5.05 ac/basin (0.85 to 2.05 ha/basin) in the U.S.
(Lager et al., 1977b). Unless the area served is low, surface loadings tend to
overwhelm those from catchbasins. Although they do contribute to a first flush
effect, the most important task in most simulations is to obtain a proper total
536
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
storm load, to which catchbasins are seldom strong contributors. Hence, excessive effort to pin down catchbasin simulation parameters is seldom justified.
20.8.6 Constituent Fractions
Background
As previously discussed, the original SWMM quality routines were based on the
1969 APWA study in Chicago (APWA, 1969). A particular aspect of that study
that led to modifications to the first buildup-washoff formulation was that the
Chicago quality data (e.g. Table 20-18) were reported for the soluble fraction
only (i.e. the samples were filtered prior to chemical analysis). Hence, they
could not represent the total content of, say, BOD5 in the stormwater. In calibration of SWMM in San Francisco and Cincinnati, 5% of predicted suspended
solids was added to BOD5 to account for the insoluble fraction. This provided a
reasonable BOD5 calibration in both cities.
The Version II release of SWMM (Huber et al., 1975) followed the STORM
model (Roesner et al., 1974) and added to BOD5, N and PO4 fractions of both
suspended solids and settleable solids. Adding a fraction from settleable solids is
double counting, however, since it is no more than a fraction of suspended solids
itself. Furthermore, all the fractions in SWMM and STORM were basically just
assumed from calibration exercises as opposed to being measured from field
samples.
Agricultural models, such as NPS (Donigian and Crawford, 1976), ARM
(Donigian et al., 1977) and HSPF (Johanson et al., 1980) also relate other constituent mass load rates and concentrations to that of solids, usually sediment
predicted by an erosion equation. The ratio of constituent to solids is then called
a potency factor and for some constituents is the only means by which their concentrations are predicted. The approach works well when constituents are
transported in solid form, either as particulates or by adsorption onto soil particles. This approach can also be used in SWMM. For instance, one constituent
could represent solids and be predicted by any of the means available (i.e.
buildup-washoff, rating curve, Universal Soil Loss Equation). Other constituents
could then be treated simply as a fraction, F1, of solids. The fractions (potency
factors) can be entered. As a refinement, two or more constituents could represent solids in different particle size ranges, and fractions of each summed to
predict other constituents. Again, this approach will not work well for constituents that are transported primarily in a dissolved state, e.g. NO3.
Available Information
In an effort to evaluate potency factors for various constituents in both urban
and agricultural runoff, Zison (1980) examined available data and developed
regression relationships as a function of suspended solids and other parameters.
His only urban catchments were three from Seattle, taken from the Urban Rainfall-Runoff-Quality Data Base (Huber et al., 1981a), for which several water
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
537
quality and storm event parameters were available. Unfortunately, statistically
meaningful results could only be obtained using log-transformed data, and simple fractions of the type required for input are seldom reported. Zison (1980)
acknowledged this and suggested that model modifications might be made or
piecewise-linear approximations made to the power function relationship. In any
event, Zison related the total constituent concentration (not just the nonsoluble
portion) to other parameters. Hence, for their use in SWMM the
buildup-washoff portion would need to be zeroed out (easily accomplished), as
suggested earlier.
Other reports also provide some insight as to potential values for the constituent fractions. For instance, Sartor and Boyd (1972), Shaheen (1975) and
Manning et al. (1977) report particle size distributions for several constituents.
However, the distributions refer principally to fractions of constituents appearing as dust and dirt, not to fractions of total concentration, soluble plus
nonsoluble. Finally, Pitt and Amy (1973) give fractions (and surface loadings)
for heavy metals.
If constituent fractions are used in SWMM, local samples should identify the
soluble (filterable) and nonsoluble fractions for the constituents of interest. Alternatively, the fractions may be avoided altogether by treating the
buildup-washoff or rating curve approach as one for the total concentration, thus
eliminating the need to break constituents into more than one form.
Effect in SWMM
The fractions entered act only in one direction. That is, nothing is subtracted
from, say, suspended solids if it is a constituent that contributes to others. When
the fractions are used, they can contribute significantly to the concentration of a
constituent. For instance, if 5% of suspended solids is added to BOD5, high SS
concentrations will insure somewhat high BOD5 concentrations, event if BOD5
loadings are small.
Units conversions must be accounted for in the fractions. For instance, if a
fraction of SS is added to total coliforms, units for F1 would be MPN per mg of
SS. In general, F1 has units of the quantity of KTO (e.g. MPN) per quantity of
constituent KFROM (e.g. mg).
20.8.7 Precipitation Contributions
Precipitation Chemistry
There is now considerable public awareness of the fact that precipitation is by
no means pure and does not have characteristics of distilled water. Low pH (acid
rain) is the best known parameter but many substances can also be found in precipitation, including organics, solids, nutrients, metals and pesticides. Compared
to surface sources, rainfall is probably an important contributor mainly of some
nutrients, although it may contribute substantially to other constituents as well.
In particular, Kluesener and Lee (1974) found ammonia levels in rainfall higher
538
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
than in runoff in a residential catchment in Madison, Wisconsin; rainfall nitrate
accounted for 20% to 90% of the nitrate in stormwater runoff to Lake Wingra.
Mattraw and Sherwood (1977) report similar findings for nitrate and total nitrogen for a residential area near Fort Lauderdale, Florida. Data from the latter
study are presented in Table 20-28 in which rainfall may be seen to be an important contributor to all nitrogen forms, plus COD, although the instance of a
higher COD value in rainfall than in runoff is probably anomalous.
Table 20-28 Rainfall and Runoff Concentrations For a Residential Area
Near Fort Lauderdale, Florida (after Mattraw and Sherwood, 1977)
Rainfall, in.
Runoff, in.
Concentration (mg/l):
Total N, rainfall
Total N, runoff
NO3-N, rainfall
NO3-N, runoff
Org.-N, rainfall
Org.-N, runoff
NH3-N, rainfall
NH3-N, runoff
Total P, rainfall
Total P, runoff
COD, rainfall
COD, runoff
8/23/75
1.01
0.060
Storm
9/17/75
0.55
0.012
9/26/75
0.77
0.072
0.30
0.52
0.14
0.16
0.15
0.34
0.01
0.02
0.01
0.12
22
16
0.84
0.74
0.73
0.19
0.09
0.49
0.01
0.04
0.02
0.20
12
21
0.29
1.50
0.12
0.26
0.12
1.10
0.04
0.13
0.05
0.30
4
17
In addition to the two references first cited, Weibel et al. (1964, 1966) report
concentrations of constituents in Cincinnati rainfall (Table 20-20), and a summary is also given by Manning et al. (1977). Other data on rainfall chemistry
and loadings is given by Betson (1977), Hendry and Brezonik (1980), Novotny
and Kincaid (1981) and Randall et al. (1981). A comprehensive summary is presented by Brezonik (1975) from which it may be seen in Table 20-29 that there
is a wide range of concentrations observed in rainfall. Again, the most important
parameters relative to urban runoff are probably the various nitrogen forms.
Uttormark et al. (1974) provide annual nitrogen (and phosphorus) precipitation loading values (kg/ha-yr) for many cities regionally for the U.S. and
Canada. It should be remembered that considerable seasonal variability may
exist. These may be easily converted to precipitation concentrations required for
SWMM input if the local rainfall is known, since 10 x kg/ha-yr / cm/yr = mg/l.
For instance, annual NH3-N + NO3-N loadings at Miami are almost 2 kg/ha-yr,
and annual rainfall is 60 in. (152 cm). From the above, the inorganic nitrogen
concentration is 10 x 2/152 = 0.13 mg/l which compares quite favorably with the
sum of NH3-N and NO3-N concentrations for two of the three Ft. Lauderdale
storms given in Table 20-28. For a better breakdown of nitrogen forms, see Table 17 of Uttormark et al. (1974).
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
539
Table 20-29 Representative Concentrations in Rainfall.
Parameter
Acidity (pH)
Organics
BOD5, mg/L
COD, mg/L
TOC, mg/L
Inorg. C, mg/L
Color, PCU
Solids
Total Solids, mg/L
Suspended Solids, mg/L
Turbidity, JTU
Nutrients
Org. N, mg/L
NH3-N, mg/L
NO2-N, mg/L
NO3-N, mg/L
Total N, mg/L
Orthophosphorus, mg/L
Total P, mg/L
Pesticides, µg/L
Heavy Metals, µg/L
Lead, µg/L
a
Range for three storms
Ft. Lauderdalea (Mattraw
and Sherwood, 1977)
Cincinnatib (Weibel et al.,
1966)
4-22
1-3
0-2
5-10
16
18-24
2-10
4-7
Typical Range (Brezonik,
1975)
3-6
1-13
9-16
Few
13
0.09-0.15
0.01-0.04
0.00-0.01
0.12-0.73
0.29-0.84
0.01-0.03
0.01-0.05
0.58
1.27c
0.08
3-600
b
Average of 35 Storms
0.05-1.0
0.05-1.0
0.2-1.5
0.0-0.05
0.02-0.15
Few
Few
30-70
c
Sum of NH3-N, NO2 –N, NO3-N
Effect in SWMM
Constituent concentrations in precipitation can be entered. All runoff, including
snowmelt, is assumed to have at least this concentration, and the precipitation
load is calculated by multiplying this concentration by the runoff rate and adding
to the load already generated by other mechanisms. It may be inappropriate to
add a precipitation load to loads generated by a calibration of buildup-washoff
or rating curve parameters against measured runoff concentrations, since the
latter already reflect the sum of all contributions, land surface and otherwise.
But precipitation loads might well be included if starting with buildup-washoff
data from other sources. They also provide a simple means for imposing a constant concentration on any SWMM constituent.
For single event simulation, use of precipitation concentrations is a simple
way in which to account for the high concentrations of several constituents
found in snowpacks (Proctor and Redfern and James F. MacLaren, 1976b). It
would be inappropriate for continuous simulation, however, since such high
concentrations in runoff would not be expected to persist over the whole year.
If this is the only method used to simulate melt quality, however, a constant
predicted concentration will result. Also, caution should be used if simulating
particulates (e.g. suspended solids) or heavy metals since high concentrations in
a snowpack do not necessarily mean high concentrations in runoff, since the
material may rapidly settle during overland flow. For instance, the very high
lead concentrations (2 - 100 mg/l) found in snow windrows in urban areas are
greatly reduced in the melt runoff (0.05 - 0.95 mg/l), (Proctor and Redfern and
James F. Maclaren, 1976b).
540
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
20.8.8 Urban Erosion
Background
Erosion and sedimentation are often cited as a major problem related to urban
runoff. They not only contribute to degradation of land surfaces and soil loss but
also to adverse receiving water quality and sedimentation in channels and sewer
networks. Several ways exist to analyze erosion from the land surface (e.g.
Vanoni, 1975), the most sophisticated of which include calculations of the shear
stress exerted on soil particles by overland flow and/or the influence of rainfall
energy in dislodging them.
20.8.9 Subcatchment Quality Data
Introduction
As discussed earlier while describing buildup and washoff mechanisms, certain
quality parameters are unique to each subcatchment. These parameters are independent of the quantity parameter entered (except for subcatchment number, of
course) and are not required if no quality simulation is performed.
Land Use
Each subcatchment is assigned one of up to five defined land uses. Parameters
entered for an individual land use will then be used on the corresponding subcatchments.
20.8.10 Integrated Form of Complete Mixing Quality Routing
Quality routing SWMM through sediments has long been accomplished by assuming complete mixing within the conduit (link) in the manner of a
continuously stirred tank reactor (CSTR). It may easily be shown that negative
concentrations may be predicted if
Δt >
where
2V
Q
(20-132)
∆t = time step, sec,
V = average volume in the conduit or storage unit,
ft3, and
Q = average flow through the conduit or storage
unit, cfs.
This rarely causes a problem for storage unit simulation due to their large
volumes. But when long time steps (e.g. 1 hr) are used in SWMM instabilities
in the predicted concentrations may arise.
These may readily be avoided with minimal loss of accuracy by using the integrated form of the solution to the differential equation. The procedure is
described by Medina et al. (1981) and is outlined below as applied to SWMM.
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
541
The governing differential equation for a completely mixed volume is
dVC
dC
dV
=V
+C
= Qi Ci − QC − KVC + L
dt
dt
dt
(20-133)
where
C = concentration in effluent and in the mixed
volume, e.g. mg/L,
V = volume, ft3,
Qi = inflow rate, cfs,
Ci = concentration of influent, e.g. mg/L,
Q = outflow rate, cfs,
K = first order decay coefficient, sec-1, and
L = source (or sink) of pollutant to the mixed volume, mass/time, e.g. cfs.mg/L.
An analytical solution of this equation is seldom possible when Q, QI, CI, V
and L vary arbitrarily with time, as in the usual routing through conduits (links).
However, a simple solution is available to the ordinary, first order differential
equation with constant coefficients if parameters Q, QI, CI, V, L and dV/dt are
assumed to be constant over the solution time interval, t to t + ∆t. In practice,
average values over the time interval are used at each time step. Equation 20133 is then readily integrated over the time interval t to t + ∆t with
C ( 0 ) = C (t )
(20-134)
to yield
" Qi Ci + L
V
C ( t + !t ) = $
$$ DENOM
#
%
' 1( e( DENOM )!t + C ( t ) e( DENOM )!t
)
'' (
&
(20-135)
where
DENOM =
Q
1 ! dV $
+K + #
&
V
V " dt %
(20-136)
Thus, the concentration at the end of the time step is computed to be the sum
of the weighted inflow concentration and a decaying concentration from the
previous time step.
Equation 20-135 is used in SWMM and is completely stable with respect to
changes in ∆t. It does not reflect rapid changes in volume and flow as well as
the finite difference solution but it is updated at each time step. Given the many
other uncertainties of quality routing within the sewer system, it should be adequate.
542
Land Surface Phase: Theoretical Basis from … SWMM 4 RUNOFF
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