EPA/600/R-09/077

July 2009 

STORM WATER MANAGEMENT MODEL 

APPLICATIONS MANUAL 

By 

Jorge Gironás 

Larry A. Roesner 

Jennifer Davis 

Department of Civil and Environmental Engineering 

Colorado State University 

Fort Collins, CO 80523-1372 

Project Officer 

Lewis A. Rossman 

Water Supply and Water Resources Division 

National Risk Management Research Laboratory 

Cincinnati, OH 45268 

NATIONAL RISK MANAGEMENT RESEARCH LABORATORY 

OFFICE OF RESEARCH AND DEVELOPMENT 

U.S. ENVIRONMENTAL PROTECTION AGENCY 

CINCINNATI, OH 45268 
DISCLAIMER 

The information in this document has been funded wholly or in part by the U.S. 

Environmental Protection Agency (EPA). 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. 

ii 
FOREWORD 

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 

Stormwater Management Model is a computer program that can assess the impacts of 

such runoff and evaluate the effectiveness of mitigation strategies. This manual 

presents a number of worked-out examples that shows new users how to set up and 

apply SWMM to the most common types of stormwater management and design 

problems encountered in practice. 

Sally C. Gutierrez, Director 

National Risk Management Research Laboratory 

iii 
ABSTRACT 

The EPA Storm Water Management Model (SWMM) is a dynamic rainfall-runoff 

simulation model that computes runoff quantity and quality from primarily urban areas. 

This manual is a practical application guide for new SWMM users who have already 

had some previous training in hydrology and hydraulics. It contains nine worked-out 

examples that illustrate how SWMM can be used to model some of the most common 

types of stormwater management and design problems encountered in practice. These 

include: computing runoff for both pre- and post development conditions; analyzing the 

hydraulics of simple collection systems; designing a multi-purpose detention pond; 

modeling distributed low impact runoff controls; simulating the buildup, washoff, 

transport and treatment of stormwater pollutants; analyzing both dual drainage and 

combined sewer systems; and running long-term continuous simulations. Each example 

is accompanied by a complete SWMM input data file. 

iv 
Contents 

Foreword .......................................................................................... iii 

Abstract ............................................................................................ iv 

Figures ............................................................................................. vi 

Tables .............................................................................................. ix 

Acknowledgment ................................................................................. xi 

Introduction.................................................................................................................... 12 

Example 1. Post-Development Runoff ..................................................................... 15 

Example 2. Surface Drainage Hydraulics ................................................................. 35 

Example 3. Detention Pond Design .......................................................................... 50 

Example 4. Low Impact Development...................................................................... 69 

Example 5. Runoff Water Quality ............................................................................ 85 

Example 6. Runoff Treatment................................................................................. 103 

Example 7. Dual Drainage Systems........................................................................ 117 

Example 8. Combined Sewer Systems.................................................................... 132 

Example 9. Continuous Simulation......................................................................... 154 

References.................................................................................................................... 177 

v 
Figures 

Figure 1-1. Undeveloped site......................................................................................... 16 

Figure 1-2. Developed site............................................................................................. 16 

Figure 1-3. Idealized representation of a subcatchment ................................................ 17 

Figure 1-4. SWMM representation of the undeveloped study area ............................... 21 

Figure 1-5. Computation of width of the undeveloped subcatchment........................... 22 

Figure 1-6. Design storm hyetographs........................................................................... 23 

Figure 1-7. Runoff hydrographs (flow Q versus time) for the undeveloped site........... 27 

Figure 1-8. Discretization of the developed site into subcatchments ............................ 28 

Figure 1-9. Definition of overland flow length and slope for subcatchment S2............ 29 

Figure 1-10. Width and slope computation for subcatchments S3 (a) and S4 (b) ......... 30 

Figure 1-11. Runoff hydrographs (flow Q versus time) for the developed site............. 32 

Figure 2-1. Pre-development site................................................................................... 36 

Figure 2-2. Post-development site without conveyance system .................................... 37 

Figure 2-3. Links and Nodes.......................................................................................... 37 

Figure 2-4. Post-development site with runoff conveyance added................................ 40 

Figure 2-5. SWMM representation of the post-development conveyance system ........ 41 

Figure 2-6. Post-development outflow hydrographs for 2-yr storm.............................. 46 

Figure 2-7. Post-development outflow hydrographs for 10-yr storm............................ 47 

Figure 2-8. Post-development outflow hydrographs for 100-yr storm.......................... 47 

Figure 3-1. Detention pond location for the post-development site .............................. 51 

Figure 3-2. Schematic representation of a detention pond ............................................ 55 

Figure 3-3. Water quality capture volume (UDFCD, 2001).......................................... 55 

Figure 3-4. Average depth (inches) of runoff producing storms in the US 

(Driscoll, et al., 1989) .................................................................................. 57 

Figure 3-5. Geometry of the pond's WQCV .................................................................. 57 

Figure 3-6. Study area map with storage unit SU1........................................................ 59 

Figure 3-7. Properties of storage unit SU1 .................................................................... 59 

Figure 3-8. WQCV drainage times for the iterations shown in Table 3-3..................... 61 

Figure 3-9. Final design of the detention pond and outlet structure .............................. 65 

Figure 3-10. Detail of the pond outlet structure............................................................. 65 

Figure 3-11. Outlet hydrographs for the 2-yr storm ...................................................... 67 

Figure 3-12. Outlet hydrographs for the 10-yr storm .................................................... 67 

Figure 3-13. Outlet hydrographs for the 100-yr storm .................................................. 68 

Figure 4-1. Post-development site with LIDs in place .................................................. 70 

Figure 4-2. Schematic representation of a filter strip .................................................... 71 

Figure 4-3. Schematic representation of an infiltration trench ...................................... 72 

Figure 4-4. Re-discretization of subcatchments S3 and S4 ........................................... 75 

Figure 4-5. Representation of subcatchments S_FS_1, S3.1, and S3.2......................... 76 

Figure 4-6. Representation of subcatchments S_FS_3, S_FS_4, S4.1, S4.2, and S4.3 . 76 

Figure 4-7. Re-discretization of subcatchments S1 and S2 for infiltration trenches ..... 78 

vi 
 

 

Figure 4-8. Influent and effluent hydrographs for filter strip S_FS_1........................... 81 

Figure 4-9. Influent and effluent hydrographs for infiltration trench S_IT_1................ 81 

Figure 4-10. Comparison of outlet discharges with and without LID controls ............. 83 

Figure 4-11. Percent reduction in outlet peak flows and runoff volumes with LIDs .... 83 

Figure 5-1. Post-development site with no runoff controls ........................................... 86 

Figure 5-2. TSS buildup curve....................................................................................... 92 

Figure 5-3. TSS concentrations for the 0.1 in. storm with EMC washoff ..................... 96 

Figure 5-4. TSS concentrations for the 0.23 in. storm with EMC washoff ................... 96 

Figure 5-5. TSS concentration at site outlet with EMC washoff................................... 97 

Figure 5-6. Runoff flow and TSS load at site outlet for the 0.1 in. storm with EMC 

washoff......................................................................................................... 98 

Figure 5-7. TSS concentrations for the 0.1 in. storm with Exponential washoff .......... 99 

Figure 5-8. TSS concentrations for the 0.23 storm with Exponential washoff.............. 99 

Figure 5-9. TSS concentrations for the 2-yr (1 in.) storm with Exponential washoff . 100 

Figure 5-10. TSS concentration at the site outlet for Exponential washoff................. 100 

Figure 6-1. Developed site with LIDs and detention pond.......................................... 104 

Figure 6-2. Schematic of the re-designed pond outlet structure .................................. 105 

Figure 6-3. TSS and runoff reduction through filter strip S_FS_1 for the 0.1 in. 

storm .......................................................................................................... 110 

Figure 6-4. TSS and runoff reduction through infiltration trench S_IT_4 for the 2-yr 

storm .......................................................................................................... 111 

Figure 6-5. TSS concentrations in pond SU2 with and without treatment 

(k = 0.01 ft/hr)............................................................................................ 112 

Figure 6-6. TSS mass load released by pond SU2 for the 0.23 in storm
 

(k = 0.01 ft/hr)............................................................................................ 113 

Figure 6-7. TSS concentrations in pond SU2 with and without treatment 

(k = 0.3 ft/hr).............................................................................................. 114 

Figure 6-8. TSS mass load released by pond SU2 for the 0.23 in. storm
 

(k = 0.3 ft/hr).............................................................................................. 114 

Figure 6-9. Total TSS load discharged at site outlet under different treatment 

scenarios..................................................................................................... 116 

Figure 7-1. Post-development site with simple drainage system................................ 118 

Figure 7-2. Parallel pipe and gutter conveyance.......................................................... 118 

Figure 7-3. Elements of streets defined in the drainage criteria .................................. 120 

Figure 7-4. Three-dimensional layout of the site's dual drainage system.................... 122 

Figure 7-5. Full_Street cross section. The Half_Street section is half of this section. 122 

Figure 7-6. Post-development site with dual drainage system .................................... 125 

Figure 7-7. Examples of surcharge and flooding......................................................... 127 

Figure 7-8. Flows in pipes P5 and P6 during the 100-yr storm ................................... 130 

Figure 7-9. Surcharge behavior along the eastern boundary of the site....................... 131 

vii 
 

Figure 8-1. Combined sewer system study area .......................................................... 133 

Figure 8-2. Conceptual representation of overflows in a combined system
 

(Field and Tafuri, 1973)............................................................................. 134 

Figure 8-3. Transverse weir flow regulator ................................................................. 136 

Figure 8-4. Alternative ways to represent trnaverse weir flow regulators in SWMM 136 

Figure 8-5. (a) Pump Property Editor and (b) Pump Curve Editor.............................. 137 

Figure 8-6. Schematic representation of the combined sewer system......................... 138 

Figure 8-7. Layout of the combined sewer system before adding regulators and 

pump .......................................................................................................... 141 

Figure 8-8. Force main line.......................................................................................... 143 

Figure 8-9. Final combined sewer system model layout ............................................. 146 

Figure 8-10. Flow (Q) along sections of the stream for the 0.23 in. storm.................. 147 

Figure 8-11. Flow (Q) along sections of the interceptor for the 0.23 in. storm........... 148 

Figure 8-12. Flow (Q) diverted from each regulator to the interceptor for the 

0.23 in. storm ............................................................................................. 148 

Figure 8-13. Flow (Q) along sections of the stream for the 2-yr storm....................... 149 

Figure 8-14. Flow (Q) along the sections of the interceptor for the 2-yr storm .......... 149 

Figure 8-15. Flows (Q) in regulators R1 and R4 for the 2-yr storm ............................ 150 

Figure 8-16. Pump behavior for the 0.23 in. storm: (a) wet well water depth, 

(b) pump flow ............................................................................................ 151 

Figure 9-1. Drainage system and detention pond (SU1) designed in Example 3 ........ 155 

Figure 9-2. Ten year rainfall record for Fort Collins, CO (Source: National 

Climatic Data Center) ................................................................................ 160 

Figure 9-3. Rainfall event producing the largest flow rates to the detention pond...... 162 

Figure 9-4. Water depth in the detention pond between days 3061 and 3069............. 163 

Figure 9-5. Inflow and outflow (Q) for the detention pond between days 3061 

and 3069..................................................................................................... 164 

Figure 9-6. Losses for subcatchment S1 between days 3061 and 3069....................... 165 

Figure 9-7. Statistics Selection dialog for analyzing peak pond outflows................... 166 

Figure 9-8. Summary statistics for peak inflow to node J_out (same as peak 

pond outflow)............................................................................................. 167 

Figure 9-9. Event listing of peak inflow to node J_out (same as peak pond outflow) 167 

Figure 9-10. Histogram of peak inflow to node J_out (same as peak pond outflow).. 168 

Figure 9-11. Cumulative frequency of peak inflow to node J_out (same as peak 

pond outflow)............................................................................................. 168 

Figure 9-12. Statistical query for daily peak water depth in the detention pond......... 170 

Figure 9-13. Frequency plot of daily peak water depth in the detention pond ............ 170 

Figure 9-14. Selection of an MIT for analyzing a rainfall record ................................ 172 

Figure 9-15. Frequency plots for event duration and depth......................................... 173 

viii 
Tables 

Table 1-1. Properties of the undeveloped subcatchment ............................................... 22 

Table 1-2. Flow lengths and slopes of the undeveloped subcatchment......................... 23 

Table 1-3. Analysis options ........................................................................................... 25 

Table 1-4. Summary of results for the undeveloped site ............................................... 27 

Table 1-5. Geometric properties of the subcatchments in the developed site ............... 29 

Table 1-6. Land use categories in the developed site .................................................... 31 

Table 1-7. Land use coveage (ac) and imperviousness for subcatchments in the 

developed site............................................................................................... 31 

Table 1-8. Summary of results for post-development conditions.................................. 33 

Table 1-9. Comparison of runoff for pre- and post-development conditions................ 33
 

Table 2-1. Invert elevations of junctions ....................................................................... 41 

Table 2-2. Subcatchment outlets.................................................................................... 42 

Table 2-3. Characteristics of the conduits used in the model ........................................ 43 

Table 2-4. Conduit properties ........................................................................................ 43 

Table 2-5. Available culvert sizes.................................................................................. 44 

Table 2-6. Maximum depths and flows for conduits during the 100-yr event .............. 45 

Table 2-7. Comparison of runoff for post-development conditions with and without 

routing.......................................................................................................... 48
 

Table 3-1. Pre- and post-development peak discharges................................................. 50 

Table 3-2. Post-development subcatchment data........................................................... 56 

Table 3-3. Design of the WQCV outlet (Or1) ............................................................... 60 

Table 3-4. Characteristics of the pond's outlet structure................................................ 66
 

Table 4-1. Subcatchments containing filter strips.......................................................... 72 

Table 4-2. Properties of the new junctions .................................................................... 74 

Table 4-3. Properties of the new conduits ..................................................................... 74 

Table 4-4. Properties of the subcatchments derived from S3 and S4 ............................ 75 

Table 4-5. Widths of the filter strip subcatchments....................................................... 76 

Table 4-6. Properties of the filter strip subcatchments .................................................. 77 

Table 4-7. Properties of the subcatchments derived from S1 and S2 ............................ 78 

Table 4-8. Subcatchments containing infiltration trenches............................................ 79 

Table 4-9. Properties of the infiltration trench subcatchments...................................... 79 

Table 4-10. Properties of the new junctions .................................................................. 80 

Table 4-11. Properties of the new conduits ................................................................... 80 

Table 4-12. Runoff coefficients for filter strips............................................................. 82 

Table 4-13. Runoff coefficients for infiltration trenches............................................... 82
 

Table 5-1. Rainfall time series for the 0.1 and 0.23 inch events.................................... 86 

Table 5-2. Typical dust and dirt buildup rates after Manning et al. (1977)................... 91 

Table 5-3. Parameters for TSS buildup.......................................................................... 92 

Table 5-4. Curb length and land uses for each subcatchment........................................ 92 

Table 5-5. Washoff characteristics for each land use .................................................... 94 

ix 
Table 5-6. Average TSS concentration for the 0.23 in. event...................................... 101
 

Table 6-1. Storage curve for the re-designed pond...................................................... 104 

Table 6-2. Properties of the pond’s re-designed outlet structure ................................. 105 

Table 6-3. Curb lengths and land uses for LID subcatchments ................................... 108 

Table 6-4. Detention pond TSS treatment performance summary .............................. 115
 

Table 7-1. General drainage system criteria for Fort Collins (City of Fort Collins, 

1984 and 1997) .......................................................................................... 121 

Table 7-2. Cross section data for street transects......................................................... 124 

Table 7-3. Junction invert elevations for dual drainage system................................... 126 

Table 7-4. Conduit shapes and offsets for dual drainage system................................. 126 

Table 7-5. Calculated gutter grades ............................................................................. 128 

Table 7-6. Available drainage pipe sizes ..................................................................... 129 

Table 7-7. Iterations for 2-yr storm pipe sizing ........................................................... 129
 

Table 8-1. Properties of the combined sewer system nodes1....................................... 139 

Table 8-2. Properties of the combined sewer system conduits1

................................... 140 

Table 8-3. Subcatchment outlets.................................................................................. 140 

Table 8-4. Properties of the regulator structures.......................................................... 143 

Table 8-5. Properties of the force main line ................................................................ 144 

Table 8-6. Pump curve data ......................................................................................... 145 

Table 8-7. Summary of dry weather flows .................................................................. 146 

Table 8-8. Summary of system performance for different storm events ..................... 152
 

Table 9-1. Monthly evaporation for Fort Collins, CO (Source: Western Regional 

Climate Center).......................................................................................... 159 

Table 9-2. Summary statistics for various rainfall event properties ............................ 173 

Table 9-3. Ten most severe events based on duration, depth and intensity................. 174 

Table 9-4. Correspondence among the most severe events ......................................... 175 

x 
ACKNOWLEDGEMENT 

The authors would like to acknowledge the active participation of EPA’s Project 

Officer, Lewis Rossman in the development of this Manual. Dr. Rossman participated 

in the development of all examples contained in the manual, reviewed and commented 

on the model results and participated in the write-up of the examples. His active 

participation in this project has contributed to the high quality of the resulting Manual. 

xi 
Introduction 

The EPA Storm Water Management Model (SWMM) is a dynamic rainfallrunoff simulation model that computes runoff quantity and quality from primarily 

urban 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 through a system of pipes, 

channels, storage/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 1971 and since then has undergone several 

major upgrades. It continues to be widely used throughout the world for planning, 

analysis, and design related to stormwater runoff, combined sewers, sanitary sewers, 

and other drainage systems in urban areas and has also been used for modeling nonurban areas. The most current implementation of the model is version 5.0 which was 

released in 2005. It has modernized both the model’s structure and its user interface, 

making SWMM easier to use and more accessible to a new generation of hydrologists, 

engineers, and water resources management specialists. 

12 
The objective of this manual is to serve as a practical application guide for new 

SWMM users who have already had some previous training in hydrology and 

hydraulics. It contains nine worked-out examples that illustrate how SWMM can be 

used to model some of the most common types of stormwater management and design 

problems encountered in practice. The following applications are discussed in the 

manual: 

1.	 Post-Development Runoff. Surface runoff from a 29 acre residential site is 

computed for several design-storm events under both pre- and postdevelopment conditions. 

2.	 Surface Drainage Hydraulics. A surface runoff conveyance network is added to 

the post-development catchment area of Example 1 and is analyzed with 

SWMM’s various hydraulic routing options. 

3.	 Detention Pond Design. A detention pond and outlet structure are designed for 

the post-development condition of Example 2 that meets both water quality 

control and peak flow reduction criteria. 

4.	 Low Impact Development. Two typical Low Impact Development (LID) 

controls, filter strips and infiltration trenches, are placed within the postdevelopment catchment modeled in Example 2. 

5.	 Runoff Water Quality. The buildup, washoff and routing of total suspended 

solids (TSS) is simulated within the post-development catchment modeled in 

Example 2. 

6.	 Runoff Treatment. The removal of TSS in the LID controls and detention pond 

of Examples 3 and 4 is modeled. 

7.	 Dual Drainage Systems. The surface drainage system of Example 2 is converted 

into a parallel system of below ground storm sewers and above ground streets 

and gutters that is subjected to both surcharged flow and street flooding. 

8.	 Combined Sewer Systems. The sewer system of Example 7 is converted into a 

combined system that carries both dry weather sanitary flow and wet weather 

runoff and includes various flow diversion structures and a pumped force main. 

9.	 Continuous Simulation. SWMM’s statistical tools are used to analyze the 

performance of the detention pond designed in Example 3 over a continuous ten 

year period of historical rainfall. 

All the examples are developed for the same catchment area and each one 

builds in some degree on the results of a previous example. Therefore, it is 

recommended that the reader begin with Example 1 and work sequentially through 

Example 9, while hopefully building the required input data files and running them 

with SWMM for each example. They can then compare the input files they build with 

the files created by the authors. These files, as well as the backdrop image files that are 

needed to complete the examples, are available in a compressed file named 

epaswmm5_apps_manual.zip. It can be downloaded from the EPA SWMM web site 

at: http://www.epa.gov/endnrmrl/models/swmm. 

13 
This manual assumes that readers have a basic knowledge of how to run EPA 

SWMM 5 and perform such functions as opening a new project, setting project 

defaults, adding drainage system objects to a project, editing the properties of these 

objects, and viewing simulation results. These topics and more are covered in the 

SWMM Users Manual which is also available from the EPA SWMM web site. That 

manual includes a tutorial example that leads new users through each of these steps. 

14 
Example 1. Post-Development Runoff 

This first example demonstrates how to construct a hydrologic model of an urban 

catchment and use it to compare stormwater runoff under both pre- and post-development 

conditions. It illustrates the process of spatially dividing a catchment into smaller 

computational units, called subcatchments, and discusses the characteristics of these 

subcatchments that SWMM uses to transform rainfall into runoff. This example considers 

runoff only. Flow routing of runoff through the drainage pipes and channels contained 

within the catchment is addressed in Example 2. 

Models of this type are very common in practice. Many local stormwater 

ordinances and agencies require that new developments limit peak runoff flows relative 

to those under pre-development conditions. To meet environmental sustainability 

objectives, similar criteria are being applied to total runoff volume as well. 

1.1 Problem Statement 

Figure 1-1 is a contour map of a 29 acre natural catchment area where a new 

residential development is planned. This undeveloped area is primarily pasture land that 

has a silt loam soil type. Figure 1-2 shows the proposed development for this site. With 

the exception of the depressions located in the parkland area, no major changes in 

topography are expected. This implies that future streets will, in general, follow the 

natural slope. However, the residential lots will be graded toward the street at a slope of 

2% so they can drain easily. The developed site will drain to a stream through a culvert 

under the street located on the southeast side of the site, which is considered to be the 

outlet point of the catchment. 

The objective is to estimate the stormwater discharges at the catchment’s outlet 

and compare them to the ones generated prior to urbanization. The approach typically 

employed in stormwater drainage manuals will be used, which is to compute the 

hydrologic response of the catchment to a series of synthetic design storms associated 

with different return periods. The design storms used here will be for a 2-hour event with 

return periods of 2, 10, and 100 years. Most of the parameter values used in this example 

were taken from tables published in the SWMM User’s Manual (Rossman, 2008). These 

were supplemented with design guidelines published by the Denver Urban Drainage and 

Flood Control District (UDFCD) (UDFCD, 2001). 

Two models will be built: one that represents the catchment in its current 

undeveloped condition and one that represents the catchment after it is fully developed. 

Because this is an initial estimation of the discharges at the outlet of the catchment under 

its current and future conditions, no channelized flows will be defined and only runoff as 

overland flow will be simulated. Example 2 in this manual will add a conveyance system 

of swales, channels, and culverts to this model. 

15 
Figure 1-1. Undeveloped site 

Figure 1-2. Developed site 

16
 
1.2 System Representation 

SWMM is a distributed model, which means that a study area can be subdivided 

into any number of irregular subcatchments to best capture the effect that spatial 

variability in topography, drainage pathways, land cover, and soil characteristics have on 

runoff generation. An idealized subcatchment is conceptualized as a rectangular surface 

that has a uniform slope and a width W that drains to a single outlet channel as shown in 

Figure 1-3. Each subcatchment can be further divided into three subareas: an impervious 

area with depression (detention) storage, an impervious area without depression storage 

and a pervious area with depression storage. Only the latter area allows for rainfall losses 

due to infiltration into the soil. 

Figure 1-3. Idealized representation of a subcatchment 

The hydrologic characteristics of a study area’s subcatchments are defined by the 

following set of input parameters in SWMM: 

• Area 

This is the area bounded by the subcatchment boundary. Its value is determined 

directly from maps or field surveys of the site or by using SWMM’s Auto-Length 

tool when the subcatchment is drawn to scale on SWMM’s study area map. 

• Width 

The width can be defined as the subcatchment’s area divided by the length of the 

longest overland flow path that water can travel. If there are several such paths 

then one would use an average of their lengths to compute a width. 

In applying this approach one must be careful not to include channelized flow as 

part of the flow path. In natural areas, true overland flow can only occur for 

distances of about 500 feet before it begins to consolidate into rivulet flow. In 

urbanized catchments, true overland flow can be very short before it is collected 

into open channels or pipes. A maximum overland flow length of 500 feet is 

appropriate for non-urban catchments while the typical overland flow length is the 

17 
length from the back of a representative lot to the center of the street for urban 

catchments. If the overland flow length varies greatly within the subcatchment, 

then an area-weighted average should be used. 

Because it is not always easy to accurately identify all of the overland flow paths 

within a subcatchment, the width parameter is often regarded as a calibration 

parameter whose value can be adjusted to produce a good match between 

observed and computed runoff hydrographs. 

• Slope 

This is the slope of the land surface over which runoff flows and is the same for 

both the pervious and impervious surfaces. It is the slope of what one considers to 

be the overland flow path or its area-weighted average if there are several such 

paths in the subcatchment. 

• Imperviousness 

This is the percentage of the subcatchment area that is covered by impervious 

surfaces, such as roofs and roadways, through which rainfall cannot infiltrate. 

Imperviousness tends to be the most sensitive parameter in the hydrologic 

characterization of a catchment and can range anywhere from 5% for 

undeveloped areas up to 95% for high-density commercial areas. 

• Roughness Coefficient 

The roughness coefficient reflects the amount of resistance that overland flow 

encounters as it runs off of the subcatchment surface. Since SWMM uses the 

Manning equation to compute the overland flow rate, this coefficient is the same 

as Manning’s roughness coefficient n. Separate values are required for the 

impervious and pervious fractions of a subcatchment since the pervious n is 

generally an order of magnitude higher than the impervious n (e.g., 0.8 for dense 

wooded areas versus 0.012 for smooth asphalt). 

• Depression Storage 

Depression storage corresponds to a volume that must be filled prior to the 

occurrence of any runoff. Different values can be used for the pervious and 

impervious areas of a subcatchment. It represents initial abstractions such as 

surface ponding, interception by flat roofs and vegetation, and surface wetting. 

Typical values range between 0.05 inches for impervious surfaces to 0.3 inches 

for forested areas. 

• Percent of Impervious Area Without Depression Storage 

This parameter accounts for immediate runoff that occurs at the beginning of 

rainfall before depression storage is satisfied. It represents pavement close to the 

gutters that has no surface storage, pitched rooftops that drain directly to street 

gutters, new pavement that may not have surface ponding, etc. By default the 

value of this variable is 25%, but it can be changed in each subcatchment. Unless 

special circumstances are known to exist, a percent imperviousness area without 

depression storage of 25% is recommended. 

18 
•	 Infiltration Model 

Three different methods for computing infiltration loss on the pervious areas of a 

subcatchment are available in SWMM. They are the Horton, Green-Ampt and 

Curve Number models. There is no general agreement on which model is best. 

The Horton model has a long history of use in dynamic simulations, the GreenAmpt model is more physically-based, and the Curve Number model is derived 

from (but not the same as) the well-known SCS Curve Number method used in 

simplified runoff models. 

The Horton model will be used in the current example. The parameters for this 

model include: 

•	 Maximum infiltration rate: This is the initial infiltration rate at the start of 

a storm. It is difficult to estimate since it depends on the antecedent soil 

moisture conditions. Typical values for dry soils range from 1 in/h for 

clays to 5 in/h for sands. 

•	 Minimum infiltration rate: This is the limiting infiltration rate that the soil 

attains when fully saturated. It is usually set equal to the soil’s saturated 

hydraulic conductivity. The latter has a wide range of values depending 

on soil type (e.g., from 0.01 in/hr for clays up to 4.7 in/hr for sand). 

•	 Decay coefficient: This parameter determines how quickly the infiltration 

rate “decays” from the initial maximum value down to the minimum 

value. Typical values range between 2 to 7 hr-1. 

•	 Precipitation Input 

Precipitation is the principal driving variable in rainfall-runoff-quantity 

simulation. The volume and rate of stormwater runoff depends directly on the 

precipitation magnitude and its spatial and temporal distribution over the 

catchment. Each subcatchment in SWMM is linked to a Rain Gage object that 

describes the format and source of the rainfall input for the subcatchment. 

1.3 Model Setup – Undeveloped Site 

The SWMM model for the undeveloped site is depicted in Figure 1-4. It consists 

of a rain gage R1 that provides precipitation input to a single subcatchment S1 whose 

runoff drains to outfall node O1. Note that the undeveloped site contour map has been 

used as a backdrop image on which the subcatchment outline has been drawn. The 

SWMM input file for this model is named Example1-Pre.inp. 

19 
 

 

Utilizing a Backdrop Image in SWMM 

To help facilitate the placement of drainage-system objects, SWMM can 

utilize an image as a backdrop behind a project’s study area map. This image is 

typically a site map of some kind with known dimensions. Any bitmap image file 

(BMP extension), Windows metafile (WMF or EMF extension) or JPEG image 

file (JPG or JPEG extension) can be used as a backdrop. These images would 

typically come from a CAD or GIS drawing of the site or perhaps from an 

electronically published or scanned topographic or street map. 

Before adding the backdrop image, the actual horizontal and vertical 

dimensions represented in the image must be known in order to scale the map 

correctly. To add a properly scaled backdrop image to a SWMM project do the 

following: 

1.	 Select View | Backdrop | Load from the main menu. 

2.	 Enter the name of the backdrop image file to be loaded in the Backdrop Image 

Selector dialog that appears. After closing the dialog, the backdrop will appear 

on the Study Area Map with a default set of dimensions. 

3.	 To properly scale both the backdrop and the study area map, select View | 

Backdrop | Resize from the main menu. In the Backdrop Dimensions dialog 

select the “Scale Map to Backdrop Image” checkbox. This will automatically 

adjust the dimensions of the map to be the same as the backdrop. Then enter 0,0 

for the lower left coordinates and the backdrop’s width and height for the upper 

right coordinates. 

4.	 Finally, select View | Dimensions from the main menu and select the 

appropriate units for the map’s dimensions (typically feet or meters). 

At times one will want to lighten the backdrop image so that the added drainage 

system objects will stand out more clearly on the map. This can be done by toggling 

the View | Backdrop | Watermark option on the main menu. 

20 
Subcatchment Properties 

According to the site’s contour map, its topography is fairly homogenous and no 

well-defined channels exist within the basin which means that mainly overland flow takes 

place. There are no roads or other local impervious areas and the type of soil is similar 

throughout the watershed (Sharpsburg silt loam). Therefore, no disaggregation is required 

based on the spatial distribution of catchment properties. The single subcatchment S1 

drains to the free outfall node O1 whose elevation is 4967 ft. 

Figure 1-4. SWMM representation of the undeveloped study area 

The area shown in Figure 1-4 is not the entire pre-development natural catchment. 

It has been bounded by the post-development roadways to come so that comparisons 

between the two conditions (developed and undeveloped) can be made. 

The properties assigned to the single subcatchment S1 are summarized in Table 1­

1. Their values were developed on the basis of the undeveloped site being primarily 

pasture land containing a silt loam soil. Parameter values for this soil type can be found 

in the SWMM User’s Manual and the UDFCD Guidance Manual. 

21 
Table 1-1. Properties of the undeveloped subcatchment 

Property Value Property Value 

Area 28.94 ac Depression storage, 

pervious areas 

 0.3 in. 

Width 2521 ft Depression storage, 

impervious areas 

 0.06 in. 

Slope 0.5 % % of impervious area without

depression storage 25% 

Imperviousness 5 % Maximum infiltration rate 4.5 in./hr 

Roughness coefficient, 

impervious areas 0.015 Minimum infiltration rate 0.2 in./hr 

Roughness coefficient, 

pervious areas 0.24 Infiltration decay coefficient -1 6.5 hr

 

 

The subcatchment’s area was determined using SWMM’s Auto-Length tool. The 

subcatchment width was arrived at by first assuming a maximum overland-flow length of 

500 ft, as recommended for undeveloped areas. By the time runoff has travelled this 

distance it has consolidated into rivulets and therefore no longer behaves as overland 

flow over a uniform plane. Based on this assumption, the subcatchment was divided into 

subareas with flow-path lengths of 500 feet or less. Figure 1-5 shows that there were 

three such areas whose flow-path lengths are each 500 ft. Thus, the average flow length is 

also 500 ft. When the total subcatchment area of 28.94 acres (1,260,626 ft2) is divided by 

the average flow length the resulting subcatchment width is 2,521 ft. The average slope 

of the subcatchment was derived from the area-weighted average of the slopes of the 

three sub-areas that comprise the overland flow paths as shown in Figure 1-5 and Table 

1-2. Its value is 0.5. 

Figure 1-5. Computation of width of the undeveloped subcatchment 

1 2 3 + + 

500 ft 

28.84 ac / 500 ft = 2521 ft 

500 ft 

2521 ft 

1 

2 3 

S = 0.5% 

22 
 

 

 

 

=

=

⋅ 3i 

1i i

ii 

A

AS ∑ ∑

2-year 10-year 100-year 

Intensity (in/h) 

12 

10 

8 

6 

4 

2 

0 

0 30 60 90 120 

Time (minutes) 

Table 1-2. Flow lengths and slopes of the undeveloped subcatchment 

Sub-Area 

1 

Flow Path 

Length 

(ft) 

500 

Associated 

Area (Ai) 

(ac) 

11.13 

Upstream 

Elevation 

(ft) 

4974.8 

Downstream 

Elevation 

(ft) 

4973 

Elevation 

Difference 

 (ft) 

1.8 

Slope 

(Si) 

 (%) 

0.4% 

2 500 14.41 4973 4970 3 0.6% 

3 500 3.4 4970 4967 3 0.6% 

Average 500 0.51 

1 Weighted average corresponding to

The Horton method was selected as the infiltration model for this analysis. The 

values assigned to its parameters are typical of those for a silt loam soil as found in this 

watershed and are listed in Table 1-1. It is strongly recommended to use any available 

site-specific data from the study area BEFORE relying on values from the literature. 

Rain Gage Properties 

The properties of rain gage R1 describe the source and format of the precipitation 

data that are applied to the study area. In this example, the rainfall data consist of three 

synthetic design events that represent the 2-, 10- and 100-year storms of 2-hour duration. 

Each storm is represented by a separate time series object in the SWMM model that 

consists of rainfall intensities recorded at a 5 minute time-interval. The time series are 

named 2-yr, 10-yr and 100-yr, respectively and are plotted in Figure 1-6. The total depth 

of each storm is 1.0, 1.7, and 3.7 inches, respectively. These design storms were selected 

by the City of Fort Collins, CO to be used with SWMM (City of Fort Collins, 1999). 

Figure 1-6. Design storm hyetographs 

23 
Measuring Tools Available in SWMM 

SWMM’s graphical user interface has several tools that can assist in 

measuring distances and areas on a project’s study area map. One such tool is the 

Auto-Length option. If Auto-Length is turned on, any subcatchment’s polygon 

outline that is drawn or edited will have its area computed automatically and stored 

in its Area property. The same holds true for conduit lengths. The current status of 

the Auto-Length option is shown in the status bar at the bottom of SWMM’s main 

window. It can be switched on/off by clicking the drop-down arrow next to the 

Auto-Length display. 

Another feature of Auto-Length is its ability to re-compute the areas of all 

subcatchments and the lengths of all conduits in a project at once. This capability 

proves useful when a user changes the map scaling, switches between using US and 

metric units, or has done a lot of map editing with Auto-Length turned off. To 

implement this feature, make sure Auto-Length is turned on and select View | 

Dimensions from the main menu. In the Map Dimensions dialog that appears, 

check on the option to re-compute all lengths and areas. There is no need to change 

any of the other settings in the dialog unless one so desires. Once OK is clicked, all 

of the subcatchments and conduits on the map will have their areas and lengths 

updated. 

A second measurement tool is the Ruler tool. It is used to measure the 

distance along a polyline as well as compute an area if the polyline is closed to form 

a polygon. To activate the Ruler tool select the button on the Map Toolbar. Then 

click the mouse on the first point to begin measuring from, and continue to click at 

intermediate points along the path being measured. To complete the path and 

determine its length, right click (or press Enter) at the terminating point. To 

measure the perimeter and area of a polygon, make the terminating point the same 

as the initial point of the path. 

24 
 

1.4 Model Results – Undeveloped Site 

Analysis Options 

Table 1-3 shows the analysis options used to run the model. Three runs of the 

model were made, one for each design storm event. To analyze a particular storm event 

one only has to change the Series Name property of the rain gage to the rainfall time 

series of interest. The total discharges to the outfall for each storm were then plotted on 

one graph for comparison. 

Table 1-3. Analysis options 

Option Value Explanation 

Flow units CFS U.S customary units used throughout 

Routing Method Kinematic wave Must specify a routing method, but it is not used 

in the overland flow computations in this example 

Start analysis time and date 01/01/07 - 00:00 Not important for single event simulation 

Start reporting time and date 01/01/07 - 00:00 Start reporting results immediately 

End analysis time and date 01/01/07 - 12:00 12 h of simulation (storm duration is 2 h) 

Good level of detail in results for a short Reporting time step 1 minute simulation 

Runoff dry-weather time step 1 hour Not important for single event simulation 

Runoff wet-weather time step 1 minute Should be less than the rainfall interval 

Routing time step 1 minute Should not exceed the reporting time step 

Simulation Results 

Figure 1-7 shows the outlet hydrographs obtained for each of the design storms. It 

was created by following the procedure outlined in the sidebar titled Exporting Data from 

SWMM. Note the significant increase in the peak discharge as the return period increases 

and how sensitive it is to the rainfall intensity. (The 2-yr storm hyetograph is plotted for 

comparison.) The rate at which the discharge volume increases is much greater than the 

rate at which the rainfall volume changes for different return periods. This is because the 

soil becomes more saturated during larger storms resulting in more of the rainfall 

becoming runoff. 

Table 1-4 compares the peak rainfall intensity, total rainfall, total runoff volume, 

runoff coefficient, peak runoff discharge and total infiltrated volume for each design 

storm. Additionally, the last column provides the percent of the rainfall that is infiltrated 

in each case. These values came directly from the Subcatchment Runoff Summary table 

that appears in the Status Report of a SWMM run. 

25 
Exporting Data from SWMM 

While data can be plotted in the SWMM interface for one run’s results, it is 

not possible to plot the results of an additional run with those of an older run. To do 

this the results from each run must be exported to a spreadsheet or other plotting 

software. Data from both plots and tables can be easily exported in SWMM. The 

steps below explain how this is done for the runoff seen at the watershed outlet for 

the 2- and 10-yr storms. 

1.	 Run the 2-yr simulation. Click on the watershed outlet 

( )

O1 and then select 

the Table icon on the Standard Toolbar. For this example, choose “by 

Object...” 

2.	 In the Table by Object dialog box select Date/Time for the Time Format 

and for the variable select Total Inflow. Click Ok. 

3.	 A table of runoff flow rates and their times will appear. Select Edit | Select 

All and then Edit | Copy to... from the main menu. In the Copy Table 

dialog box you have the choice of copying the data to the Clipboard and 

pasting it from there directly into the spreadsheet or saving it to a text file. 

Choose Clipboard for this example. Open a spreadsheet document, and 

paste the Clipboard contents into it. 

4.	 Return to SWMM and run the 10-yr storm and repeat steps 1 to 3. Paste the 

data into the same spreadsheet, next to the data from the 2-yr storm. 

5.	 Now use the Scatter plot and the formatting tools of your spreadsheet to plot 

the Total Inflow data for both runs on the same graph. 

26 
Q(cfs) 

35 

0 

5 

10 

15 

20 

25 

40 

45 

0:00 1:00 2:00 3:00 4:00 5:00 6:00 

time (hr:min) 

0 

1.5 

2-yr storm 

2-yr 

10-yr 

100-yr 

3 

30 4.5 

6 

7.5 

9 

10.5 

12 

13.5 

in/h 

Table 1-4. Summary of results for the undeveloped site 

Peak Total Runoff Runoff Design Rainfall Rainfall Volume Coeff. Storm (in./h) (in.) (in.) (%) Peak 

Runoff 

(cfs) 

Total 

Infiltration 

(in.) 

% of 

Rainfall 

Infiltrated 

2-yr 2.85 0.978 0.047 4.8 4.14 0.93 95.1 

10-yr 4.87 1.711 0.22 13.1 7.34 1.48 86.5 

100-yr 9.95 3.669 1.87 50.8 31.6 1.80 49.1 

Figure 1-7. Runoff hydrographs (flow Q versus time) for the undeveloped site 

1.5 Model Setup – Developed Site 

The increase in impervious surface and reduction of overland flow length are the 

main factors affecting the hydrologic response of a catchment when it becomes 

urbanized. The reduction in infiltrative surface creates additional surface runoff as well as 

higher and faster peak discharges. In this section, the runoff hydrology of our example 

site will be modeled in its post-development condition. The SWMM input data for this 

model is named Example1-Post.inp. Again, the focus will be on just the rainfall-runoff 

transformation and overland flow processes. Routing through channelized elements will 

be covered in Example 2. 

Catchment Discretization 

In the urbanized catchment there are channelized elements (gutters and swales) 

that conduct runoff to the site’s outlet. The partitioning of the study area into individual 

27 
subcatchments depends not only on the spatial variability in land features but also on the 

location of the channelized elements. Inspection of the developed site plan for the 

example study area (see Figure 1-2) suggests that a total of seven subcatchments would 

be sufficient to represent both the spatial differences in planned land uses and the location 

of channelized elements within the site. The subcatchment boundaries were determined 

by aggregating together sub-areas whose potential overland flow paths share a common 

direction and drain to the same collection channel. The resulting discretization is shown 

in Figure 1-8. 

Figure 1-8. Discretization of the developed site into subcatchments 

Figure 1-8 shows all of the subcatchments discharging their overland flow 

directly into the watershed’s outlet node, O1. In reality, the discharge outlet of each 

subcatchment should be the point where its runoff enters the channelized drainage 

system. However, since this example does not consider routing through any channelized 

elements in the watershed (Example 2 covers this issue) it is acceptable to use the study 

area’s outlet node (O1) as a common outlet for all of the subcatchments. The elevation of 

this point is 4962 ft, which corresponds to the bottom elevation of a planned culvert 

under the street. 

28 
 

Geometric Parameters 

Table 1-5 lists the area, flow path length, width, slope and imperviousness of each 

subcatchment. The areas were computed using SWMM’s Auto-Length tool as the outline 

of each subcatchment was traced on the scaled backdrop image. (See the sidebar 

“Measuring Tools Available in SWMM” for more information.) 

Table 1-5. Geometric properties of the subcatchments in the developed site 

Subcatchment Area 

(ac) 

Flow 

Length (ft) 

Width 

(ft) 

Slope 

(%) 

Percent 

 Impervious 

1 4.55 125 1587 2.0 56.8 

2 4.74 125 1653 2.0 63.0 

3 3.74 112 1456 3.1 39.5 

4 6.79 127 2331 3.1 49.9 

5 4.79 125 1670 2.0 87.7 

6 1.98 125 690 2.0 95.0 

7 2.33 112 907 3.1 0.0 

Figure 1-9 illustrates how the overland flow path length was estimated for 

subcatchment S2 which consists entirely of residential lots. This subcatchment can be 

represented as a rectangular area with an overland flow length equal to the distance from 

the back of a typical lot to the middle of the street (125 ft in this case). SWMM’s width 

parameter can then be computed as the area (4.74 ac = 206,474.4 ft2

) divided by the 

overland flow length, which results in a value of 1650 ft. 

Figure 1-9. Definition of overland flow length and slope for subcatchment S2 

29 
Total Area = 3.74 ac Total Area = 6.79 ac 

ZU = 4974.5 ft 

L1 = 125 ft 

S1 = 2% 

ZD = 4970 ft 

L2 = 95 ft 

S2 = 4.7% 

. % . S

.

.

.

. L

743 

561 2 743 182 

743 

561 125 743 182 

+⋅=

(a) +⋅=

ZU = 4972.3 ft 

L1 = 125 ft 

S1 = 2% 

ZD = 4967 ft 

L2 = 130 ft 

S2 = 5% 

%.% .

.

.

.

135 796 

492 

127130 796 

492 

=⋅+

=⋅+ (b) 4.3 L = ⋅125 ⋅ 95 = 112 6.79 

4.3 S = ⋅ 2% ⋅ 4.7% = 3.1% 6.79 . .

In contrast to S2, subcatchments S3 and S4 contain both residential lots and grasscovered areas. Their overland flow lengths are computed as an area-weighted average of 

the flow lengths across each type of area as shown in Figure 1-10. Their widths are then 

found by dividing their areas by their overland flow lengths. 

Figure 1-10. Width and slope computation for subcatchments S3 (a) and S4 (b) 

Slopes characterizing overland flow in mostly urbanized subcatchments will be 

the lot slope, which is usually about 2%. By way of illustration, Figure 1-10 shows how 

the slopes of subcatchments S3 and S4 correspond to the area-weighted average of the 

slope of the overland flow paths over both the residential lots and the grass-covered 

areas. 

Imperviousness 

The imperviousness parameter in SWMM is the effective or directly connected 

impervious area, which is typically less than the total imperviousness. The effective 

impervious area is the impervious area that drains directly to the stormwater conveyance 

system, e.g. a gutter, pipe or swale. Ideally, the imperviousness should be measured 

directly in the field or from orthophotographs by determining the percent of land area 

devoted to roofs, streets, parking lots, driveways, etc. When these observations are not 

available, it is necessary to use other methods. A conservative approximation that tends 

to overestimate runoff discharges is to use runoff coefficients as the imperviousness 

value. A runoff coefficient is an empirical-constant value that represents the percentage 

of rainfall that becomes runoff. Using the runoff coefficient to represent the percent 

imperviousness of a subcatchment results in a higher estimate of impervious area because 

the value is calculated from the runoff of both the impervious and pervious areas of the 

subcatchment. For purely illustrative purposes, runoff coefficients will be used in this 

example to estimate the imperviousness for each subcatchment within the developed 

watershed. The steps involved are as follows: 

1. Identify all of the major land uses that exist within the subcatchment. 

2. Compute the area Aj devoted to each land use j in the subcatchment. 

30 
Table 1-6. Land use categories in the developed site 

Id Land Use Runoff coefficient (C) 

M Medium density 0.65 

L Low density 0.45 

DL Duplex 0.70 

M2 Medium density 0.65 

S Apartment, high 

density 0.70 

RT Commercial 0.95 

T Commercial 0.95 

P Natural (park)	 0 

Table 1-7. Land use coveage (ac) and imperviousness for subcatchments in the developed site 

Sub- Total Area Area Area Area Area Area Area Area Imperviousness 

catchment Area (ac) M L DL M2 S RT T P (%) 

S1 4.55 2.68 1.87 0 0 0 0 0 0 56.8 

S2 4.74 0 1.32 3.42 0 0 0 0 0 63 

S3 3.74 0 0 0 1 1.18 0 0 1.56 39.5 

S4 6.79 0.61 0 0 0 2.05 1.64 0 2.49 49.9 

S5 4.79 0 0 0 0 0 0.7 3.72 0.37 87.7 

S6 1.98 0 0 0 0 0 0 1.98 0 95 

S7 2.33 0 0 0 0 0 0 0 2.33 0 

3.	 Assign a runoff coefficient Cj to each land use category j. Typical values are available 

in drainage criteria and basic literature (see for example UDFCD, 2001; Akan, 2003). 

Pervious areas are assumed to have a runoff coefficient of 0. 

4.	 Compute the imperviousness I as the area weighted average of the runoff coefficients 

for all of the land uses in the subcatchment, I = (ΣCjAj)/A, where A is the total area of 

the subcatchment. 

When this approach is applied to the current example the results listed in Tables 

1-6 and 1-7 are obtained. Table 1-6 displays the various land-use categories that appear in 

the developed site along with their runoff coefficients. The latter were obtained from the 

City of Fort Collins Storm Drainage Design Criteria and Construction Standards (City of 

Fort Collins, (city of Fort Collins, 1984 and 1997). Table 1-7 lists the amount of area 

devoted to each land use within the site’s subcatchments. These areas were used to 

compute a weighted-average runoff coefficient that is used as a surrogate for the 

imperviousness of the given subcatchment. 

31 
300 0 

270 1 

2-yr storm 

2-yr 

10-yr 

100-yr 

0:00 1:00 2:00 3:00 4:00 5:00 

time (hr:min) 

240 

210 

2 

3 

Q(cfs) 

180 

150 

120 

90 

60 

30 

0 

4 

5 

6 

7 

8 

9 

10 

in/h 

Remaining Parameters 

The remaining subcatchment properties for the developed site (roughness 

coefficients, depression storages, and infiltration parameters) are kept the same as they 

were for the undeveloped condition. Likewise, the same analysis options were used to run 

the simulations. Refer to Tables 1-1 and 1-3 for a listing of the parameter values used in 

the undeveloped condition. 

1.6 Model Results – Developed Site 

Outlet Hydrographs 

Figure 1-11 shows the outlet hydrographs (the Total Inflow to node O1) obtained 

for each of the design storms under post-development conditions in the study site. As 

with the pre-development hydrographs, the peak runoff flow occurs close to when the 

peak rainfall does and there is a significant increase in peak discharge as the return period 

increases. Unlike the pre-development case, the post-development’s hydrographs show a 

more rapid decline once the rainfall ceases. This behavior can be attributed to the much 

larger amount of imperviousness under the post-development condition (57%) as 

compared to pre-development (5%). Table 1-8 summarizes the results obtained for each 

design storm in the same fashion that Table 1-4 did for the pre-development condition. 

Figure 1-11. Runoff hydrographs (flow Q versus time) for the developed site 

32 
Table 1-9. Comparison of runoff for pre- and post-development conditions 

Design	 

Storm 

Total 

Rainfall 

(in.) 

Runoff Volume (in.) Runoff Coeff. (%) Peak Runoff (cfs) 

Pre Post Pre Post Pre Post 

2-yr 0.978 0.047 0.53 4.8 54.50 4.14 46.74 

10-yr 1.711 0.24 1.11 13.1 64.70 7.34 82.64 

100-yr 3.669 1.87 3.04 50.8 82.70 31.6 240.95 

Table 1-8. Summary of results for post-development conditions 

Design 

Storm 

Peak 

Rainfall 

(in./h) 

Total 

Rainfall 

(in.) 

Runoff 

Volume 

(in.) 

Runoff 

Coeff. 

(%) 

Peak 

Runoff 

(cfs) 

Total 

Infiltration 

(in.) 

% of 

Rainfall 

Infiltrated 

2-yr 2.85 0.978 0.53 54.5 46.7 0.42 42.9 

10-yr 4.87 1.711 1.11 64.7 82.6 0.58 33.8 

100-yr 9.95 3.669 3.04 82.7 241 0.61 16.6 

Pre- and Post-Development Comparison 

Table 1-9 compares total runoff volumes, runoff coefficients, and peak discharges 

computed for both the pre- and post-development conditions. For larger storm events, 

where infiltration plays a minor role in the runoff generation, the responses become more 

similar between the two cases. Total runoff volume under post-development conditions is 

approximately 10, 5, and 2 times greater than under pre-development conditions for the 

2-yr, 10-yr, and 100-yr storms, respectively. Peak flows are about 10 times greater for 

both the 2-yr and 10- yr storms but only 7 times greater for the 100-yr event. 

1.7 Summary 

This example used SWMM to estimate the runoff response to different rain events 

for a 29 ac development that will be built in a natural area. Comparisons were made 

between the runoff peaks and total volume for each event for both pre- and postdeveloped conditions. The key points illustrated in this example were: 

1.	 Building a SWMM model for computing runoff requires that a study area be properly 

partitioned into a collection of smaller subcatchment areas. These can be determined 

by examining the potential pathways that runoff can travel as overland flow and the 

location of the collection channels, both natural and constructed, that serve to 

intercept this runoff. 

2.	 Initial estimates of most subcatchment parameters can be based on published values 

that are tabulated for various soil types and land uses. The primary exception to this is 

the width parameter which should be based on the length of the overland-flow path 

that the runoff travels. 

33 
3.	 Path lengths for true overland flow should be limited to about 500 ft or to the distance 

at which a collection channel/pipe is reached if it is less than 500 ft. 

4.	 Urban development can create large increases in the imperviousness, peak-runoff 

flow rate, and total-runoff volume. 

The next case study, Example 2, will further refine the model built in this example 

by adding a stormwater collection system to it and routing the runoff flows through this 

system. 

34 
Example 2. Surface Drainage Hydraulics 

Example 1 showed how to construct a hydrologic model of an urban catchment 

that compared stormwater runoff under both pre- and post-development conditions. 

Hydraulic routing was not considered. This example will demonstrate how SWMM’s 

hydraulic elements and flow routing methods are used to model a surface drainage 

system. A conveyance network will be added to the post-development model built in 

Example 1 and be sized to pass the 2 hour synthetic storm events with return periods of 

2-, 10-, and 100-years. For simplicity, open channels (e.g. swales or gutters) will be used 

to convey flow. The simple routing network developed in this example will be built upon 

further in Example 7 where additional open channels and below-ground pipes will be 

added that are designed according to typical drainage design criteria. 

2.1 Problem Statement 

Figures 2-1 and 2-2 show the SWMM model layouts of the pre- and postdevelopment study area developed in Example 1. In Figure 2-1 the pre-development site 

was represented by a single subcatchment whose width parameter was determined by 

assuming a maximum overland flow length of 500 ft, as recommended for undeveloped 

areas. For the developed case (Figure 2-2), the post-development site was discretized into 

seven subcatchments, the subcatchment widths were computed using an area-weighted 

average of the flow lengths across each type of area, and all subcatchments discharged 

their overland flow directly to the site’s outlet, node O1 (see Section 1.5 of Example 1). 

The objective of this example is to add a simple surface drainage system to the 

post-development site. A system of gutters, grass swales, and culverts will be designed 

and sized to convey the 100-yr storm. Runoff from three design storms (the 2-, 10- and 

100-yr storms) will be routed through this system using the three alternative hydraulic 

routing methods available in SWMM. The resulting outflow hydrographs at the site’s 

outlet will be compared to those generated in Example 1 where no hydraulic routing was 

used. 

2.2 System Representation 

SWMM models a conveyance network as a series of nodes connected by links 

(Figure 2-3). Links control the rate of flow from one node to the next and are typically 

conduits (e.g. open channels or pipes) but can also be orifices, weirs or pumps. Nodes 

define the elevation of the drainage system and the time-varying hydraulic head applied 

at the end of each link it connects. The flow conveyed through the links and nodes of the 

model is ultimately discharged to a final node called the outfall. Outfalls can be subjected 

to alternative hydraulic boundary conditions (e.g. free discharge, fixed water surface, 

time varying water surface, etc.) when modeled with Dynamic Wave. The properties of 

these drainage system elements are explained in detail in the sidebar “Hydraulic Elements 

in SWMM”. 

35 
Figure 2-1. Pre-development site 

Hydraulic routing is the process of combining all inflows that enter the upstream 

end of each conduit in a conveyance network and transporting these flows to the 

downstream end over each instance of time. The resulting flows are affected by such 

factors as conduit storage, backwater, and pipe surcharging. SWMM can perform 

hydraulic routing by three different methods: Steady Flow, Kinematic Wave and Dynamic 

Wave. These three methods are summarized below. 

• Steady Flow 

Steady Flow routing is an instantaneous translation of a hydrograph from the 

upstream end of a conduit to the downstream end with no time delay or change in 

shape due to conduit storage. Steady Flow routing will simply sum the surface runoff 

from all subcatchments upstream of the selected node through time. 

36 
 

Figure 2-2. Post-development site without conveyance system 

Figure 2-3. Links and Nodes 

37
 
Type of Hydraulic 

Element 

Category of 

Element 

Examples or 

Types 

Required 

Properties 

Optional
 

Properties 

Junction -Manholes 

-Points of change 

in conduit slope or 

cross section 

-Invert elevation 

-Maximum depth 

-Initial depth 

-Surcharge depth 

-Treatment 

-Inflows 

-Ponded area 

Divider -Cutoff 

-Tabular 

-Weir 

-Overflow 

-Invert elevation 

-Diversion link 

-Type 

-Maximum depth 

-Initial depth 

-Ponded area 

-Surcharge depth 

-Treatment 

-Inflows 

Nodes 

Storage 

Unit 

-Reservoirs 

-Peak shaving 

detention ponds 

-BMPs 

-Invert elevation 

-Storage curve 

-Maximum depth 

-Initial depth 

-Treatment 

-Inflows 

-Evaporation factor 

Outfall -Free	 

-Normal 

-Fixed 

-Tidal 

-Invert elevation 

-Type 

-Inflows 

-Treatment 

-Tide gate 

-Time series 

Conduit -Natural channels 

-Closed conduits 

-Inlet node 

-Outlet node 

-Initial flow

-Maximum flow 

-Open Channels -Shape and section 

geometry 

-Length 

-Roughness 

-Inlet offset 

-Entry loss coefficient 

-Exit loss coefficient 

-Average loss 

coefficient 

Links 

Pump	 

Orifice 

-Outlet offset 

-Off-line 

-In-line 

incremental 

-Variable speed 

in-line 

-Inlet node 

-Outlet node 

-Pump curve 

-Initial status 

-Startup depth 

-Shutoff depth 

-Circular orifice 

-Rectangular 

orifice 

-Inlet node 

-Outlet node 

-Type 

-Shape and geometry 

-Inlet offset 

-Flap gate 

-Time to open/close 

Weir 

-Discharge coefficient 

-Transverse	 

-Side-flow 

-Inlet node 

-Outlet node 

-Flap gate 

-End contractions 

-V-notch 

-Trapezoidal 

-Type 

-Geometry 

-Inlet offset 

-End coefficient 

Outlet 

-Discharge coefficient 

-Used to model 

special headdischarge 

relationships 

-Inlet node 

-Outlet node 

-Inlet offset 

-Rating curve 

-Flap gate 

Hydraulic Elements in SWMM 

All hydraulic elements modeled in SWMM are classified as either nodes or links. 

The hierarchy of these elements is shown below along with both the required and optional 

properties that characterize each element’s hydraulic behavior. 

38 
• Kinematic Wave 

Kinematic Wave uses the normal flow assumption for routing flows through the 

conveyance system. In Kinematic Wave routing, the slope of the hydraulic grade line 

is as the same as the channel slope. Kinematic Wave routing is most applicable to the 

upstream, dendritic portions of drainage systems where there are no flow restrictions 

that might cause significant backwater or surcharging. It can be used to approximate 

flows in non-dendritic systems (i.e., those that have more than one outflow conduit 

connected to a node) only if “flow divider” nodes are used. 

• Dynamic Wave 

Dynamic Wave routing is the most powerful of the flow routing methods because it 

solves the complete one-dimensional Saint Venant equations of flow for the entire 

conveyance network. This method can simulate all gradually-varied flow conditions 

observed in urban drainage systems such as backwater, surcharged flow and flooding. 

Dynamic Wave can simulate looped conduit systems and junctions with more than 

one link connected downstream (bifurcated systems). The ability to simulate 

bifurcated systems allows one to model pipes and gutters in parallel; this more 

advanced level of modeling will be described in Example 7. 

2.3 Model Setup 

System Layout 

Figure 2-4 shows the layout of the runoff conveyance system that will be added to 

the developed site. It consists of 7 grass swales, 3 culverts, and one street gutter. The 

objective in this example is to estimate the discharges at the outlet of the site and not 

design all of the elements within the entire drainage system. For this reason, only the 

main surface conduits that route runoff to the outlet in the aggregated model will be 

considered. These will purposely be oversized to ensure that all the generated runoff is 

conveyed to the outlet and that no flooding occurs within the site (see Example 7 for an 

analysis of surcharged pipes and flooded junctions). The starting point for building this 

model is the input file Example1-Post.inp that was created in Example 1. 

In Example 1, the subcatchment widths were set to properly represent the 

overland flow process. All the subcatchments were directly connected to the outlet of the 

study area; flows through channels were not modeled. In this example, the subcatchment 

properties will remain the same as defined previously, but conduits representing the 

channelized flow throughout the site will be added into the model. 

The definition of the conveyance system begins by specifying the location of its 

nodes (or junctions). A node is required wherever runoff enters the conveyance system, 

whenever two or more channels connect and where the channel slope or cross section 

changes significantly. They are also required at locations with weirs, orifices, pumps, 

storage, etc. (see Example 3 where orifices and weirs are used as outlets to a storage 

unit). The locations of the nodes for this example are shown in Figure 2-5. They are 

labeled J1 through J11. The invert elevation of each node (i.e., the elevation at the 

bottom of the lowest connecting channel) is shown in Table 2-1. 

39 
Figure 2-4. Post-development site with runoff conveyance added 

40
 
J6 

J1 

J8 

J7 

J4 J5

J3 

J2 

J9 

J11 

J10 

C9 

C8 

C7 

C5 C6

C4

C3 

C2 

C1 

C10 

C11 

O1 

Table 2-1. Invert elevations of junctions 

Junction ID Invert Elevation (ft) 

J1 4973.0 

J2 4969.0 

J3 4973.0 

J4 4971.0 

J5 4969.8 

J6 4969.0 

J7 4971.5 

J8 4966.5 

J9 4964.8 

J10 4963.8 

J11 4963.0 

Figure 2-5. SWMM representation of the post-development conveyance system 

41 
Table 2-2. Subca

Subcatchment 

S1 

tchment outlets 

Outlet Junction 

J1 

Outlet Conduit 

C1(Swale) 

S2 J2 C2 (Gutter) 

S3 J3 C3 (Culvert) 

S4 J7 C6 (Swale) 

S5 J10 C10 (Swale) 

S6 J11 C11 (Culvert) 

S7 J10 C10 (Swale) 

The definition of the conveyance system continues by adding the feeder channels 

C1, C2 and C6 that convey runoff into the main drainage way that runs through the 

undeveloped park area of the site. Conduit C1 is a grass swale that drains subcatchment 

S1’s runoff to the watershed’s main drainage way; Conduit C2 is a gutter that carries 

subcatchment S2’s runoff to the upstream end of the culvert (C11) that discharges to the 

site’s outlet (O1); conduit C6 carries runoff from subcatchment S4 into culvert C7. At 

this point, the elevations of the bottom bed of these channels correspond to the invert 

elevations of their respective upstream and downstream junctions. Their lengths are 

automatically determined by drawing them with Auto-Length turned on. SWMM uses 

this information to compute the slope of each channel. 

Finally, the remaining conduits C3 through C11 that comprise the main drainage 

way through the park to the outlet need to be defined. As before, they connect to their end 

nodes with no vertical offset and the Auto-Length tool is used to compute their lengths. 

Subcatchments S3 through S7 drain to different locations of the main drainage channel. 

S3 drains to the culvert (C3) at the beginning of the main drainage channel, S4 drains to 

the swale C6 that connects to the second culvert (C7) on the main drainage channel, S7 

and S5 drain to the main drainage channel at J10, and S6 drains directly to the last culvert 

(C11) on the main drainage channel. Table 2-2 summarizes the outlet junction and 

conduit associated with each subcatchment. 

Note that the conveyance system modeled in this example (Figure 2-5) ignores the 

storage and transport provided by the street gutters within each subcatchment. In some 

applications, however, these conveyance elements can play a significant role and should 

be represented, perhaps by adding a channel within each subcatchment that represents the 

aggregated effects of routing through all of its street segments. To keep the example 

simple, this level of detail is not included and only the major drainage channels within the 

site are considered. 

System Properties 

Properties can now be assigned to the conduits and junctions that have been 

defined. Table 2-3 shows the cross-sectional shapes of the three conduit types used in this 

example. The swale side slopes (Z1 and Z2 (horizontal:vertical)), roughness coefficient 

(n), bottom width (b) and height (h) of the swale section are as recommended by the 

42 
Table 2-3. Characteristics of the conduits used in the model 

Type of Shape Cross Section Representing D (ft) Z1 Z2 b (ft) h (ft) n 

Trapezoidal Swales - 5 5 5 3 0.05 

Trapezoidal Gutters - 0.00011 25 0 1 0.016 

Circular Culverts 4.752 - - - - 0.016 

1

UDFCD Manual (2001). The gutter cross-slopes (Z1 and Z2), roughness coefficient (n), 

bottom width (b) and height (h) are based on typical design practice. The culvert 

diameters will be sized as described in the next section to convey runoff from the 100­

year storm. 

 SWMM cannot accept a slope of zero 

2

 This is the initial diameter of the culverts, not the final value 

Table 2-4 shows the SWMM properties assigned to each conduit. Conduit lengths 

were computed using the Auto-Length option as described in the previous section. The 

inlet and outlet offset of all the conduits, with one exception, were set to zero which 

means that the bottom elevation of each conduit coincides with the elevation of its inlet 

and outlet junctions. The exception is conduit C2 (the gutter), whose outlet offset of 4 ft 

represents the difference in elevation between the bottom of the gutter and the channel 

bed in the park. The diameters of the three circular culverts will be determined in the next 

section. 

Table 2-4. Conduit properties 

Conduit Type of Inlet Outlet Length h (ft) or b (ft) Z1 Z2 ID Conduit Node Node (ft) D (ft) 

C1 Swale J1 J5 185 3 5 5 5 

C2 Gutter J2 J11 526 1 0 0.0001 25 

C3 Culvert J3 J4 109 TBD - - -

C4 Swale J4 J5 133 3 5 5 5 

C5 Swale J5 J6 207 3 5 5 5 

C6 Swale J7 J6 140 3 5 5 5 

C7 Culvert J6 J8 95 TBD - - -

C8 Swale J8 J9 166 3 5 5 5 

C9 Swale J9 J10 320 3 5 5 5 

C10 Swale J10 J11 145 3 5 5 5 

C11 Culvert J11 O1 89 TBD - - -

TBD = To Be Determined 

43 
Because the conduits are all surface channels and not buried pipes, it is sufficient 

to set the maximum depth of all the junctions as zero. This will cause SWMM to 

automatically set the depth of each junction as the distance from the junction’s invert to 

the top of the highest conduit connected to it. Thus, junction flooding (the only flooding 

allowed by SWMM) will occur when the channel capacity is exceeded. Finally, the 

outfall node O1 is defined as a free outfall (see the sidebar “Hydraulic Elements in 

SWMM”) with an elevation of 4962 ft. The resulting SWMM input file has been named 

Example2-Post.inp. 

2.4 Model Results 

Culvert Sizing 

Before SWMM’s alternative routing methods are compared, the diameters of the 

three culverts in the conveyance system must be determined. This is done by finding the 

smallest available size for each culvert from those listed in Table 2-5 that will convey the 

runoff from the 100-year, 2-hr design storm without any flooding. This process involves 

the following steps: 

1.	 Start with each culvert at the largest available diameter. 

2.	 Make a series of SWMM runs, reducing the size of conduit C3 until flooding occurs. 

Set the size of C3 to the next larger diameter. 

3.	 Repeat this process for conduit C7 and then for C11. 

Note that one proceeds systematically from upstream to downstream, making sure 

that each culvert in turn is just big enough to handle the flow generated upstream of it. 

This procedure is appropriate because there is no flooding under the baseline condition 

(with the culverts at their maximum possible size). The approach should not necessarily 

be applied when pipe diameters have to be enlarged (or when there is flooding under the 

baseline condition). It is very common to find design situations in which changes 

downstream have significant effects upstream, so that a minor change in the diameter of a 

pipe located downstream may solve flooding problems upstream. 

Table 2-5. Available culvert sizes 

Diameter Diameter Diameter Diameter Diameter Diameter Diameter Diameter 

(ft) (in) (ft) (in) (ft) (in) (ft) (in) 

1 12 2 24 3 36 4 48 

1.25 15 2.25 27 3.25 39 4.25 51 

1.5 18 2.5 30 3.5 42 4.5 54 

1.75 21 2.75 33 3.75 45 4.75 57 

These culvert-sizing runs are made using the Example2-Post.inp file with the 

routing method set to KW (Kinematic Wave), the Rain Gage’s time series set to 100-yr, 

and the following set of time steps: 1 minute for reporting, 1 h for dry weather, 1 minute 

for wet weather and 15 s for routing. Note that the routing time step is somewhat 

stringent for the drainage system being modeled and the routing method used (KW). It is 

44 
Table 2-6. Maximum depths and flows for conduits during the 100-yr event 

Conduit Maximum Depth Maximum Flow 

ID Full Depth Full Flow 

C1 0.37 0.11 

C2 0.96 0.94 

C3 0.70 0.83 

C4 0.38 0.12 

C5 0.67 0.41 

C6 0.44 0.16 

C7 0.71 0.85 

C8 0.70 0.44 

C9 0.88 0.76 

C10 0.88 0.74 

C11 0.78 0.95 

used here, however, because Dynamic Wave routing will be used later in this example 

and it typically requires smaller time steps than Kinematic Wave to produce stable results. 

If just KW routing were used for this model, the routing time step could probably be 

safely set to 1 minute (see sidebar “A Note About Time Steps”). The presence or absence 

of flooding is determined by examining the Node Flooding Summary section of a run’s 

Status Report. 

A Note About Time Steps 

SWMM requires that four time steps be specified: runoff time steps for both 

wet weather and dry weather, a flow routing time step, and a reporting time step. 

The most common error new users make is to use time steps that are too long. The 

runoff wet weather time step should not exceed the precipitation recording interval. 

The flow routing time step should never be larger than the wet weather time step, 

and in most cases should be 1 to 5 minutes (or less) for Kinematic Wave routing and 

30 s (or less) for Dynamic Wave routing. Dynamic Wave routing can also employ a 

Variable Time Step option that automatically lowers the time step during periods 

when flows change rapidly. High continuity errors typically result when runoff or 

routing time steps are too large. If the reporting time step is set too high important 

details in the output results might be missed. Setting the reporting time step equal to 

the routing time step helps prevent this, but can generate very large output files. 

Starting with smaller time steps, users can experiment with larger time steps to find 

one that produces acceptably accurate results most efficiently. 

After making these sizing runs with Example2-Post.inp, the final diameters 

selected for the culverts are 2.25 ft for C3, 3.5 ft for C7, and 4.75 ft for C11. Table 2-6 

lists the fraction that each conduit is full and the fraction of its full Manning flow that is 

reached under peak flow conditions for the 100-year event. These values are available 

from the Link Flow Summary table of SWMM’s Status Report. 

45 
100 0 

2-yr storm 90 1 

2-yr, steady 

80 2 2-yr, K.W 

70 2-yr, D.W. 3 

Example 1

60 4 

50

Q(cfs) 

5 

in/h 

40 6 

30 7 

20 8 

10 9 

0 10 

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 

time (hr:min) 

Comparison of Routing Methods 

Having adequately sized the culverts, the model is next run using all three routing 

methods (Steady Flow, Kinematic Wave, and Dynamic Wave) to obtain the outlet 

discharges which are then graphed by design storm along with the discharges found from 

Example 1. Figures 2-6, 2-7 and 2-8 show the outflow hydrographs (Total Inflow to node 

O1) generated for each design storm using all three hydraulic routing methods. As in 

Example 1, these graphs were created by first exporting the pertinent SWMM results for 

each run to a spreadsheet and then using the spreadsheet’s graphing tools. For Steady 

Flow routing the outlet flows are identical to the flows generated in Example 1 (shown as 

a dotted line) except for the case of the 100-yr design storm which produced flooding 

within the system, This is because the discharge that appears at the outlet of each 

subcatchment in Steady Flow routing instantaneously appears at the site outlet where it is 

added to the discharges of the other subcatchments of the watershed. Thus, Steady Flow

routing produces results at the site outlet that would have been generated had no channels 

been simulated in the model. 

Regarding flooding, the Steady Flow method indicates potential for flooding in 

the system by computing the flow depth in the conduits using Mannings equation; if this 

depth exceeds the channel capacity, the flow is truncated to the full-flow capacity of the 

conduit and flooding is reported. Figure 2-8 shows this difference between the outlet 

discharges generated by the Steady Flow routing method and the simulation without 

routing when flooding does occur. 

Figure 2-6. Post-development outflow hydrographs for 2-yr storm 

46
Q(cfs) 

150 0 

135 10-yr storm 

10-yr, steady 

1 

120 10-yr, K.W 2 

105 

10-yr, D.W. 

Example 1

3 

90 4 

75 5 

60 6 

45 7 

30 8 

15 9 

0 10 

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 

time (hr:min) 

in/h 

210 

240 

270 

300 

100-yr storm 

100-yr, steady 

100-yr, K.W 

100-yr, D.W. 

Example 1

0 

2 

4 

6 

Q(cfs) 

180 8 

150 10 

120 12 

90 14 

60 16 

30 18 

0 20 

0:00 0:30 1:00 1:30 2:00 2:30 3:00 3:30 4:00 4:30 5:00 

time (hr:min) 

in/h 

Figure 2-7. Post-development outflow hydrographs for 10-yr storm 

Figure 2-8. Post-development outflow hydrographs for 100-yr storm 

47
Table 2-7. 

Design	 

Storm 

2-yr 

Comparison 

Total 

Rainfall 

(in.) 

0.98 

of runoff for post-develop

Runoff Volume (in.) 

No Routing1 DW 

0.53 0.53 

ment conditions with and w

Runoff Coeff. (%) 

No Routing DW 

54.5 54.5 

ithout routing 

Peak Runoff (cfs) 

No Routing DW 

46.7 33.4 

10-yr 1.71 1.11 1.11 64.7 64.7 82.6 62.2 

100-yr 3.67 3.04 3.04 82.7 82.7 241 164.1 

The other two routing methods, Kinematic and Dynamic Wave, both produce a 

time-lag and a reduction in the peak flow, spreading the volume of the outlet hydrograph 

out over time. These effects are more pronounced under Dynamic Wave routing because 

it accounts for backwater that can increase even further the storage utilized within the 

conveyance system. 

Table 2-7 compares total runoff volumes, runoff coefficients, and peak discharges 

at the outlet computed for the post-development model without routing (from Example 1) 

and with Dynamic Wave (DW) routing from this example. These values come directly 

from SWMM’s Status Report. In terms of runoff volumes and coefficients, the results 

obtained with routing are identical to those found in Example 1 where no hydraulic 

routing was considered. The effects of routing are observed in the comparison of peak 

flows, which decrease when routing is considered. In the case of this example, peaks 

produced with Dynamic Wave routing are 28.7% smaller for the 2-yr storm, 24.8% 

smaller for the 10-yr storm and 32.4% smaller for the 100-yr storm in comparison to the 

peaks produced when no routing was considered. 

1

Results from Example1-Post.inp 

2.5 Summary 

This example introduced the use of hydraulic routing in SWMM. It demonstrated 

how a surface runoff collection system is laid out, how to size the elements of this 

system, and the effect that routing of runoff flows through this system has on the 

catchment’s outlet hydrograph. Comparisons were made between the runoff peaks and 

total volume for different design storm events using each of SWMM’s three routing 

options as well as with no routing. The key points illustrated in this example are: 

1.	 A runoff collection system can be represented as a network of links and nodes, where 

the links are conduits (such as grass swales, street gutters, and circular culverts) and 

the nodes are the points where the conduits join to one another. 

2.	 An iterative process that proceeds from upstream to downstream can be used to 

determine the minimum conduit size needed to prevent flooding under a particular 

extreme design event. 

3.	 Steady Flow hydraulic routing produces outlet discharges identical to those produced 

without routing unless there is flooding in the drainage system. The method 

instantaneously translates hydrographs from the upstream end of a conduit to the 

downstream end, with no delay or change in shape. 

48 
4.	 Dynamic Wave and Kinematic Wave routing produce smaller peak runoff discharges 

than models without routing (Example 1) due to storage and possible backwater 

effects within the channels. Routing with Dynamic Wave resulted in a decrease of 

32.4% for the 100-yr peak outlet flow. 

5.	 Except for flooding, the choice of routing method (Steady Flow, Kinematic Wave or 

Dynamic Wave) does not affect the total volume of runoff that leaves the study area 

through the outlet. 

In the next case study, Example 3, a storage unit will be added to the postdevelopment drainage system developed in this example to mitigate the effects that 

urbanization has on receiving streams. 

49 
Table 3-1. Pre- and post-development peak discharges 

Return Rainfall Depth Pre-development Peak Post-development Peak 

Period (yr) (in.) Discharge (cfs)1 Discharge (cfs)2
 

2 0.98 4.14 33.5 

10 1.71 7.34 62.3 

100 3.67 31.6 163.8 

Example 3. Detention Pond Design 

This example illustrates how to define, design, and evaluate a detention pond 

using SWMM. Storage units, orifices and weirs will be used to model a multi-purpose 

detention pond built to detain a water quality capture volume (WQCV) and control peak 

post-development release rates to their pre-development levels. The urban catchment 

studied in Examples 1 and 2 will also be used in this example. 

Storage is widely used in urban runoff quantity and quality control, providing 

both peak flow reduction and suspended solids removal. The design criteria for storage 

structures have changed over time due to an improved understanding of the effects that 

urban runoff has on the environment. Facilities must control not only the extreme runoff 

events to prevent flooding, but also the more common smaller events that produce a “first 

flush” pollution phenomenon and thereby impact the quality of receiving water bodies. 

3.1 Problem Statement 

In Example 1 a model was built to estimate the pre-development runoff from a 29 

acre site. Additional models were constructed to estimate the site’s post-development 

runoff both without flow routing (Example 1) and with routing through a surface 

collection system (Example 2). Total site runoff for the 2-, 10- and 100-yr design storms 

was computed for both the pre- and post-development conditions. Based on the results of 

these models, it is now required to design a detention pond immediately downstream of 

the planned urban development to both prevent flooding and protect water quality in a 

receiving stream. It is required that the pond reduce the peak discharges of the 2-, 10- and 

100-yr storms to those of the undeveloped site, and that extended detention be provided 

for a specific water quality capture volume. 

Table 3-1 shows the discharges to be controlled by the pond. The predevelopment peaks were determined in Example 1 (Table 1-9 in Section 1.5) and postdevelopment peaks were determined in Example 2 (Table 2-7 in Section 2.4). The 

SWMM input files that produced these results are Example1-Pre.inp and Example2-

Post.inp, respectively. The 2-, 10- and 100-yr rainfall hyetographs are included in both 

these input files. 

1

 From Example1-Pre.inp 

2

 From Example2-Post.inp 

50 
In addition to controlling the discharges listed, it is required that a Water Quality 

Capture Volume (WQCV) be controlled. The WQCV is defined as a suitable volume 

expressed in units of watershed depth that is detained for a long enough period of time to 

achieve a targeted level of pollutant removal. The required volume and drawdown time 

vary under different stormwater control policies (Akan and Houghtalen, 2003). In this 

example, the WQCV must be released over 40 hours, during which a significant portion 

of particulate pollutants found in urban stormwater are removed. Finally, for safety 

reasons, a maximum storage depth of 6 ft is considered for the final design. In this 

example the minor storms ( the WQCV and 2-yr storm) and the major storms (the 10- and 

100-yr storms) runoff will be detained in separate sections of the detention pond. Both 

sections will have the shape of a trapezoidal prism. The location of the pond within the 

developed study area is shown in Figure 3-1. 

Figure 3-1. Detention pond location for the post-development site 

51 
3.2 System Representation 

The main elements used to design detention ponds in SWMM are storage units 

with orifice and weir outlets. These three elements are described below: 

1.	 Storage units 

Storage units in SWMM are modeled as nodes. They are similar to the conveyancesystem junction nodes introduced in Example 2 but have some fundamental 

differences: storage volume is described by a Storage Curve, an Evaporation Factor 

can be specified, and a Maximum Depth of storage must be defined. 

•	 Storage Curve: This curve defines the shape of a storage unit by describing 

how the surface area within the unit varies with water depth. This curve is 

integrated by SWMM to compute stored volume as a function of depth. It can 

be specified to the model as either a functional equation or as a tabular curve 

(area-depth pair data). 

•	 Evaporation Factor: To allow evaporation from the surface of a storage unit 

one sets its Evaporation Factor to 1 and provides evaporation data to the 

model using SWMM’s Climatology Editor. The default value for this 

parameter is 0, implying that evaporation is ignored. 

•	 Maximum Depth: The maximum depth of a storage unit must be defined and 

should not be left at the default zero value. If the storage unit’s depth is not 

defined, the model will assume the storage unit has a zero depth even if a 

storage curve has been assigned or a conduit is connected to the storage unit. 

If the largest depth on the storage curve is below the maximum depth, the last 

area value on the curve will be extended outward. 

2.	 Orifices 

SWMM’s orifice-type link can be used to represent the opening along the side or 

bottom of the storage unit that serves as an outlet. The upstream node of the orifice is 

the storage unit while its downstream node would be a junction that connects it to a 

downstream conduit. Orifice properties that need to be defined include its height 

above the bottom of the storage unit (invert offset), its type (side or bottom orifice), 

its geometry (rectangular or circular shape and the respective dimensions) and its 

hydraulic properties (discharge coefficient and the presence/absence of a flap gate to 

prevent backflows). 

3.	 Weirs 

SWMM’s weir-type link can be used to represent the opening at the top of the storage 

unit that serves as an overflow structure. As with the orifice, the upstream node of the 

weir is the storage unit while its downstream node connects it to a downstream 

conduit. Weir properties that need to be defined include the weir’s height above the 

bottom of the storage unit, its type (transverse, V-notch or trapezoidal), its geometry 

and its hydraulic properties (discharge coefficients, end contractions and the 

presence/absence of a flap gate to prevent backflows). 

52 
Converting Node and Link Elements 

Nodes need not be deleted and links redrawn to replace a node with a 

storage unit or to define orifices and weirs in SWMM. Instead, they can be 

converted. For example, a node can be converted to a storage unit by following the 

procedure outlined below. 

Convert a Node to a Storage Unit 

1.	 Right-click on the node to be converted and choose “Convert to...” from the 

pop-up menu as show in the figure below. 

2.	 Select “Storage Unit” from the sub-menu that appears. 

3.	 Open the Property Editor for the new storage unit and define its new name 

(e.g. SU1). The new unit is given the invert elevation and maximum depth of 

the node from which it was converted. 

4.	 Enter any additional properties needed to define the behavior of the storage 

unit (such as its Storage Curve). 

Convert a Conduit to an Orifice 

Like nodes, links can be converted to other types of links. Follow the steps 

below to convert the conduit connecting a storage unit to an outfall into an orifice. 

1.	 Right-click on the conduit downstream of the storage unit and choose 

“Convert to...” from the pop-up menu. 

2.	 Select “Orifice” from the sub-menu that appears.. 

3.	 Open the Property Editor of the orifice and define its dimensions, invert 

offset and discharge coefficient. 

Convert an Outfall to a Node 

4.	 If the storage unit (SU1) is to have more than one orifice, then the orifices 

cannot be connected directly to an outfall (O1). The outfall must be converted 

into a node (O1) in this case and a new outfall created (O2). Convert the 

outfall using the same procedure described above. 

53 
3.3 Model Setup 

SWMM can be used to model storage facilities that capture runoff from different 

design storms and release it to a receiving channel at a controlled rate. This example 

demonstrates how the design of a storage pond is an iterative process in which the 

dimensions of the pond and its outlets are changed to satisfy the design criteria and 

constraints for the design storms considered. The three main steps used to design the 

storage pond are: 

1.	 Estimate the water quality capture volume (WQCV). 

2.	 Size the storage volume and the outlet to control the release rate of the WQCV. 

3.	 Size the storage volume and the outlet to control the peak runoff rates from the 2-, 10- 

and 100-yr design storms. 

The final design will be a storage unit with a shape specific to its location, rainfall 

and climate conditions; a defined relationship between its surface area and storage depth; 

and a multi-outlet structure designed to control different runoff events. Figure 3-2 shows 

the schematic of a detention pond and its outlets designed to control a WQCV and the 

peak discharges for three design storms. The stacked trapezoidal prism shape shown in 

this figure will be used in this example; the upper prism will control the major storms 

(10- and 100-yr) while the lower prism will control the minor storms (WQCV and 2-yr). 

Note that the discharge for different storms is controlled by a combination of 

orifices and weirs rather than a single unique outlet. Orifice 1 in Figure 3-2 controls the 

release of the WQCV; orifices 1 and 2 control the release of the 2-yr storm; orifices 1, 2 

and 3 control the release of the 10-yr storm and all the orifices combined together with 

the weir (4) control the release of the 100-yr storm. 

Estimation of the Water Quality Capture Volume 

The WQCV is the critical runoff volume to be used in the design of stormwater 

quality enhancement facilities. Detailed investigation based on calibrated long-term 

runoff simulations is the preferred method to determine this volume for a given site (Guo 

and Urbonas, 1996). However, several methodologies or “rules of thumb” have been 

proposed to estimate the WQCV that are simpler to use but still reliable when long-term 

records are not available (see for instance Guo and Urbonas, 1995, 1996 and 2002; Water 

Environment Federation, 1998). This example will use the methodology proposed by the 

UDFCD (2001). Figure 3-3 shows the curves defined in this methodology to estimate the 

WQCV as a function of the tributary catchment’s total imperviousness and the drain time 

of the capture volume. The following steps are used to estimate the WQCV for the 

detention basin being designed in this example: 

54 
100-yr 

1 

2 

3 

4 

10-yr 

2-yr 

WQCV 

Major 

Storm 

Volume 

WQCV & 

Minor Storm 

Volume 

Figure 3-2. Schematic representation of a detention pond 

Figure 3-3. Water quality capture volume (UDFCD, 2001) 

55
 
Table 3-2. Post-development subcatchment data 

Subcatchment S1 S2 S3 S4 S5 S6 S7 

Area (ac) 4.55 4.74 3.74 6.79 4.79 1.98 2.33 

Imperviousness (%) 56.8 63 39.5 49.9 87.7 95 0 

 

1.	 First, determine the developed site’s average Directly Connected Impervious Area 

(DCIA). DCIA is the impervious area that is directly connected to the stormwater 

drainage system; it does not include rooftops, patios, etc. that drain to lawns or other 

pervious areas, and is smaller than the gross or total impervious area that is typically 

estimated through aerial photography. These areas were previously estimated for each 

of the seven subcatchments defined for the post-development site condition in 

Example 1 and are presented in Table 3-2. 

2.	 Next calculate the site’s average percent imperviousness by weighting the 

imperviousness of each subcatchment by its area and dividing by the total area 

(28.94-ac) of the study area. The average percent imperviousness of the site 

determined by this method is 57.1% ≈ 57%. 

3.	 The next step is to determine the WQCV in watershed inches. Assume that the 

example site is located in Colorado’s high plains near the foothills and that the 

storage unit is to have a 40 hr drain time. From Figure 3-3 the corresponding WQCV 

in watershed inches is 0.23 in. Thus the total water quality control volume is 28.94­

ac·0.23 in/12 = 0.555 acre-ft or 24,162 ft3. 

4.	 If the design location were not in Colorado’s high plains near the foothills, one would 

need to adjust the WQCV determined from Figure 3-3. The curves shown in Figure 3­

3 are defined to control the 80th percentile runoff event and are appropriate for use in 

Colorado’s high plains near the foothills. For other locations, the WQCV from Figure 

3-3 can be adjusted to obtain an appropriate volume, WQCVo, using Equation 3-1. In 

this equation, d6 is the average precipitation depth of the runoff-producing storms. 

Storm events for Equation 3-1 were defined for a 6-hour inter-event period and have a 

minimum depth of 0.1 in. Figure 3-4 shows estimates of d6 for the contiguous United 

States (UDFCD, 2001). 

WQCV WQCVO = d6	 (3-1) 0.43 

Pond Geometry and Dimensions 

The shape of the storage unit will depend on the regulations in the location where 

the structure will be constructed. Generally, it is recommended that the distance between 

the inlet and outlet of the facility be maximized; a length to width ratio of 2:1 to 3:1 is 

adequate. This example will use a length to width ratio of 2:1, a WQCV depth (h1) of 1.5 

ft, and a side slope of 4:1 (H:V). Figure 3-5 shows the geometry of the WQCV and 

equations developed based on the length to width ratio (2:1) and the storage unit side 

slope (4:1) that describe the unit’s geometry. The steps used to determine the dimensions 

of the WQCV are: 

56 
Figure 3-4. Average depth (inches) of runoff producing storms in the US (Driscoll, et al., 1989) 

Figure 3-5. Geometry of the pond's WQCV 

1.	 Solve for L3 using the WQCV found in the previous section (24,162 ft3) and h1 equal 

to the WQCV depth (1.5 ft). Rearranging the fifth equation listed in Figure 3-5 yields 

the following quadratic equation for L3: 

2 2 4L	 + 24h L + (64h − 2V / h ) = 0 3 1 3 1 WQCV 1
 

Solving for L3 gives L3 = 85.15 ft ≈ 86 ft. 

57
 
 

2.	 Next solve for the other dimensions of the WQCV using L3 and h1. From the first 

equation from the top in Figure 3-5, L1 = 170.3 ft ≈ 171 ft, from the second equation 

L2 = 184 ft, and from the third equation L4 = 98 ft. 

3.	 Then define the storage curve for the WQCV portion of the storage unit. At 0 depth 

the area is L1·L3 = 14,706 ft2 while at the full depth of 1.5 ft the area is L2·L4 = 18,032 

ft2. These pairs will be entered into the model in the following section together with 

new points in the surface area-depth curve representing the shape shown in Figure 3-2 

to control larger volumes. 

Adding a Storage Unit to the Model 

The Example2-Post.inp file will be used as a starting point to add a storage unit into the 

model that represents the detention pond. The following steps are taken to define the 

storage unit. 

1.	 A new Storage Curve object named SU1 is created to represent the shape of the 

storage unit. 

2.	 The two previously determined depth-area points are entered into the Curve Editor 

dialog for curve SU1. These two points are d1 = 0, A1 = 14706 ft2

 and d2 = 1.5 ft, A2 = 

18032 ft2. 

3.	 A new storage unit node, also named SU1, is placed onto the study area map as 

shown in Figure 3-6, and is left disconnected from the drainage system. The 

following properties are assigned to SU1; Storage Curve = Tabular; Curve Name = 

SU1; Invert Elevation = 4956 ft (six feet lower than the outfall node elevation defined 

in the previous examples); Maximum Depth and Initial Depth = 1.5 ft (the maximum 

allowable depth defined to control the WQCV). 

4.	 An additional node (J_out), conduit (C_out) and outfall node (O2) are added that will 

connect the orifices and weirs draining the storage unit (SU1) to the outfall node 

(O2). This must be done because it is not possible to connect more than one hydraulic 

link to an outfall node in SWMM. The invert elevations of J_out and O2 are set to 

4954 ft to avoid backwater effects (again, details in the geometric definition of the 

storage unit will depend on the local conditions and it is not the intention of this 

example to cover these details) and C_out is given a length of 100 ft and a roughness 

of 0.01. Figure 3-7 shows the independent storage unit system, the tabular storage 

curve SU1 for the WQCV and the storage unit’s Properties table. 

Initially, the storage unit and its WQCV orifice are modeled independent of the 

watershed to size the WQCV orifice to drain in 40 hours. Although the storage unit and 

the watershed are shown in the same input file in Figure 3-6, they will run as independent 

systems in the model because they are not hydraulically connected. The location of the 

pond in Figure 3-6 will be its final location in the model. The pond could have been 

placed in the park area since there is significant open space for it, but for clarity it was 

placed at the downstream end of the park. 

58 
Figure 3-6. Study area map with storage unit SU1 

Figure 3-7. Properties of storage unit SU1 

59
 
Sizing the WQCV Orifice 

The next step is to design the pond outlet so that the entire WQCV is released 

within 40 hours. The outlet will be an orifice connecting the storage unit to the 

downstream outfall O2. This orifice could be located at the bottom or side of the storage 

unit and be either circular or rectangular in shape. The following steps are used to size the 

orifice so the WQCV drains in 40 hours. 

1.	 A side orifice (Or1) is added between the storage unit (SU1) and the node (J_out) 

leading to the outfall node. It is given a rectangular shape and assigned an inlet offset 

of zero so that its invert is the same as the storage unit. Its discharge coefficient is 

assumed to be the default value of 0.65. 

2.	 The simulation time step options are set as follows: reporting, wet-weather and 

routing time steps to 15 seconds and the dry-weather time steps to 1 hr. The 

simulation duration must be longer than 40 hours so that the performance of the 

orifice can be properly evaluated; this example uses 72 hours. 

3.	 The final dimensions of orifice Or1 are determined by running SWMM several times 

using Dynamic Wave flow routing while iteratively changing the orifice dimensions 

until a size is found that drains the WQCV in approximately 40 hours. For each run, 

the dimensions of the orifice are varied while keeping the initial water depth in the 

storage unit at the depth of the WQCV, 1.5 ft. One can assume that the basin is 

essentially empty once the water depth is 0.05 ft. Note that the runoff discharge 

generated by the rainfall falling on the subcatchments does not affect the storage unit 

during this part of the example because it is not connected to the drainage system. 

Figure 3-8 shows the drainage time for three iterations as well as that for the final 

design. Table 3-3 shows the dimensions assigned to the orifice by iteration. The final 

orifice design has a height of 0.3 ft and a width of 0.25 ft. This small size is typical of a 

WQCV orifice. That is why the orifice must be protected by a screen to prevent plugging 

during the storm and maintenance must be done regularly to ensure the screen remains 

free of debris. 

Table 3-3. Design of the WQCV outlet (Or1) 

Iteration 1 2 3 Final 

Height (ft) 0.166 0.25 0.25 0.3 

Width (ft) 0.25 0.25 0.4 0.25 

Inlet Offset (ft) 0 0 0 0 

Discharge Coefficient 0.65 0.65 0.65 0.65 

Drainage time (hr:min) 53:58 43:21 27:07 40:12 

60 
0 

0.3 

0.6 

0.9 

1.2 

1.5 

depth (ft) 

Iteration 1 

Iteration 2 

Iteration 3 

Final 

0 8 16 24 32 40 48 56 64 72 

time (hr) 

 

Figure 3-8. WQCV drainage times for the iterations shown in Table 3-3 

Sizing the 2-yr Design Storm Orifice 

The runoff volume generated by the 2-yr storm will be larger than the WQCV 

volume designed for in the previous section. The volume of the storage unit must now be 

enlarged and a new outlet must be defined. This new outlet, which will be placed at a 

height of 1.5 ft above the basin floor, will begin to discharge when the runoff volume 

from any storm just exceeds the WQCV. This outlet will control not only the peak runoff 

rate of the 2-yr storm but also partially control the runoff rate from storms greater than 

the 2-yr storm. The required increase in storage volume will be achieved by extending the 

sides of the storage unit above the WQCV depth while keeping a lateral slope of 4:1 

(H:V) as shown in the basin schematic, Figure 3-2. The following steps outline how the 

storage unit is sized for the 2-yr design storm orifice. 

1.	 The storage unit is first connected to the rest of the drainage system. This can be done 

by changing culvert C11’s outlet to SU1 and deleting the original outfall node O1. 

Culvert C11 is given a downstream offset of 1ft so that for minor storms it has no 

backwater but still has its crown below the top of the storage pond. 

2.	 Next the size of the pond is enlarged for flood control by expanding its height while 

keeping a constant slope (refer to Figure 3-2 for an illustration). This is done by 

entering a new pair of surface area-depth pairs to the storage curve SU1. The values 

for this new pair are: d3 = 6 ft, A3 = 29583 ft2

. The initial depth of the storage unit is 

set to zero and its maximum depth to 6 ft to account for the new volume. 

3.	 The model is then run for the 2-yr storm using only the WQCV orifice to determine 

the maximum depth in the storage unit, the peak discharge of the WQCV orifice 

(Or1), and the time it takes the storage unit to empty. The results show a maximum 

61 
 

storage unit depth of 2.82 ft, a maximum orifice discharge of 0.64 cfs and an 

emptying time of 56:23 (hr:min). 

4.	 Based on the results in step 3, the peak outflow for the 2-yr storm can be increased 

because the pre-development 2-yr peak runoff (4.14 cfs from Table 3-1) is larger than 

the discharge through the WQCV orifice (0.64 cfs). Increasing this discharge is 

advantageous because it will reduce the final volume of the storage required and save 

in costs. To increase the 2-yr storm pond outflow, a second orifice (Or2) is added 

directly above the WQCV depth (inlet offset = 1.5 ft) as illustrated in Figure 3-2. This 

orifice is assigned a rectangular shape with an inlet offset of 1.5 ft and a discharge 

coefficient of 0.65. It should be drawn on the map with at least one intermediate 

vertex so that it can be distinguished from the existing orifice Or1 (see the sidebar 

“Drawing Links as Polylines”). 

Drawing Links as Polylines 

SWMM allows links to 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 its interior points 

can be added, deleted, and moved. This 

feature is especially useful when two or 

more links share the same set of end 

nodes and would otherwise appear 

directly on top of one another on the 

map. The figure on the right shows how 

polylines were used to draw the various 

orifices and weirs that comprise the 

outlet structure of a storage unit so that 

they could be distinguished from one 

another. 

5.	 An initial estimate of Or2’s area A is made using the orifice equation: 

)

1/ 2 Q = CA(2gh	 (3-2) 

with C = 0.65, Q = (4.14 – 0.64) cfs = 3.5 cfs and h = (2.84 – 1.5) ft = 1.34 ft. This 

produces an orifice area of 0.58 ft2. Assume Or2 has an initial height of 0.58 ft and a 

width of 1 ft. 

6.	 Running the model with these dimensions for Or2 produces a discharge of 2.84 cfs. 

This value is less than the target discharge (4.14 cfs). Therefore, iterations must again 

be used to size orifice Or2 as was done for Or1 until the combined peak discharge of 

the two orifices is equal to or a little less than the 2-yr pre-development peak 

discharge (4.14 cfs). 

62 
 

7.	 To simplify the iterations for sizing Or2 its height is fixed at 0.5 ft and its width is 

varied in 0.05 ft increments until the combined discharge of both orifices is close to 

4.14 cfs. A size of 0.5 by 2 ft produces a peak discharge of 4.11 cfs and a maximum 

storage unit depth of 2.21 ft. These dimensions will thus be used for the 2-yr orifice. 

Sizing the 10-yr Design Storm Orifice 

Up to this point the storage unit has been represented as a single trapezoidal 

prism. This shape was determined for the WQCV back in the “Pond Geometry and 

Dimensions” section and increased in size (keeping the 4:1 side slope) to contain the 2-yr 

storm runoff. In this section the storage unit shape is redefined by adding an additional 

trapezoidal prism over the minor storm prism to contain the 10- and 100-yr storm 

volumes (See Figure 3-2). The steps below show how this is done to size the 10-yr storm 

orifice: 

1.	 The storage curve SU1 is modified by replacing the surface area-depth pairs d2,A2 

and d3,A3 with the following three surface area-depth pairs: d2 = 2.22 ft, A2 = 19659 

ft2

; d3 = 2.3 ft, A3 = 39317 ft2 and d4 = 6 ft, A4 = 52644 ft2. Note that the new d2,A2 

point is the highest point of the original shape (the maximum height of the 2-yr 

storm) . The area of point 3 (A3 = 39317 ft2

) doubles the area of point 2 (A2 = 19659 

ft2

). The depth, d3 is set 0.1 feet above d2 so that the change in cross sectional area is 

not too abrupt. In practice this transitional area would have a slope of 2% so that 

water in storage will drain into the smaller basin after the storm. The area of point 4 is 

computed by extending the sides of the storage unit above the point 3 while keeping a 

lateral slope of 4:1 (H:V). 

2.	 The model is run with the 10-yr storm and the existing orifices to determine if a 10-yr 

storm orifice is needed. The resulting maximum water depth is 3.20 ft and the 

combined peak discharge from both existing outlets is 6.96 cfs. The pre-development 

peak discharge for the 10-yr storm is 7.34 cfs which means that the storage unit 

volume can again be decreased by adding another orifice. 

3.	 A new 10-yr storm orifice (Or3) is added directly above the depth of the volume 

designed to control the 2-yr storm runoff (inlet offset = 2.22 ft). As with Or2, Or3 is 

drawn with intermediate vertices so that it can be seen easily on the system map. The 

orifice equation (3-2) is used to estimate its required area. For C = 0.65, Q = (7.34 – 

6.96) cfs = 0.38 cfs and h = (3.20 – 2.22) ft = 0.98 ft the resulting orifice area is 0.073 

ft2. A height of 0.25 ft and a width of 0.25 ft are used as an initial estimate of the 

orifice’s size. 

4.	 When the model is run with the 10-yr storm for this size of Or3, the combined 

discharge is 7.22 cfs. Because this discharge is less than the pre-development 

discharge (7.34 cfs), the orifice’s width is increased to 0.35 ft and the model is re-run. 

The new combined discharge is 7.32 cfs and the maximum depth in the storage unit is 

3.17 ft. This is sufficiently close to the target discharge to accept this orifice size 

(height = 0.25 ft, width = 0.35 ft). 

63 
 

Designing the 100-yr Weir 

The model can now be run with the 100-yr storm using the combined WQCV, 2­

yr and 10-yr orifices to determine if the 100-yr weir is needed. The peak discharge of 

these combined orifices for the 100-yr storm is 12.57 cfs, which is not enough to pass the 

100-yr storm’s runoff (31.6 cfs), and the storage unit floods. A weir will be designed to 

control this extreme event so that the pre-development discharge is matched and the total 

water depth in the pond does not exceed the 6 ft depth that was given as the maximum 

depth for safety reasons. This is accomplished as follows: 

1.	 A new weir link W1, drawn with intermediate vertices, is added between the storage 

unit and the node (J_out) leading to the final outfall. It is specified as a transverse 

weir whose inlet offset is 3.17 ft above the storage unit bottom (the maximum depth 

reached by the volume controlling the 10-yr storm runoff), and whose discharge 

coefficient is 3.3. The height of the weir opening is set at 2.83 ft which is the distance 

between the volume controlling the 10-yr storm runoff and the maximum depth of the 

storage unit. 

2.	 The weir equation (3-3) is used to determine an initial width L for the weir: 

Q = CLh3 / 2	 (3-3) 

Using Q = (31.6 – 12.57) cfs = 19.03 cfs, C = 3.3 and h = 2.83 ft produces a width of 

3.43 ft ≈ 3.45 ft. 

3.	 With weir dimensions of height = 2.83 ft, width = 3.45 ft and invert offset = 3.17 ft 

the model is run for the 100-yr storm. The resulting peak total discharge from the 

storage unit is 42.4 cfs which exceeds the target flow of 31.6 cfs. 

4.	 Step 3 is repeated with successively smaller weir widths until a combined discharge 

close to 31.6 cfs is obtained. A width of 1.75 ft produces a combined 100-yr 

discharge of 31.2 cfs and a maximum depth of 5.42 ft in the storage unit. 

5.	 The final step is to insure that adequate freeboard is maintained in the storage unit. 

The current design provides 6.0 – 5.43 = 0.53 ft. The required amount will depend on 

local design guidelines. For example, the UDFCD (2001) requires a freeboard of 1 

foot above the maximum water surface elevation when the weir is conveying the 

maximum discharge. 

3.4 Model Results 

The final SWMM model for the post-development site with the detention pond is 

shown in Figure 3-9 and its input file is named Example3.inp. Table 3-4 summarizes the 

characteristics of the different discharge elements included in the pond’s outlet, which are 

illustrated in Figure 3-10. 

64 
 

Figure 3-9. Final design of the detention pond and outlet structure 

Orifice & Weir 

Dimensions Offsets 

6 ft 0.25 ft 

0.5 ft 

1.5 ft 2.22 ft 

3.17 ft 

0.3 ft 

2.83 ft 

Hmax= 5.43 ft 

Figure 3-10. Detail of the pond outlet structure 

65 
Table 3-4. Characteristics of the pond's outlet structure 

ID Type of 

Element 

Event 

Controlled Shape Height 

h (ft) 

Width 

b (ft) 

Invert 

Offset Z (ft) 

Discharge 

Coefficient 

Or1 

Or2 

Orifice 

Orifice 

WQCV 

2-yr 

Side 

Rectangular 

Side 

Rectangular 

0.3 

0.5 

0.25 

2 

0 

1.5 

0.65 

0.65 

Or3 Orifice 10-yr Side 

Rectangular 0.25 0.35 2.22 0.65 

W1 Weir 100-yr Rectangular 2.83 1.75 3.17 3.3 

The outflow hydrographs produced by this final design for the detention pond 

were compared against those resulting with no control as well as against the predevelopment discharge targets. Those target discharges were 4.14, 7.34 and 31.6 cfs for 

the 2-, 10- and 100-yr storms, respectively. The post-development controlled 

hydrographs were generated using the input file for the final design of this example 

(Example3.inp), while the post-development uncontrolled discharges were generated 

using the final design developed in Example 2 (Example2-Post.inp). The predevelopment hydrographs were generated using the final design developed in Example 1 

for the pre-development watershed (Example1-Pre.inp). The models were run using a 15 

second time step for reporting, wet-weather runoff and flow routing and a 1 hr dry 

weather runoff time step. 

The resulting sets of hydrographs are shown in Figures 3-11 through 3-13. Once 

again a spreadsheet program was used to combine results from different SWMM runs 

onto one graph. They verify that the detention pond was able to control post-development 

peak discharges from the site to their pre-development levels. Note, however, that the 

storage unit had no effect on reducing the total volume of post-development runoff that 

resulted from the large increase in impervious area. 

3.5 Summary 

This example showed how SWMM could be used to design a detention pond and 

its outlet structure to provide both a water quality capture volume (WQCV) and peak 

runoff control. The WQCV was designed to provide a 40 hour drawdown time to satisfy 

water quality treatment requirements while the peak runoff goal was to limit the 

maximum post-development discharges for the 2-, 10- and 100-yr storms to their predevelopment values. The key points illustrated in this example were: 

66 
0:00

4:008:00

12:00 

0 

4 

8 

12 

16 

20 

24 

28 

32 

36 

Q (cfs)

 2-yr, uncontrolled

 2-yr, controlled

 2-yr, pre-developed 

time (hr:min) 

0:004:00

0 

6 

12 

18 

24 

30 

36 

42 

48 

54 

60 

66 

8:00

12:00 

Q (cfs) 

10-yr, uncontrolled 

10-yr, controlled 

10-yr, pre-developed 

time (hr:min) 

Figure 3-11. Outlet hydrographs for the 2-yr storm 

Figure 3-12. Outlet hydrographs for the 10-yr storm 

67 
0 

20 

40 

60 

80 

100 

120 

140 

160 

180 

Q (cfs) 

100-yr, uncontrolled 

100-yr, controlled 

100-yr, pre-developed 

0:004:008:00

12:00 

time (hr:min) 

Figure 3-13. Outlet hydrographs for the 100-yr storm 

1.	 The WQCV’s outlet structure can be designed by using a full storage unit (volume = 

WQCV) disconnected from the drainage system and an orifice whose dimensions are 

varied until the storage is drained in a time equal to that defined by local regulation 

(40 hr in this example). 

2.	 The dimensions of the other component of the outlet structures (e.g. orifices and 

weirs) used to control peak flows can be designed sequentially. The maximum water 

depth reached using one design storm is the location of the invert offset of the orifice 

or weir used to control the next larger design storm. 

3.	 The orifice and weir equations are useful for making initial estimates of an outlet’s 

dimensions. 

4.	 Although detention storage is effective in controlling peak runoff rates it has no effect 

on reducing runoff volume. 

This example will be extended to include water quality treatment associated with 

the storage pond in Example 6 and continuous simulation in Example 9. 

68 
Example 4. Low Impact Development 

This example demonstrates how to model two Low Impact Development (LID) 

control alternatives, filter strips and infiltration trenches. The detention pond modeled in 

Example 3 is an example of a subdivision-scale drainage control structure. The LIDs in 

this example are hydrologic source controls that operate on a smaller scale and rely 

heavily on infiltration and distributed small-scale storage to reduce the overall runoff 

volume from a watershed and control water quality. 

SWMM is better suited to simulating some types of hydrologic source control 

techniques than others. Filter strips and infiltration trenches are two such source controls. 

This example will illustrate how they can be represented in SWMM by applying them to 

the same catchment area studied in the previous Examples 1, 2 and 3. 

4.1 Problem Statement 

In Examples 1 and 2, runoff estimates for the 29 acre residential development 

shown in Figure 4-1 were made without any source controls in place. In this example, the 

effects that infiltration trenches (IT) and filter strips (FS), two commonly used LIDs, have 

on the site’s runoff will be examined. As illustrated in Figure 4-1, four infiltration 

trenches will be placed at each side of the east-west street in the upper part of the study 

area. Additionally, filter strips will be used to control the runoff from lots S, M and M2, 

located in the southwest section of the site. These strips will be built along the sidewalks 

so they control runoff from the lots before it reaches the gutters. 

In Example 3 the quantitative objective for the design of a detention pond was to 

reduce the post-development watershed discharge to pre-development levels. The LIDs 

modeled here will not be designed to accomplish a specific quantitative objective but 

rather to achieve a general reduction in runoff volume to help meet sustainability goals 

and place a lower burden on stormwater controls further downstream in the basin. The 

performance of the LIDs for the 2-, 10- and 100-yr storms will be analyzed. 

4.2 System Representation 

The two LIDs modeled here are filter strips and infiltration trenches. Guidance in 

the representation of these and other LIDs can be found in Huber at al. (2006). 

69 
Figure 4-1. Post-development site with LIDs in place 

Filter Strips 

Filter strips are grassed or vegetative areas through which runoff passes as sheet 

flow. They do not effectively reduce peak discharges but are effective in removing 

particulate pollutants for small storms (< 1 year storm) (Akan and Houghtalen, 2003). 

Flat slopes (<5%) and low to fair permeability (0.15 to 4.3 mm/h or 0.006 to 0.17 in/h) of 

natural subsoil are required for their effective operation (Sansalone and Hird, 2003). 

SWMM does not have a unique visual object to represent filter strips but they can be 

represented as a pervious subcatchment that receives runoff from an upstream 

subcatchment as illustrated in Figure 4-2. The two most important processes that must be 

simulated with filter strips are infiltration and storage. A filter strip can be simulated as a 

100% pervious subcatchment whose geometry (area, width and slope) is obtained directly 

70 
from the field. This subcatchment receives water from an upstream contributing area 

(impervious or semi-impervious) and drains to a conduit representing the gutter or street. 

The infiltration for a filter strip can be simulated using any of SWMM’s infiltration 

options. 

Figure 4-2. Schematic representation of a filter strip 

Infiltration Trenches 

Infiltration trenches are excavations backfilled with stone aggregate used to 

capture runoff and infiltrate it to the ground (Guo, 2001). Subsoil with a minimum 

permeability of 13 mm/h (0.5 in/h) is required for a good performance (U.S. EPA, 1999). 

The most important processes that must be simulated for an infiltration trench are 

infiltration, storage and the water flow along the trench. Figure 4-3 shows a workable 

SWMM representation of an infiltration trench. It consists of a rectangular, fully pervious 

subcatchment whose depression storage depth equals the equivalent depth of the pore 

space available within the trench. 

71 
Figure 4-3. Schematic representation of an infiltration trench 

4.3 Model Setup – Filter Strips 

Figure 4-1 shows the locations of the filter strips (FS) to be modeled in this 

example. The initial SWMM file to which the LIDs will be added is Example2-Post.inp, 

which includes both subcatchments and a runoff conveyance system in it. Figure 4-1 will 

be used as the backdrop of the new model to help facilitate the placement of the filter 

strips. The image file for this backdrop is named Site-Post-LID.jpg. Table 4-1 lists the 

subcatchment to which each filter strip belongs and the length of each strip. 

Table 4-1. Subcatchments containing filter strips 

Subcatchment controlled Filter Strip Filter Strip Length (ft) 

S3 FS 1 410 

S3 FS 2 105 

S3 FS 3 250 

S4 FS 4 359 

S4 FS 5 190 

S4 FS 6 345 

S3 and S4 FS 7 375 

72 
 

73
 

Sub-Area Routing in SWMM 

An alternative method to modeling LIDs, other than creating additional 

subcatchments as used in this example, is to use Sub-Area Routing. Each 

subcatchment modeled in SWMM is composed of two sub-areas, an impervious 

sub-area and a pervious sub-area, and options called Sub-Area Routing and Percent 

Routed appear in their Properties tables. 

Sub-Area Routing has three options: Outlet, Impervious and Pervious. The 

Outlet option ((a) in the figure below) routes the runoff from both sub-areas directly 

to the subcatchment’s outlet. The Pervious option ((b) in the figure below) routes 

the runoff from the impervious sub-area across the pervious sub-area and then to 

the outlet, and the Impervious option ((c) in the figure below) routes the runoff 

from the pervious sub-area across the impervious sub-area and then to the outlet. 

When the runoff from the impervious surface is routed across the pervious 

surface ((b) in the figure below), some of the runoff is lost to infiltration and 

depression storage in the pervious sub-area. The graph below shows the typical 

effect on runoff these three sub-area routing methods have when applied to a single 

subcatchment. Note that because the runoff produced by the pervious area in this 

case is negligible, the “100% routed to Outlet” and the “100% routed to 

Impervious” cases are practically the same. 

0 

0.5 

1 

1.5 

2 

2.5 

3 

3.5 

4 

0:00:00 1:12:00 2:24:00 3:36:00 4:48:00 

Time (hr) 

Q (cfs) 

100% routed to 

Outlet, 2-yr 

100% routed to 

Pervious, 2-yr 

100% routed to 

Impervious, 2-yr 

The Sub-Area Routing - Pervious option can be used to model LIDs. This is 

done by representing the LID as the pervious sub-area, setting the subcatchment’s 

pervious values to those of the LID, routing the runoff from the impervious subarea of the subcatchment to the pervious subarea, and defining the Percent Routed 

to represent the percentage of impervious surface connected to the LID. 

Modeling LIDs with this method implies that the entire subcatchment’s 

pervious surface represents the LID. This approach is not as flexible as the one 

presented in this example because the slope and width of the LID must be those of 

the subcatchment, which is not always the case. 
Table 4-2. Properties of the new junctions 

New Junction Invert Elevation (ft) 

J15 4974.5 

J16 4973.5 

J17 4973.5 

Table 4-3. Properties of the new conduits 

New Inlet Outlet Length Type of Manning Maximum Bottom Left Right 

Conduit Node Node (ft) Section1 Coefficient Depth (ft) Width (ft) Slope Slope 

C15 J15 J3 444.75 Swale 0.05 3 5 5 5 

C16 J17 J5 200.16 Swale 0.05 3 5 5 5 

C17 J16 J7 300.42 Gutter 0.016 1.5 0 0.0001 25 

1 Type of section based on those defined in Example 2 

The filter strips to be constructed are identified in Table 4-1 with letters FS and a 

number. In the model being built some of the strips will be aggregated together as they 

are represented as new subcatchments. These filter-strip subcatchments will be identified 

as “S_FS_number”. 

To better estimate the runoff treated by the filter strips, subcatchments S3 and S4 

will be discretized further. S3 will be divided into three subcatchments S3.1, S3.2 and 

S3.3 and S4 into four subcatchments S4.1, S4.2, S4.3 and S4.4 as shown in Figure 4-4. It 

will be necessary to re-estimate the average overland runoff length and new 

subcatchment widths, slopes and percents imperviousness to place in the model. Refer to 

Example 1 for help in determining the new subcatchments’ hydrologic properties. The 

slopes of the new subcatchments representing lots will be 2%. The same Horton 

infiltration rates already defined in the previous examples will be used here: 4.5 in/hr for 

the maximum, 0.2 in/hr for the minimum and 6.5 hr-1 for the decay constant. With the 

addition of these new subcatchments and the re-discretization of some of the original 

ones, it is necessary to define new channels and junctions to connect them to the drainage 

system. These new elements are illustrated in Figure 4-4 (pipes in red and junctions in 

blue). Table 4-2 lists the properties of the new junctions and Table 4-3 does the same for 

the new conduits. 

Table 4-4 summarizes the properties of the new subcatchments. The outlets of the 

new subcatchments (S3.2, S3.3, S4.2, and S4.3) are not junctions but filter strips 

represented as subcatchments. This cascade layout used in the SWMM model is shown in 

Figures 4-5 for subcatchments S3.1, S3.2 and Figure 4-6 for subcatchments S4.1, S4.2, 

S4.3 and S4.4. 

The length of the filter strips (i.e., the overland flow length existing between lots 

and streets) will be 4 feet and the slope of each strip along this length is the same as the 

typical lot slope of 2%. The widths of the strips (perpendicular to the overland flow 

direction) is computed directly from the map with the Ruler tool as explained in Example 

1 and are given in the last column of Table 4-5. 

74 
Table 4-4. Proper

New 

Subcatchment 

S3.1 

ties of the subcatc

Outlet 

J3 

hments deriv

Area (ac) 

1.29 

Width (ft) 

614 

ed from S3 and S4 

Slope (%) 

4.7 

Imperviousness (%) 

0 

S3.2 S_FS_1 1.02 349 2 65 

S3.3 S_FS_2 1.38 489 2 58 

S4.1 J6 1.65 580 5 0 

S4.2 S_FS_3 0.79 268 2 70 

S4.3 S_FS_4 1.91 657 2 65 

S4.4 J9 2.40 839 2 69 

Figure 4-4. Re-discretization of subcatchments S3 and S4 

75 
 

 

 

S4.2

S4.1

S4.3

J16

J7

J6

Table 4-5. Widths of the filter strip subcatchments 

Filter 

Strip 

Subcatchment 

Controlled Composition Partial Widths (ft) Total Widths (ft) 

S_FS_1 S3.2 FS 1 410 410 

S_FS_2 S3.3 FS 2 + FS 3 + part FS 7 105 + 250 + 108 463 

S_FS_3 S4.2 Part FS 7 267 267 

S_FS_4 S4.3 FS 4 + FS 5 + FS 6 359 + 190 + 345 894 

Figure 4-5. Representation of subcatchments S_FS_1, S3.1, and S3.2 

S_FS_3

J16 C17 J7 C6 J6

S_FS_3 

S4.2 J16 C17 J6

S4.1 

J7 C6 

S4.3 

J16 

J7 

J6 

S_FS_4 

Figure 4-6. Representation of subcatchments S_FS_3, S_FS_4, S4.1, S4.2, and S4.3 

Table 4-6 summarizes the characteristics of the subcatchments used to model the 

filter strips in this example. The areas of the filter strips are calculated from the lengths of 

the strips measured in the model and the flow path length (4 ft) used in this example. This 

76 
 

 

 

 

means the areas calculated by Auto-Length for these subcatchments will be replaced with 

those calculated in Table 4-6. 

Table 4-6. Properties of the filter strip subcatchments 

Subcatchment Upstream 

Subcatchment Outlet Area1 

(ft2

) 

Area 

(ac) 

Width2 

(ft) 

Slope 

(%) 

Depression3 

Storage (in) 

S_FS_1 S3.2 J15 1640 0.038 410 2 0.3 

S_FS_2 S3.3 J17 1852 0.043 463 2 0.3 

S_FS_3 S4.2 J16 1068 0.025 267 2 0.3 

S_FS_4 S4.3 J16 3576 0.082 894 2 0.3 

Once the filter strip properties shown in Tables 4-5 and 4-6 are added to the 

model, all filter strips are assigned a zero percent imperviousness, an impervious 

roughness of 0.015 and an impervious depression storage of 0.06 in (although neither of 

the latter properties are used due to 0% imperviousness); a pervious roughness of 0.24, 

and a pervious depression storage of 0.3 in. These last two values are the same as those 

for the rest of the pervious areas within the watershed. Finally, both the maximum and 

minimum infiltration rates for Horton infiltration are set to the same value, 0.2 in/hr, 

which is the minimum infiltration rate of the soil in the study area. This is a conservative 

approach that takes into account possible losses to infiltration capacity as well as the fact 

that soil may be saturated at the beginning of a new storm. 

All subcatchments must have a rain gage assigned to them in order for the 

SWMM model to run. However, no rain should fall on the subcatchments representing 

the filter strips because their areas are considered part of the subcatchments within which 

they were placed. Thus, a new Time Series called “Null” is defined with a single time and 

rain value equal to zero. A new rain gage also called “Null” is created and linked to the 

time series “Null”. This gage is defined to be the rain gage of all the filter strip 

subcatchments, while the subcatchments that generate runoff are connected to the original 

rain gage “RainGage”, as in the previous examples. 

4.4 Model Setup – Infiltration Trenches 

The infiltration trenches (IT) included in this example are located in the north part 

of the study area (see Figure 4-1). To model these devices subcatchments S1 and S2 are 

first divided into six smaller subcatchments as shown in Figure 4-7. Their areas are 

determined automatically by using the SWMM’s Auto-Length tool. Their widths are 

based on an assumed urban runoff length of 125 ft (measured from the back of the lot to 

the street), as discussed in Example 1. The imperviousness of each newly sub-divided 

subcatchment is based on the type of land use (M, L or DL) as listed in Table 1-6 of 

Example 1. Table 4-7 summarizes the properties of the newly sub-divided 

subcatchments. The remaining properties not shown in the table (Horton infiltration, 

pervious depression storage, etc.) are the same as those given to the original 

subcatchments. 

77 
Table 4-7. Proper

New 

Subcatchment 

S1.1

ties of the subc

Outlet

 J12 

atchments 

Area 

(ac) 

1.21 

derived fro

Width 

(ft) 

422 

Slope 

(%) 

2 

m S1 and S2 

Imperviousness 

(%) 

65 

S1.2 S_IT_1 1.46 509 2 65 

S1.3 S_IT_2 1.88 655 2 45 

S2.1 J14 1.30 453 2 45 

S2.2 S_IT_3 1.50 523 2 70 

S2.3 S_IT_4 1.88 655 2 70 

Figure 4-7. Re-discretization of subcatchments S1 and S2 for infiltration trenches 

The infiltration trenches added to the model are identified in Table 4-8. Their 

names begin with the letters IT followed by a number. The location of these infiltration 

trenches is shown in Figure 4-7. The four infiltration trenches are added into the model as 

78 
 

 

 

 

 

 

 

subcatchments and have an S_ prefix added to their name. They serve as the outlets of 

subcatchments S1.2, S1.3, S2.2 and S2.3 as shown in Table 4-9. The outlets of the other 

new subcatchments, S1.1 and S2.1, are junctions J12 and J14, respectively. 

When sizing the infiltration trenches, note that the definition of length and width 

is opposite of the manner in which length and width were defined for filter strips. The 

length of each infiltration trench is listed in Table 4-8. The trench area can be computed 

using this length and assuming a width of 3 ft. The widths and areas of each infiltration 

trench are listed in Table 4-9. Each trench is modeled as having a depression storage 

depth of 1.2 ft (below this depth water is infiltrated, while above this depth there is flow 

along the trench). The actual storage depth of the infiltration trenches is 3 ft, but when the 

40% porosity of the 1-1/2 in. diameter gravel filling the trenches is considered, the depth 

of the trenches available to store the water to be infiltrated is reduced to 40% of the actual 

trench depth. Table 4-9 summarizes the properties assigned to the infiltration trench 

subcatchments. 

Table 4-8. Subcatchments containing infiltration trenches 

Subcatchment Controlled Infiltration Trench Trench Length (ft) 

S1 IT 1 450 

S1 IT 2 474 

S2 IT 3 450 

S2 IT 4 470 

Table 4-9. Properties of the infiltration trench subcatchments 

Subcatchment Upstream 

Subcatchment Outlet Area1 

(ft2

) 

Area1 

(ac) 

Width 

(ft) 

Slope2 

(%) 

Depression3 

Storage (in) 

S_IT_1 S1.2 J1 1350 0.031 3 0.422 14.4 

S_IT_2 S1.3 J1 1422 0.033 3 0.422 14.4 

S_IT_3 S2.2 J13 1350 0.031 3 0.444 14.4 

S_IT_4 S2.3 J13 1410 0.032 3 0.468 14.4 

1 Area = length of the trench × 3 ft width perpendicular to the flow direction. 2 Slope as computed from the site map.
 3 This corresponds to the effective depth of the trench, 0.4 x 36 in. 

The slopes of the infiltration trenches are calculated directly from the site map, 

their imperviousness is 0%, their Manning’s roughness coefficient is 0.24, and their 

storage depths are accounted for by setting their depression storage to the effective 

storage depth of 14.4 in (1.2 ft). As was done for the filter strips, a constant (minimum) 

soil infiltration capacity of 0.2 in/hr will be used for the infiltration trenches. This ignores 

any horizontal infiltration that might occur through the sides of the trench. Also the rain 

gage assigned to each trench subcatchment is the newly created “Null” rain gage so that 

no rainfall occurs directly over the trench’s area. 

79 
Table 4-10. Properties of the new junctions 

New Junction Invert Elevation (ft) 

J12 4973.8 

J13 4970.7 

J14 4972.9 

Table 4-11. Properties of the new conduits 

New Inlet Outlet Length Type of Manning Maximum Bottom Left Right 

Conduit Node Node (ft) Section1 Coefficient Depth (ft) Width (ft) Slope Slope 

C12 J12 J1 281.7 Swale 0.05 3 5 5 5 

C13 J14 J13 275.5 Gutter 0.016 1.5 0 0.0001 25 

C14 J13 J2 157.48 Gutter 0.016 1.5 0 0.0001 25 

This trench design assumes there is no barrier affecting the flow of water into the 

trench. A layer of grass and soil above the 1-1/2 in. diameter gravel, for example, might 

slow the rate of flow into trench; causing a smaller quantity of flow to be treated by the 

trench. This will be touched on again in the results section of this example. 

To complete the model it is necessary to define the additional channels and 

junctions that connect the newly added subcatchments to the drainage system. These new 

elements are illustrated in Figure 4-7 (conduits in red and junctions in blue). Table 4-10 

lists the properties of the new junctions and Table 4-11 does the same for the new 

conduits. 

1

 Type of section based on sections defined in Example 2 

4.5 Model Results 

The final model with all LIDs included can be found in the file Example4.inp. It 

was run under Dynamic Wave flow routing using a wet runoff time step of 1 minute, a 

reporting time step of 1 minute, and a routing time step of 15 s for each of the three 

design storms. Figure 4-8 compares the resulting influent and effluent runoff hydrographs 

for filter strip S_FS_1 for each of the design storms. Figure 4-9 does the same for 

infiltration trench S_IT_1. Results for the other LIDs look similar to these. Tables 4-12 

and 4-13 list runoff coefficients for each filter strip and infiltration trench, respectively. 

As used here, the runoff coefficient is the ratio of the effluent-runoff volume flowing out 

of the LID to the influent-runoff volume flowing into the LID. The fractional reduction in 

runoff volume provided by the LID is simply 1 minus the runoff coefficient. 

80 
0 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

Flow (cfs) 

2-yr: Inflow 2-yr: Outflow 

10-yr: Inflow 10-yr: Outflow 

100-yr: Inflow 100-yr: Outflow 

0:00 0:15 0:30 0:45 1:00 1:15 1:30 1:45 2:00 2:15 2:30 2:45 3:00 

Time (hr:min) 

Figure 4-8. Influent and effluent hydrographs for filter strip S_FS_1 

14
 

12
 

Flow (cfs) 

2 

4 

6 

8 

10 2-yr: Inflow 2-yr: Outflow 

10-yr: Inflow 10-yr: Outflow 

100-yr: Inflow 100-yr: Outflow 

0 

0:00 0:15 0:30 0:45 1:00 1:15 1:30 1:45 2:00 2:15 2:30 2:45 3:00 

Time (hr:min) 

Figure 4-9. Influent and effluent hydrographs for infiltration trench S_IT_1 

81 
Table 4-12. Runoff coefficients for filter strips 

Runoff Coefficient 

Filter Strip 2-year Storm 10-year Storm 100-year Storm 

S_FS_1 0.95 0.98 0.99 

S_FS_2 0.95 0.98 0.99 

S_FS_3 0.96 0.98 0.99 

S_FS_4 0.94 0.97 0.99 

Table 4-13. Runoff coefficients for infiltration trenches 

Runoff Coefficient Infiltration 

Trench 2-year Storm 10-year Storm 100-year Storm 

S_IT_1 0.45 0.73 0.89 

S_IT_2 0.35 0.71 0.90 

S_IT_3 0.51 0.75 0.90 

S_IT_4 0.59 0.79 0.92 

It is apparent that filter strips provide negligible runoff control, with the outflow 

rate very nearly equaling the inflow rate for all storm magnitudes. This confirms what 

was mentioned in section 4.2 regarding the utility of filter strips, i.e. they are primarily 

pollutant removal devices and provide no benefit in controlling runoff flow rates or 

volumes. In contrast, all of the infiltration trenches provide significant reductions in 

runoff volume, particularly for the smaller rainfall events. It should be remembered, 

however, that the trenches in this example do not have grasses planted above the gravel 

backfill. Adding such a vegetative layer to the trench may reduce its effectiveness, 

depending on how it is designed. 

Figure 4-10 compares the discharges simulated at the outlet of the study area for 

each design storm (2-, 10- and 100-yr return period) both with and without LIDs. For 

each design storm LIDs reduce both runoff volumes and peak discharges. As the storm 

event becomes larger, LIDs become less effective and the attenuation of their volumes 

and peak-discharges is reduced. These percent reductions in outlet volumes and peaks are 

compared in Figure 4-11. It shows how the benefit of LID controls decrease with 

increasing size of storm. 

82 
Peak Volume 

40
 

35
 

30
 

Percent Reduction 

25
 

20
 

15
 

10
 

5
 

0
 

2-yr Storm 10-yr Storm 100-yr Storm 

0 

20 

40 

60 

80 

100 

120 

140 

160 

180 

200 

0:00 0:15 0:30 0:45 1:00 1:15 1:30 1:45 2:00 2:15 2:30 2:45 3:00 

Time (hr:min) 

Flow (cfs) 

2-yr: no LIDs 2-yr: LIDs 

10-yr: No LIDs 10-yr: LIDs 

100-yr: No LIDs 100-yr: LIDs 

Figure 4-10. Comparison of outlet discharges with and without LID controls 

Figure 4-11. Percent reduction in outlet peak flows and runoff volumes with LIDs 

83
 
4.6 Summary 

This example illustrated how SWMM can be used to evaluate two types of Low 

Impact Development (LID) alternatives, filter strips and infiltration trenches. The key 

points illustrated in this example were: 

1.	 A filter strip can be modeled as a rectangular, 100% pervious subcatchment with a 

constant infiltration rate. 

2.	 An infiltration trench can be modeled as a rectangular, 100% pervious subcatchment 

with a constant infiltration rate whose depression storage is the effective pore volume 

depth of the trench. 

3.	 Modeling these types of LIDs can require a finer level of subcatchment discretization 

to properly account for their localized placement. 

4.	 Infiltration trenches (without a top soil layer) are more effective than filter strips in 

reducing runoff volumes and peaks. 

5.	 The effectiveness of LIDs at reducing runoff volumes and peaks decreases with 

increasing size of storm event. 

Although this example used a series of design storms to evaluate LID 

performance, a more accurate estimate of their stormwater control capabilities would 

require that a continuous long-term simulation be run for the site. Using several years’ 

worth of actual rainfall inputs would allow the model to properly account for the 

variation in antecedent soil conditions between storm events. This factor becomes a 

critical concern when infiltration-based controls are being considered. Example 9 in this 

manual illustrates how to perform such a continuous simulation. 

84 
Example 5. Runoff Water Quality 

This example demonstrates how to simulate pollutant buildup and washoff in an 

urban catchment. The influence of different land uses on pollutant buildup is considered 

and both Event Mean Concentrations (EMCs) and exponential functions are used to 

represent the washoff process. 

Surface runoff quality is an extremely important, but very complex, issue in the 

study of wet-weather flows and their environmental impacts. It is difficult to accurately 

represent water quality within watershed simulation models because of a lack of 

understanding of the fundamental processes involved as well as a lack of sufficient data 

needed for model calibration and validation. SWMM has the ability to empirically 

simulate nonpoint source runoff quality as well as water quality treatment (an example of 

which will be shown in Example 6). It provides a flexible set of mathematical functions 

that can be calibrated to estimate both the accumulation of pollutants on the land surface 

during dry weather periods and their release into runoff during storm events. The same 

study area used in Examples 1 through 4 will be used to illustrate how these functions can 

be applied to a typical urban catchment. 

5.1 Problem Statement 

The 29 acre urban catchment and drainage system presented in Example 2 will be 

extended to include water quality modeling. Pollutant buildup, washoff and routing will 

be simulated in order to estimate the quality of the water released at the catchment outlet 

under post-development conditions with no runoff controls applied (meaning no BMPs or 

flow detention in the system). The study area site is shown in Figure 5-1 and the input file 

that will be modified to include water quality is named Example2-Post.inp. 

Examination of long precipitation records reveals that most storms are quite 

small. For instance, in Example 3 the water quality capture volume (WQCV) of a 

detention pond located in the Colorado high-plains near the foothills was estimated to be 

only 0.23 inches. (See Example 3 for a methodology to calculate the WQCV in other 

areas in the country.) This volume corresponds to a depth that is exceeded by only 1 in 4 

storms and is only 25% of the 2-yr design storm that was used in the previous examples 

(1.0 in). Therefore, small-sized, frequently occurring storms account for the predominant 

number of recorded events. It is these storms that result in significant portions of 

stormwater runoff and pollutant loads from urban catchments (UDFCD, 2001). 

To explore the effect of storm volume on pollutant loading, this example will 

compute runoff loads produced by two smaller-sized 2-hour storms with volumes of 0.1 

in. and 0.23 in. respectively. These loadings will be compared against those generated 

from the 2-year design event storm used in the previous examples whose volume is 1.0 

in. The time series of intensities at five minute intervals for each of the two smaller 

storms are shown in Table 5-1. 

85 
Table 5-1. Rainfall time series for the 0.1 and 0.23 inch events 

Time 

(min) 

0.1 in Storm 

(in./h) 

1 0.23 in Storm

(in./h) 

Time 

(min) 

0.1 in Storm 

(in./h) 

1 0.23 in Storm

(in./h) 

0:00 

0:05 

0:10 

0:15 

0:20 

0:25 

0:30 

0:35 

0:40 

0:45 

0:50 

0:55 

0.030 

0.034 

0.039 

0.065 

0.083 

0.160 

0.291 

0.121 

0.073 

0.043 

0.036 

0.031 

0.068 

0.078 

0.089 

0.150 

0.190 

0.369 

0.670 

0.277 

0.167 

0.099 

0.082 

0.071 

1:00 

1:05 

1:10 

1:15 

1:20 

1:25 

1:30 

1:35 

1:40 

1:45 

1:50 

1:55 

0.020 

0.019 

0.018 

0.017 

0.017 

0.016 

0.015 

0.015 

0.014 

0.014 

0.013 

0.013 

0.047 

0.045 

0.042 

0.040 

0.040 

0.038 

0.035 

0.035 

0.033 

0.033 

0.031 

0.031 

Figure 5-1. Post-development site with no runoff controls 

1

 0.23 in. corresponds to the WQCV. 

86 
These new hyetographs are defined in SWMM using its Time Series Editor. The 

names of the new rainfall series will be 0.1-in and 0.23-in, respectively. They will be 

used by the model’s single rain gage in addition to the 2-yr, 10-yr and 100-yr storms used 

in previous examples. This example will only employ the 2-yr storm along with the 0.1 

in. and 0.23 in. events. 

5.2 System Representation 

SWMM employs several specialized objects and methods to represent water 

quality in urban runoff. These tools are very flexible and can model a variety of buildup 

and washoff processes, but they must be supported by calibration data to generate 

realistic results. The following is a brief description of the objects and methods used by 

SWMM to model water quality. 

• Pollutants 

Pollutants are user-defined contaminants that build up on the catchment surface and 

are washed off and transported downstream during runoff events. SWMM can 

simulate the generation, washoff and transport of any number of user-defined 

pollutants. Each defined pollutant is identified by its name and concentration units. 

Pollutant concentrations in externally applied water sources can be added directly to 

the model (e.g. concentrations in rain, groundwater and inflow/infiltration sources). 

Concentrations generated by runoff are computed internally by SWMM. It is also 

possible to define a dependency between concentrations of two pollutants using the 

co-pollutant and co-fraction options (e.g., lead can be a constant fraction of the 

suspended solids concentration). 

• Land Uses 

Land uses characterize the activities (e.g. residential, commercial, industrial, etc.) 

within a subcatchment that affect pollutant generation differently. They are used to 

represent the spatial variation in pollutant buildup/washoff rates as well as the effect 

of street cleaning (if used) within a subcatchment. A subcatchment can be divided 

into one or more land uses. This division is done independently of that used for 

pervious and impervious sub-areas, and all land uses in the subcatchment are assumed 

to contain the same split of pervious and impervious area. The percentages of named 

land uses assigned to a subcatchment do not necessarily have to add up to 100. Any 

remaining area not assigned a land use is assumed to not contribute to the pollutant 

load. 

• Buildup 

The buildup function for a given land use specifies the rate at which a pollutant is 

added onto the land surface during dry weather periods which will become available 

for washoff during a runoff event. Total buildup within a subcatchment is expressed 

as either mass per unit of area (e.g., lb/acre) or as mass per unit of curb length (e.g., 

lb/mile). Separate buildup rates can be defined for each pollutant and land use. Three 

options are provided in SWMM to simulate buildup: the power function, the 

87 
exponential function and the saturation function. The mathematical representation of 

each function is described in the SWMM 5 Users Manual (Rossman, 2008). These 

formulations can be adapted, by using the proper parameters, to achieve various kinds 

of buildup behavior, such as a linear rate buildup or a declining rate buildup. 

Defining an initial pollutant loading over the subcatchment is an alternative to using a 

buildup function for single event simulations. Initial loading is the amount of a 

pollutant over the subcatchment, in units of mass per unit area, at the beginning of a 

simulation. This alternative is more easily adapted to single-event simulations and 

overrides any initial buildup computed during the antecedent dry days. 

•	 Washoff 

Washoff is the process of erosion, mobilization, and/or dissolution of pollutants from 

a subcatchment surface during wet-weather events. Three choices are available in 

SWMM to represent the washoff process for each pollutant and land use: event mean 

concentrations (EMCs), rating curves and exponential functions (see the SWMM 5 

Users Manual for mathematical representations). The main differences between these 

three functions are summarized below. 

•	 EMC assumes each pollutant has a constant runoff concentration throughout 

the simulation. 

•	 Rating curves produce washoff loads that are functions of the runoff rate only, 

which means that they simulate the same washoff under the same discharge, 

regardless of the time in the storm that the discharge occurs. 

•	 Exponential curves differ from rating curves in that the washoff load is a 

function not only of the runoff rate but also the amount of pollutant remaining 

on the watershed. 

•	 Buildup functions are not required when EMCs or rating curves are used to 

represent the pollutant concentrations. If buildup functions are used, 

regardless of washoff function, buildup is continuously depleted as washoff 

proceeds, and washoff ceases when there is no more buildup remaining. 

•	 Because rating curves do not use the amount of buildup remaining as a 

limiting factor, they tend to produce higher pollutant loads at the end of a 

storm event than do exponential curves which do take into account the 

amount of buildup remaining on the surface. This difference can be 

particularly important for large storm events where much of the buildup may 

be washed off in early stages. 

After pollutants are washed off the subcatchment surface, they enter the conveyance 

system and are transported through the conduits as determined by the flow routing 

results. Here they may experience first-order decay or be subjected to reduction at 

specific nodes where treatment functions have been defined. 

•	 Pollutant Reduction from Land Surfaces 

Two procedures for reducing surface pollutant loads within subcatchments are 

available in SWMM. They are: 

88 
•	 BMP Treatment: This mechanism assumes that some type of BMP has been 

utilized in the subcatchment that reduces its normal washoff load by a 

constant removal fraction. BMP treatment will not be used in this example but 

will instead be illustrated in Example 6. 

•	 Street sweeping: Street sweeping can be defined for each land use and is 

simulated in parallel with buildup prior to the beginning of the first storm 

event and in-between the next events. Street sweeping is defined by four 

parameters used to compute the pollutant load remaining on the surface at the 

start of a storm: (1) days between street sweeping, (2) fraction of the buildup 

that is available for removal by sweeping, (3) number of days since last 

sweeping at the start of the simulation and (4) street sweeping removal 

efficiency (in percent). These parameters are defined for each land use while 

the fourth one is defined for each pollutant as well. 

5.3 Model Setup 

Total Suspended Solids (TSS) will be the lone water quality constituent 

considered in this example. TSS is one of the most common pollutants in urban 

stormwater and its concentration is typically high. The U.S. EPA (1983) reported TSS 

EMCs in the range of 180 - 548 mg/L while the UDFCD (2001) reports values between 

225 mg/L and 400 mg/L depending on the land use. Some of the receiving water impacts 

associated with this pollutant are habitat change, stream turbidity, and loss of recreation 

and aesthetics. The solids associated with TSS can also contain toxic compounds, such as 

heavy metals and adsorbed organics. The following paragraphs discuss how to modify 

the model built in Example 2 (file Example2-Post.inp) to consider the buildup, washoff, 

and transport of TSS within the post-development site. 

Define the Pollutant 

The first step is to define TSS as a new pollutant under the Quality category in 

SWMM’s Data Browser. Its concentration units will be mg/L, and a small amount (10 

mg/L) is assumed to be present in rainwater. Concentrations in groundwater as well as a 

first order decay are not considered in this example, nor will any co-pollutant be defined 

for TSS. 

Define Land Uses 

Three different land uses will be considered in this example: Residential_1, 

Residential_2 and Commercial. The Residential_1 land use will be used in residential 

areas with low and medium densities (lot types “L”, “M” and “M2”) while the 

Residential_2 land use will be used with high density apartments and duplexes (lot types 

“DL” and “S”). The Commercial land use will be used with lot types “T” and “RT”. 

89 
Land uses are defined in SWMM under the Quality category in the Data Browser. 

Street sweeping is not considered in this example so sweeping parameters are not 

defined. A mixture of land uses will be assigned to each subcatchment area. This is done 

by opening the Property Editor for a given subcatchment, selecting the Land Use 

property and clicking the ellipsis button. A Land Use Assignment dialog will appear 

where one enters the percentage of surface area that is assigned to each land use. 

Percentages are estimated visually from the study area map. Table 5-4, shown later in this 

example, summarizes the assignment of land uses in each of the subcatchments. 

Defining Pollutants and Land Uses 

Pollutants: Pollutants are defined in the Pollutant Editor 

of SWMM under the Quality category of the Data 

Browser. The minimum amount of data needed to define 

a new pollutant is a name and concentration units. Other 

characteristics include the pollutant’s concentration in 

various external (non-buildup) sources (rainwater, 

groundwater, and RDII), its first-order decay coefficient 

(day-1) and name of a co-pollutant that its buildup is 

dependant upon. 

Land Uses: Different land uses will generate pollutants at different rates. Land uses 

are defined in SWMM under the Quality category of the Data Browser. Their 

properties are edited using the Land Use Editor which is divided into three 

categories: General, Buildup and Washoff. The General tab contains the land use 

name and details on street sweeping for that particular land use. The Buildup tab is 

used to select a buildup function, and its parameters, for each pollutant generated by 

the land use. The choice of normalizer variable (total curb length or area) is also 

defined here. Finally, the Washoff tab is used to define the washoff function and its 

parameters, for each pollutant generated by the land use, as well as removal 

efficiencies for street cleaning and BMPs. 

90 
 

Table 5-2. Typical dust and dirt buildup rates after Manning et al. (1977) 

Land Use Mean (lb/curb-mi/day) Range (lb/curb-mi/day) 

Commercial 116 3 – 365 

Multiple family residential 113 8 – 770 

Single family residential 62 3 – 950 

Specify a Buildup Function 

One of SWMM’s buildup equations will be selected to characterize the 

accumulation of TSS during dry weather periods. Unfortunately, the choice of the best 

functional form is never obvious, even if data are available. Even though most buildup 

data in the literature imply a linear buildup with time, it has been observed that this linear 

assumption is not always true (Sartor and Boyd, 1972), and that the buildup rate tends to 

decrease with time. Thus, this example will use an exponential curve with parameters C1 

(maximum buildup possible) and C2 (buildup rate constant) to represent the buildup rate 

B as a function of time t: 

−C t 2 B = C1 (1− e ) (5-1) 

Buildup data for TSS reveal that commercial and residential areas tend to generate 

similar amounts of the dust and dirt that comprise the TSS (again, there is a large 

variation for different cases). Similarly, high-density residential areas tend to produce 

more of this pollutant than low-density residential areas. Typical values of dust-and-dirt 

buildup rates based on a nationwide study by Manning et al. (1977) are shown in Table 5­

2. 

Table 5-3 shows the parameters C1 and C2 used in equation 5-1 for each land use 

defined earlier. A graphical representation of the exponential buildup model with these 

parameters is shown in Figure 5-2. In SWMM the buildup function and its parameters are 

defined for each land use on the “Buildup” page of the Land Use Editor. The Buildup 

Function used here is Exp, the constant C1 is entered in the field Max. Buildup and 

constant C2 is entered in the field Rate Constant. The field Power/Sat. Constant is not 

defined when the Exponential model is used. 

The values of the parameters used in this TSS buildup function were obtained 

from the literature. No other justification supports their use and it is strongly 

recommended that modelers define them based on site data specific to their project. 

Buildup in all the subcatchments will be normalized in this example by the curb 

length (typically there is more literature data per unit length of street/gutter than per unit 

area). This choice is specified for each land use in the Land Use Editor. Curb lengths can 

be estimated by using SWMM’s Ruler tool to trace over the streets within the study area 

map (see the sidebar “Measuring Tools Available in SWMM” in Example 1). They should 

be similar to those listed in Table 5-4. These values are assigned to each subcatchment by 

using the Property Editor. The curb length units (e.g. feet or meters) must be consistent 

with those used for the buildup rate (e.g. lbs/curb-ft or kg/curb-m) in the Land Use 

Editor; do not mix units between the two systems. 

91 
Table 5-4. Curb length and land uses for each subcatchment 

Subcatchment Curb Length (ft) Residential_1 (%) Residential_2 (%) Commercial (%) 

1 1680 100 0 0 

2 1680 27 73 0 

3 930 27 32 0 

4 2250 9 30 26 

5 2480 0 0 98 

6 1100 0 0 100 

7 565 0 0 0 

Table 5-3. Parameters for TSS buildup 

Land Use C1 (lb/curb-ft) C2 (1/day) 

Residential_1 0.11 0.5 

Residential_2 0.13 0.5 

Commercial 0.15 0.2 

Figure 5-2. TSS buildup curve 

Finally, in order to start the simulation with some initial buildup already present, 

it is assumed that there were 5 days of dry antecedent conditions before the start of the 

simulation. The program will apply this time interval to the TSS buildup functions to 

compute an initial loading of TSS over each subcatchment. The Antecedent Dry Days 

parameter is specified on the General page of the Simulation Options dialog in SWMM. 

Specify a Washoff Function 

Two methods are used in this example to simulate washoff: EMCs and an 

exponential washoff equation. The following sections explain how these are added to the 

model. 

92 
 

EMCs 

An estimation of the EMCs can be obtained from the Nationwide Urban Runoff 

Program (NURP) conducted by EPA (U.S. EPA, 1983). According to this study, the 

median TSS EMC observed in urban sites is 100 mg/L. Based on the general observation 

that residential and commercial areas produce similar pollutant loads, and taking into 

account the differences among land uses, this example uses the EMCs shown in Table 5­

5 at the end of this section. These EMCs are entered into the model using the Land Use 

Editor’s Washoff page for each defined land use. The entry for the Function field is 

EMC, the concentration from Table 5-5 is entered in the Coefficient field and the 

remaining fields can be set to 0. The resulting SWMM input file is saved as Example5-

EMC.inp. 

Exponential Washoff 

The exponential washoff function used in SWMM is: 

W 2 = C1 ⋅ q

C ⋅ B (5-2) 

where: 

W = rate of pollutant load washed off at time t in lbs/hr 

C1 = washoff coefficient in units of (in/hr)-C

2(hr)-1 

C2 = washoff exponent 

q = runoff rate per unit area at time t, in/hr 

B = pollutant buildup remaining on the surface at time t, lbs. 

According to sediment transport theory, values of the exponent C2 should range 

between 1.1 and 2.6, with most values near 2 (Vanoni, 1975). One can assume that 

commercial and high-density residential areas (land uses Commercial and Residential_2), 

because of their higher imperviousness, tend to release pollutants faster than areas with 

individual lots (Residential_1). Thus a value of 2.2 is used for C2 in the Residential_2 and 

Commercial land uses and 1.8 is used for the Residential_1 land use. 

Values of the washoff coefficient (C1) are much more difficult to infer because 

they can vary in nature by 3 or 4 orders of magnitude. This variation may be less extreme 

in urban areas, but is still significant. Monitoring data should be used to help estimate a 

value for this constant. The current example assumes a C1 equal to 40 for Residential_2 

and Commercial and a C1 equal to 20 for the land use Residential_1. 

Table 5-5 summarizes the C1 and C2 coefficients used for each land use under 

exponential washoff. These are entered into the model using the Land Use Editor 

Washoff page for each defined land use. The entry for the Function field is EXP, the C1 

value from Table 5.5 is entered in the Coefficient field, and the C2 value from the table is 

entered into the Exponent field. The remaining fields can be set to 0. The resulting 

SWMM input file is saved as Example5-EXP.inp. 

93 
Table 5-5. Washoff characteristics for each land use 

Land Use EMC (mg/L) C1 [(in/hr)-C2 -1 sec ] C2 

Residential_1 160 20 1.8 

Residential_2 200 40 2.2 

Commercial 180 40 2.2 

5.4 Model Results 

Both the EMC washoff model (Example5-EMC.inp) and the exponential 

washoff model (Example5-EXP.inp) were run for the 0.1 in., 0.23 in. and 2-yr rainfall 

events under the following set of analysis options: 

Simulation Period: 12 hours 

Antecedent Dry Days: 5 

Routing Method: Dynamic Wave 

Routing Time Step: 15 seconds 

Wet-weather Time Step: 1 minute 

Dry-weather Time Step: 1 hour 

Reporting Time Step: 1 minute 

A discussion of the results obtained from each model is next presented. 

EMC Washoff Results 

Figures 5-3 and 5-4 show the runoff concentrations simulated at different 

subcatchments both for the 0.1 in. (Figure 5-3) and the 0.23 in. (Figure 5-4) storms. The 

concentrations are constant and correspond to the summation of the constant 

concentration in the rain (10 mg/L) and the EMCs assigned to the land uses within each 

subcatchment. Once the surface runoff ceases, the TSS concentration goes to zero. That is 

why no concentration is displayed for subcatchment S7, since it generates no runoff (all 

rainfall is infiltrated). Note that with EMC washoff, the size of the storm has no effect on 

a subcatchment’s runoff concentration. 

Figure 5-5 shows the TSS concentration over time (pollutograph) simulated at the 

study area outlet for each of the three storm events (0.1, 0.23, and 1.0 in.). The outlet 

concentration reflects the combined effect of the TSS washoff produced from each 

subcatchment and routing through the conveyance network. The peak-concentrations and 

shapes for the pollutographs are very similar. Compared with the washoff concentrations 

generated by the individual subcatchments (Figures 5-3 and 5-4), the outlet 

concentrations are not constant but attenuate over time. This attenuation is caused 

primarily by the longer time it takes runoff from the lower EMC subcatchments (such as 

S3 and S4) to reach the outlet. Some of it is also a result of the numerical dispersion in the 

model resulting from the assumption of complete mixing within each conveyance conduit 

during the pollutant routing process. 

94 
 

A 

B 

C 

D 

 How to Read the SWMM Status Report in Terms of Water Quality 

The simulation of water quality generates added information in SWMM’s Status 

Report. This information can be broken into four general sections (A, B, C and D). These 

additions to the status report are discussed below using Example5-EMC.inp with the 0.1 

inch precipitation event as an example. 

Part A shows the runoff-quality 

continuity balance over the entire study
 

area. The “input” loads include (a) Initial 

Buildup before the start of the simulation, 

(b) Surface Buildup during all dry 

weather periods, and (c) Wet Deposition
 

(from pollutant in the rainfall). The 

“output” loads include (1) Sweeping
 

Removal (not simulated), (2) Infiltration
 

Loss for any direct rainfall or runon from 

other subcatchments (simulated 

automatically), (3) removal associated 

with BMP Removal (not simulated in this 

example), and (4) pollutant load in the 

Surface Runoff (which includes the 

portion of buildup that is washed off as
 

well as any loads produced by direct 

deposition and runon). Finally, the 

continuity report indicates the Remaining 

Buildup. 

Part B shows the quality-routing
 

continuity balance. In this example, only
 

runoff loads are routed through the 

conveyance system. No dry weather, 

groundwater, RDII, or user-supplied 

external inflows, nor is any treatment or generate the lowest loads of TSS. S7 does not

generate any load because it does not produce 

any runoff while S3 produces a smaller load 

due to a large amount of pervious surface in the 

subcatchment. 

decay considered. Therefore, the only

three variables represented in this

summary are the Wet Weather Inflow, the

External Outflow and the Final Stored

Mass. Note that the Wet Weather Inflow

in Part B is equal to the Surface Runoff in Part D shows the total loads leaving the 

Part A. system through its outfalls. 

Part C provides a summary of the load of 

pollutant washed off from each 

subcatchment. Subcatchments S7 and S3 

95
240
 

Mg/L 

210 

180 

150 

120 

90 S1 S2 

S3 S4 

60 S7

30 

0 

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 

time (hr:min) 

240
 

210
 

180
 

150
 

Mg/L 120 

90 S1 S2 

S3 S4 

60 S7

30 

0 

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 

time (hr:min) 

Figure 5-3. TSS concentrations for the 0.1 in. storm with EMC washoff 

Figure 5-4. TSS concentrations for the 0.23 in. storm with EMC washoff 

96
0 

20 

40 

60 

80 

100 

120 

140 

160 

180 

200 

220 

mg/L 

0.1 in. storm 

0.23 in. storm 

2-yr storm 

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 

time (hr:min) 

Figure 5-5. TSS concentration at site outlet with EMC washoff 

Figure 5-5 also shows that TSS concentrations continue to appear at the outlet for 

an extended period of time after the end of the storm event. This is an artifact of the flow 

routing procedure wherein the conduits continue carry a very small volume of water 

whose concentration still reflects the high EMC levels. Thus although the concentrations 

appear high, the mass loads carried by these small discharges are negligible. This is 

evident when the outlet hydrograph is plotted alongside the outlet loadograph for a given 

storm. A loadograph is a plot of concentration times flow rate versus time. An example 

for the 0.1 in. event is shown in Figure 5-6. This plot was generated by exporting the time 

series table for Total Inflow and TSS concentration at the outfall node O1 into a 

spreadsheet, using the spreadsheet to multiply flow and concentration together (and 

converting the result to lbs/hr), and then plotting both flow and load versus time. Note 

how the TSS load discharged from the catchment declines in the same manner as does the 

total runoff discharge. 

97 
 

0 

5 

10 

15 

20 

25 

30 

35 

40 

lb/hr 

0 

0.1 

0.2 

0.3 

0.4 

0.5 

0.6 

0.7 

0.8 

cfs 

mass rate 

discharge 

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 

time (hr:min) 

Figure 5-6. Runoff flow and TSS load at site outlet for the 0.1 in. storm with EMC washoff 

Exponential Washoff Results 

Figure 5-7 shows the simulated TSS concentration in the runoff from different 

subcatchments using the 0.1 in. storm and the Exponential washoff equation. Unlike the 

EMC results, these concentrations vary throughout the runoff event and depend on both 

the runoff rate and the pollutant mass remaining on the subcatchment surface. Figure 5-8 

shows the same plots but for the 0.23 in storm. Note two significant differences with 

respect to the results obtained for the 0.1 in storm. The maximum TSS concentrations are 

much larger (around 10 times) and the generation of TSS is much faster, as seen by the 

sharper-peaked pollutographs in Figure 5-8. Finally, Figure 5-9 shows the same graphs 

for the larger 1-in., 2-yr storm. The TSS concentrations are slightly larger than those for 

the 0.23 in. storm but the difference is much smaller than the difference between the 0.1 

in and 0.23 in storms. Similar results hold for the pollutographs generated for the 

watershed’s outlet as seen in Figure 5-10. 

98 
Mg/L

300 

250 

200 

150 

S1 S2 

100 S3 S4 

S7

50 

0 

0:00 1:00 2:00 3:00 4:00 

time (hr:min) 

1800
 

1600
 

1400
 

1200
 

Mg/L 1000 

400 

600 

800 

S1 

S3 

S7

S2 

S4 

200 

0 

0:00 1:00 2:00 

time (hr:min) 

3:00 4:00 

Figure 5-7. TSS concentrations for the 0.1 in. storm with Exponential washoff 

Figure 5-8. TSS concentrations for the 0.23 storm with Exponential washoff 

99
0 

200 

400 

600 

800 

1000 

1200 

1400 

1600 

1800 

2000 

0:00 1:00 2:00 3:00 4:00 

time (hr:min) 

Mg/L

S1 S2 

S3 S4 

S7 

Figure 5-9. TSS concentrations for the 2-yr (1 in.) storm with Exponential washoff 

2200
 

2000
 

1800
 

1600
 

1400
 

mg/L 

0.1 in. storm 

0.23 in. storm 

2-yr storm 

1200 

1000 

800 

600 

400 

200 

0 

0:00	 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 

time (hr:min) 

Figure 5-10. TSS concentration at the site outlet for Exponential washoff 

100 
Even though the EMC and Exponential washoff models utilize different 

coefficients that are not directly comparable, it is interesting to compute what the average 

event concentration in the runoff from each subcatchment was under the two models. The 

resulting averages are shown in Table 5-6 for the case of the 0.23 in. storm. The point 

being made here is that even though the pollutographs produced by the two models can 

look very different, with the proper choice of coefficients it is possible to get event 

average concentrations that look similar. Although the results of the Exponential model 

are more pleasing to one’s sense of how pollutants are washed off the watershed, in the 

absence of field measurements one cannot claim that they are necessarily more accurate. 

Most SWMM modelers tend to use the EMC method unless data are available to estimate 

and calibrate the coefficients required of a more sophisticated buildup and washoff 

model. 

Table 5-6. Average TSS concentration for the 0.23 in. event 

Subcatchment EMC Model 

(mg/L) 

Exponential Model 

(mg/L) 

S1 170 180.4 

S2 199.2 163.6 

S3 117.2 67.7 

S4 131.2 91.4 

S7 0 0 

5.5 Summary 

This example illustrated how SWMM is used to model the quality of stormwater 

runoff within an urban catchment without any source or regional BMP controls. One 

pollutant, TSS, was simulated with one buildup method (exponential) and two different 

washoff methods (EMC and exponential). The key points illustrated in this example 

were: 

1.	 SWMM models runoff water quality through the definition of pollutants, land uses, 

pollutant buildup, and pollutant washoff. Any number of user-defined pollutants and 

land uses can be modeled. Pollutant buildup and washoff parameters are defined for 

each land use and more than one land use can be assigned to each subcatchment. 

2.	 There are several options available to simulate both pollutant buildup and washoff. 

Buildup expressions are defined by a buildup rate and a maximum buildup possible 

per unit of area or curb length. Pollutant washoff can be defined through an event 

mean concentration (EMC), a rating curve, or an exponential function. The 

exponential method is the only one that directly depends on the amount of buildup 

remaining on the surface. Rating-curve calculations are dependant only on the runoff 

across the subcatchment, while EMCs have constant concentrations throughout the 

simulation. 

101 
3.	 Exponential washoff produces a runoff pollutograph with rising and falling limbs, 

similar to that of a runoff hydrograph. The EMC pollutograph is flat throughout the 

duration of the event. 

4.	 Small storms can have a high impact on receiving waters because they are more 

frequent and can still generate significant washoff concentrations. 

There are many uncertainties associated with both the process representation and 

the data required to properly estimate, calibrate and validate a runoff water quality model. 

It is strongly recommended that modelers use site specific data whenever possible when 

building a runoff water quality model with SWMM. 

102 
Example 6. Runoff Treatment 

This example illustrates how to model water quality treatment in the BMPs that 

were used in two earlier examples to control runoff from a new residential development 

on a 29 acre site. Treatment of total suspended solids (TSS) is applied at both the 

detention pond introduced in Example 3 and the filter strips and infiltration trenches 

added in Example 4. The pond from Example 3 is re-designed to a smaller volume for 

this example to account for the runoff reduction associated with the upstream infiltration 

trenches. TSS removal in the detention pond is modeled as an exponential function of 

time and water depth. TSS removal in the filter strips and infiltration trenches is a fixed 

percent reduction in loading. 

6.1 Problem Statement 

In Example 3 a regional detention pond was designed for a 29 acre residential site 

to detain a water quality capture volume (WQCV) for a specific period of time and to 

reduce peak runoff flows to their pre-development levels. Example 4 added two different 

types of distributed Low Impact Development (LID) source controls throughout the site 

to help reduce the volume of runoff generated. Example 5 illustrated how to model total 

suspended solids buildup and washoff within the site without considering any TSS 

removal that might occur within the LIDs or the pond. These previous models will be 

extended to explicitly account for the removal of TSS that occurs in both the LIDs and 

the pond. A comparison will be made of the TSS concentrations and loads in the runoff 

produced by the site both with and without considering treatment. 

Figure 6-1 shows the example study area with the LIDs and detention pond 

included. The SWMM storage unit that represents the detention pond as designed in 

Example 3 was renamed to SU2 and resized for this example to incorporate a smaller 

Water Quality Capture Volume (WQCV) due to the runoff reduction produced by the 

LIDs. It was concluded from Example 4 that of the two types of LIDs modeled, 

infiltration trenches have the greatest impact on reducing the volume of water that needs 

to be treated in the pond’s WQCV. The total volume of water that can be captured by the 

infiltration trenches was determined to be 6,638 ft3. Because the WQCV is a requirement 

for the watershed as a whole, the volume captured in the infiltration trenches can be 

subtracted from the volume required in the regional pond, reducing it from the 24,162 ft3 

required in Example 3 to 17,524 ft3

 (24,162 - 6,638). 

103 
 

Table 6-1. Storage curve for the re-designed pond 

This Example 

Depth (ft) 0 2.2 2.3 6 

Area (ft2

) 10368 14512 32000 50000 

Example 3 

Depth (ft) 0 2.22 2.3 6 

Area (ft2

) 14706 19659 39317 52644 

Figure 6-1. Developed site with LIDs and detention pond 

The storage unit’s shape and outlet structures were redesigned to control this new 

WQCV and meet the general design criteria introduced in Example 3 (e.g. 40 hr 

drawdown time for the WQCV and peak shaving of the 2-, 10- and 100-yr storms). Table 

6-1 compares the storage curve of the pond designed in Example 3 without LIDs and the 

pond designed for this example with LIDs. Table 6-2 does the same for the dimensions 

and inverts of the orifices and weirs that comprise the pond’s outlet structure. Figure 6-2 

shows the general placement of the various outlets. 

104 
Table 6-2. Properties of the pond’s re-designed outlet structure 

ID Type of 

Element 

Event 

Controlled Shape Height h (ft) 

Width, 

b (ft) 

Invert 

Offset z (ft) 

Discharge 

Coefficient 

Orifice or Weir 

Area (ft2) 

Example 3 

Or1 

Or2 

Or3 

Orifice 

Orifice 

Orifice 

WQCV 

2-yr 

10-yr 

Side 

Rectangular 

Side 

Rectangular 

Side 

Rectangular 

0.3 

0.5 

0.25 

0.25 

2 

0.35 

0 

1.5 

2.22 

0.65 

0.65 

0.65 

0.08 

1 

0.09 

W1 Weir 100-yr Rectangular 2.83 1.75 3.17 3.3 4.95 

This Example 

Or1 Orifice WQCV Side 

Rectangular 0.16 0.25 0 0.65 0.04 

Or2 Orifice 2- and 10­

yr 

Side 

Rectangular 0.5 2.25 1.5 0.65 1.13 

W1 Weir 100-yr Rectangular 2.72 1.6 3.28 3.3 4.35 

h3 

h2 

h1 

Z3 

b3 

b2 

b1 

Z2 

6 ft 

Or 1 

Or 2 

W1 

Figure 6-2. Schematic of the re-designed pond outlet structure 

6.2 System Representation 

Water Quality Treatment in LIDs 

As defined in Example 4, the filter strip and infiltration trench LIDs are modeled 

as subcatchments in order to represent the combined effects of infiltration and storage on 

storm runoff. This example will also consider their ability to reduce pollutant loads in the 

surface runoff they handle. There are no widely accepted mechanistic models of pollutant 

removal through these types of LIDs. The best one can do is to apply average removal 

efficiencies for specific contaminants based on field observations reported in the 

literature. 

105 
 

 

 

SWMM can apply a constant BMP Removal Efficiency for any pollutant in the 

washoff generated from a particular land use. At each time step the pollutant load 

generated by a given land use is reduced by this user-supplied value. This reduction also 

applies to any upstream runoff that runs onto the subcatchment. The LIDs added in 

Example 4 receive runoff from upstream subcatchments and do not generate any 

pollutant load themselves. Thus it will be convenient to define a new land use, named 

“LID”, that is used exclusively for the LID subcatchments and has a specific BMP 

Removal Efficiency for TSS associated with it. 

Water Quality Treatment in Detention Ponds 

Detention ponds are modeled as storage unit nodes within SWMM. By adding 

Treatment Functions to the storage node’s properties, SWMM can reduce the pollutant 

concentrations in the pond’s outflow. This example uses an empirical exponential decay 

function to model solids removal through gravity settling within a pond. For controlling 

the WQCV event, the pond fills relatively quickly over a period of 2 hours and then 

drains slowly over an extended period of 40 hours during which solids removal occurs. 

At some interval Δt during this drain time, and assuming homogenous concentration, the 

fraction of particles with a settling velocity ui that are removed would be uiΔt/d where d 

is the water depth. Summing over all particle settling velocities leads to the following 

expression for the change in TSS concentration ΔC during a time step Δt: 

ΔC = Ct ×∑ fi

ui × (Δt / d) (6-1) 

i 

where Ct is the total concentration of TSS particles at time t and fi is the fraction of 

particles with settling velocity ui. Because ∑ fi

ui is generally not known, it can be 

replaced with a fitting parameter k and in the limit Equation (6-1) becomes: 

∂Ct k = − Ct (6-2) ∂t d 

Note that k has units of velocity (length/time) and can be thought of as a representative 

settling velocity for the particles that make up the total suspended solids in solution. 

Integrating Equation (6-2) between times t and t+Δt, and assuming there is some 

residual amount of suspended solids C* that is non-settleable leads to the following 

treatment function for TSS in the pond: 

−(k / d )Δt C = C * +(C − C*)e (6-3) t+Δt t 

Equation (6-3) is applied at each time step of the simulation to update the pond’s TSS 

concentration based on the current concentration and water depth. 

106 
 

 

Simulating Treatment within a Conveyance Network 

SWMM can apply water quality treatment at any node of a drainage 

system’s conveyance network. Treatment for a node is defined by opening its 

Property Editor and clicking the ellipsis button next to the Treatment property. This 

brings up a Treatment Expression dialog box in which the user can define a 

treatment function for each pollutant that passes through the node. 

The treatment function for a given pollutant can have one of the following forms: 

R = f (P, R _ P,V ) 

C = f (P, R _ P,V ) 

where R is the fractional removal, C is the outlet concentration, P is one or more 

concentrations given by the pollutant names (e.g., TSS), R_P is one or more 

pollutant removals (e.g., R_TSS), and V is one or more of the following process 

variables: FLOW (flow rate into the node), DEPTH (water depth above node invert), 

HRT (hydraulic residence time), DT (routing time step) and AREA (node surface 

area). Some examples of treatment expressions are: 

C = BOD * exp(-0.05*HRT) 

R = 1 – (1 + (0.001/(2*FLOW/AREA))^(-2) 

With a fractional removal expression, the new concentration at the node, C, 

is defined as Cin(1-R) where Cin is the inflow concentration to the node. Also, when 

a concentration P appears in an expression applied to a non-storage node, it is the 

same as Cin for the node whereas for a storage node it is the current concentration C 

in the storage unit. 

107 
Table 6-3. Curb lengths and land uses for LID subcatchments 

Subcatchment Area (ac) Curb Length (ft) Reside ntial_1 (%) Residential_2 (%) Commercial (%) 

S1.1 1.21 450 100 0 0 

S1.2 1.46 600 100 0 0 

S1.3 1.88 630 100 0 0 

S2.1 1.3 450 100 0 0 

S2.2 1.5 600 0 100 0 

S2.3 1.88 630 0 100 0 

S3.1 1.29 0 0 0 0 

S3.2 1.02 430 100 0 0 

S3.3 1.38 500 0 85 0 

S4.1 1.65 0 0 0 0 

S4.2 0.79 400 0 100 0 

S4.3 1.91 1150 36 64 0 

S4.4 2.4 700 0 0 71 

S5 4.79 2480 0 0 98 

S6 1.98 1100 0 0 100 

S7 2.33 565 0 0 0 

6.3 Model Setup 

The starting point for adding treatment to the runoff controls placed on the study 

site is the file Example6-Initial.inp. This input file already contains the local LIDs 

defined in Example 4 and the redesigned storage unit and outlet structures described in 

section 6.1. The land uses in this file were re-calculated and re-assigned to each 

subcatchment based on the discretization employed in Example 4. The washoff function 

for TSS is the EMC washoff function used in Example 5. The curb lengths and land uses 

assigned to each subcatchment are listed in Table 6-3. The subcatchments treated by 

infiltration trenches or filter strips are marked in grey in this table. 

LID Treatment 

It is assumed that each filter strip and infiltration trench can provide 70% TSS 

removal for the runoff that passes over it. This is a typical removal observed for 

infiltration-based LIDs (Sansalone and Hird, 2003). A new land use, named “LID” is 

created with no TSS buildup function, an EMC TSS washoff function with 0 mg/L of 

TSS, and a TSS “BMP efficiency” of 70%. The land use assignment for each of the LID 

subcatchments (S_FS_1 through S_FS_4 and S_IT_1 through S_IT_4) is set to 100% LID. 

As a result, all of the runoff generated from upstream subcatchments that flow over these 

LID subcatchments will receive 70% TSS removal. 

108 
 

Detention Pond Treatment 

The removal of TSS in the detention pond is simulated using the exponential 

model given by Equation 6-3. One can roughly estimate what the removal constant k in 

this expression must be so that a targeted level of pollutant removal is achieved within a 

40 hour detention time for the 0.23 in. WQCV design storm. If Equation 6-3 were applied 

over a 40 hour period to achieve a target TSS reduction of 95%, then an estimate of k 

would be: 

k = −d ×ln(0.05 ) / 40 (6-4) 

where d is some representative value of the pond depth during the 40 hour release period. 

As can be verified later on, the average depth in the pond for the 0.23 in design storm 

over a 40 hour duration is 0.15 ft. Using this value in the expression for k yields an 

estimate of 0.01 ft/hr. This value is of the same order as the 0.03 ft/hr figure quoted in US 

EPA (1986) that represents the 20-th percentile of settling velocity distributions measured 

from 50 different runoff samples from seven urban sites in EPA’s Nationwide Urban 

Runoff Program (NURP). 

With this value of k and assuming a minimum residual TSS concentration C* of 

20 mg/L, the following expression is entered into SWMM’s Treatment Editor for the 

storage unit SU2: C = 20 + (TSS – 20) * EXP(-0.01 / 3600 / DEPTH * DT) 

Note the meaning of the individual terms in this expression with respect to those 

in Equation (6-3): 20 is the value assumed for C*, TSS is the identifier given to the TSS 

concentration C for this model, 0.01/3600 is the value of k expressed in units of ft/s, 

DEPTH is the reserved word that SWMM uses for the water depth d in feet, and DT is 

the reserved word that SWMM uses for the routing time step Δt in seconds. When 

SWMM sees reserved words like DEPTH and DT within a treatment expression it knows 

to automatically insert their current values into the expression at each time step. 

The following analysis options should be used for all of the simulations made 

with this treatment-augmented input file: 

Flow Routing Method: Dynamic Wave 

Wet Weather Time Step: 1 minute 

Flow Routing Time Step: 15 sec 

Reporting Time Step: 1 minute 

Total Duration: 2 days (48 hr) 

The 48 hour duration was chosen so that the full effect of the drawdown of the 

WQCV in the detention pond could be observed. Finally, it is suggested to increase the 

number of significant figures (from 2, the default value, to 4) for the subcatchment 

parameter “Runoff” and the node parameters “Quality” and “Total Inflow” by selecting 

Tools | Program Preferences | Number Formats from SWMM’s main menu bar. This 

will help when tabulated results are copied from SWMM to a spreadsheet program to 

compare results between different runs in cases where variations are small and would not 

be visible if only two significant figures were used. The resulting input file is named 

Example6-Final.inp. 

109 
6.4 Model Results 

Results for several sets of comparison runs will be discussed. First, the effect of 

TSS treatment at the LIDs is considered. Figure 6-3 compares the TSS concentration in 

the treated runoff from filter strip S_FS_1 to that of the upstream runoff from 

subcatchment S3.2 for the 0.1 in. storm. Also shown for reference are the runoff flows 

from each area. The reduction from 170 mg/L to 51 mg/L through the filter strip matches 

the 70 % TSS removal efficiency specified for the LID. Similar results are obtained for 

the remaining filter strips under all design storms. 

0 

20 

40 

60 

80 

100 

120 

140 

160 

180 

200 

TSS (mg/L) 

0 

0.02 

0.04 

0.06 

0.08 

0.1 

Runoff (cfs) 

Upstream TSS 

FilterStrip TSS 

Upstream Runoff 

Filter Strip Runoff 

0:00 1:00 2:00 3:00 4:00 5:00 6:00 

Time (hr:min) 

Figure 6-3. TSS and runoff reduction through filter strip S_FS_1 for the 0.1 in. storm 

Figure 6-4 presents a similar comparison for the infiltration trench S_IT_4 that 

treats runoff from subcatchment S2.3. These results are for the 2-yr (1 in.) event since for 

the smaller storms all rainfall infiltrates through the trenches. Once again note how the 

70% removal causes a drop in TSS concentration from 210 mg/L down to 63 mg/L. As 

was the case with the filter strips, the remaining infiltration trenches show a similar 

behavior to that of S_IT_4. 

110 
 

0 

20 

40 

60 

80 

100 

120 

140 

160 

180 

200 

220 

240 

TSS (mg/L) 

0 

1 

2 

3 

4 

Runoff (cfs) 

Upstream TSS 

Trench TSS 

Upstream Runoff 

Trench Runoff 

0:00 1:00 2:00 3:00 4:00 5:00 6:00 

Time (hr:min) 

Figure 6-4. TSS and runoff reduction through infiltration trench S_IT_4 for the 2-yr storm 

The next comparison is between the levels of treatment provided by the detention 

pond for the various design storms. Comparing the time series of pond influent TSS 

concentrations with the treated effluent concentrations is not particularly useful since the 

flow rates of these two streams are so different. Instead the pond effluent concentration, 

both with and without treatment will be compared for each design storm. The result is 

shown in Figure 6-5. These plots were made by running the model for each design storm 

(0.1 in., 0.23 in., and 2-year) both with the treatment function for the storage unit node 

SU2 and without it. After each run a time series table of the TSS concentration at node 

SU2 was generated and exported to a spreadsheet program from which Figure 6-5 was 

generated. 

The following observations can be drawn from Figure 6-5: 

	 With the k-value of 0.01 ft/hr, the pond behaves as designed for the WQCV storm 

(0.23 in) by removing essentially all of the settleable solids over a period of 40 

hours. 

•	 The larger the 2-hour design storm, the less effective is treatment in reducing TSS 

levels over time because of the deeper water depths experienced in the pond. 

•	 For all size storms, it takes a considerable amount of time for any significant 

removal of TSS to occur; a 50% reduction in settleable TSS requires 10, 19, and 

35 hours for the 0.1 in, 0.23 in, and 2-year storms, respectively. 

111 
0 

20 

40 

60 

80 

100 

120 

140 

160 

180 

200 

TSS (mg/L)

0.1 in 

0.23 in 

2-year 

w/o Treatment 

w/ Treatment 

k = 0.01 ft/hr 

0 5 10 15 20 25 30 35 40 45 

Time (hr) 

Figure 6-5. TSS concentrations in pond SU2 with and without treatment (k = 0.01 ft/hr) 

Another way to evaluate treatment in the pond is to compare the TSS mass 

loading that it releases both with and without treatment. This is done in Figure 6-6 for the 

0.23 WQCV storm. Plots for the other design storms look similar to this one. The effect 

of treatment on reducing the mass of TSS released is not as significant as it was for 

concentration. In fact, the Status Report for the run with treatment shows that of 72.5 lbs 

of TSS washed off for this storm event, only 15.7 lbs were removed in the pond. This 

yields an overall mass removal of only 21.7 %. The percent mass removals for the other 

design storms were 44.4 % for the 0.1 in. storm and 6 % for the 2-year (1 in.) storm. 

These low to moderate mass removals are a consequence of the extended time required 

for solids to settle in the pond during which it still is releasing an outflow. 

112 

50
0 

1 

2 

3 

4 

5 

6 

Load (lb/hr) 

Untreated Effluent 

Treated Efflue nt 

k = 0.01 ft/hr 

0 4 8 12 16 20 24 28 32 36 40 44 48 

Time (hr) 

Figure 6-6. TSS mass load released by pond SU2 for the 0.23 in storm (k = 0.01 ft/hr) 

These rather modest levels of detention pond performance were computed using a 

removal constant k that represents particles with a very low settling velocity, below that 

of the lowest 20% determined from a nationwide survey. Suppose the size distribution of 

particles comprising the TSS washoff were larger, as reflected in a k-value of 0.3 ft/hr. 

This represents the 40-th percentile of the settling velocities found from the NURP study 

(US EPA, 1986). Figure 6-7 shows the resulting TSS concentrations in the pond 

discharge with this higher k-value. Figure 6-8 does the same for the TSS discharge 

loading for the 0.23 in. event. Table 6-4 summarizes the pond’s treatment performance 

for the two different k-values. These results show that uncertainty in the removal constant 

will significantly impact predictions of TSS removal within the detention pond. 

Unfortunately, as noted in US EPA (1986), there can be high variability in solids settling 

velocity distributions from site to site and from storm to storm within a given site. This 

variability makes it very difficult to make reliable estimates of detention pond treatment 

effectiveness. 

113 
6
 

Load (lb/hr) 5
 

4
 

3
 

2
 

1
 

0 

Untreated Effluent 

Treated Effluent 

k = 0.3 ft/hr 

0 4 8 12 16 20 24 28 32 36 40 44 48 
 

Time (hr)
 

0 

20 

40 

60 

80 

100 

120 

140 

160 

180 

200 

TSS (mg/L) 

0.1 in 

0.23 in 

2-year 

w/o Treatment 

w/ Treatment 

k = 0.3 ft/hr 

0 5 10 15 20 25
 

Time (hr)
 

Figure 6-7. TSS concentrations in pond SU2 with and without treatment (k = 0.3 ft/hr)
 

Figure 6-8. TSS mass load released by pond SU2 for the 0.23 in. storm (k = 0.3 ft/hr) 

114
 
Table 6-4. Detention pond TSS treatment performance summary 

0.1 in. Storm 0.23 in. Storm 1.0 in. Storm 

k = 0.01 k = 0.3 k = 0.01 k = 0.3 k = 0.01 k = 0.3 

Time to achieve 50% reduction, hr 10 1 19 3 35 6 

Time to achieve full reduction, hr 30 7 40 10 > 48 20 

Overall mass removal, % 44.4 81.8 21.7 75.0 6.0 35.7 

Finally, Figure 6-9 compares the total pounds of TSS discharged from the study 

area site for each design storm with no treatment, with just LIDs, and with both LIDs and 

the detention pond. These loadings can be read from the Status Reports generated by 

running an analysis of each storm with (a) both types of treatment, (b) with the treatment 

function for the pond removed (LID treatment only), and (c) with the input file developed 

for EMC washoff in Example 5 (no treatment). The k value used in this comparison is the 

0.01 ft/hr value. Note the consistent pattern of load reduction as more treatment is 

applied. Also note that the pond provides a lower increment of overall load reduction 

than do the LIDs even though the pond is a regional BMP that treats all of the 

catchment’s runoff while the LIDs are local BMPs that receive runoff from only 41 % of 

the catchment’s area. This is a result of the conservative k value used in the pond’s 

treatment expression. Using a higher value, which would reflect a larger particle size 

distribution in the runoff, would result in lower loadings from the pond. 

6.5 Summary 

This example showed how water quality treatment could be modeled within 

SWMM. Total Suspended Solids (TSS) removal was considered in both local LID source 

controls as well as in a regional detention basin. The key points illustrated in this example 

were: 

1.	 LID controls can be modeled as distinct subcatchments with a single landuse that has 

a constant removal efficiency assigned to it. SWMM applies this removal efficiency 

to the runoff that the control receives from upstream subcatchments. 

2.	 Treatment within a detention pond is modeled with a user-supplied Treatment 

Function that expresses either the fractional removal or outlet concentration of a 

pollutant as a function of inlet concentration and such operational variables as flow 

rate, depth, and surface area. 

3.	 An exponential treatment function was used to predict TSS removal within this 

example’s detention pond as a function of a removal constant and the pond’s water 

depth, where the removal constant reflects the settling velocity of the particles to be 

removed. 

4.	 SWMM’s use of constant removal efficiencies for LID controls makes its LID 

treatment performance insensitive to size of storm. 

5.	 Treatment performance for detention ponds decreases with increasing size of storm 

due to an increase in pond depth. It also decreases with decreasing size distribution of 

the sediments that constitute the TSS in the runoff. 

115 
0.1 in Storm	 0.23 in Storm 

40 120 

TSS Load (lbs) 30 

20 

10 

0 

TSS Load (lbs) 

80 

40 

0 No LIDs O nly LIDs + No LIDs O nly LIDs + Treatment Pond 

Treatment Pond 

2-yr Storm 

0 

100 

200 

300 

400 

500 

600 

TSS Load (lbs) 

No LIDs O nly LIDs + 

Treatment Pond 

6.	 For the treatment function used in this example, the pond provided less incremental 

TSS load reduction than did the LIDs. This result, however, is completely dependent 

on the value of the removal constant used within the pond’s treatment function. 

7.	 The large variability reported for particle settling velocities in urban runoff makes it 

extremely difficult to estimate a removal constant for a detention pond’s treatment 

function that can consistently provide reliable estimates of the pond’s treatment 

performance. 

Figure 6-9. Total TSS load discharged at site outlet under different treatment scenarios 

116 
Example 7. Dual Drainage Systems 

The post-development model in Example 2 simulated simple hydraulic routing 

within a surface drainage system that employed open channels in the form of gutters and 

swales. The three hydraulic routing methods (Steady Flow, Kinematic Wave and Dynamic 

Wave) were introduced and their effects on the drainage system behavior shown. 

Example 7 will convert some of the open channels in Example 2 to parallel pipe and 

gutter systems. A series of storm sewer pipes placed below the existing swales will also 

be added to help drain the downstream section of the site’s park area. Both the 2-yr and 

100-yr design storms will be used to size and analyze the performance of this expanded 

dual drainage system. Particular attention will be paid to the interaction between the 

below-ground storm sewer flows and the above-ground street flows that occurs during 

high rainfall events. 

7.1 Problem Statement 

The objective of this example is to simulate the interaction between the minor and 

major drainage systems through the interconnection of part of their underground and 

surface sections. For frequent events the minor or “initial” system operates (Grigg, 1996); 

overland flows are conveyed by gutters and enter into the pipe system. For large events 

these pipes surcharge and flood, and the major system handles the flows (Grigg, 1996). In 

particular, the entire street (not only the gutters) becomes a conveyance element. 

Figure 7-1 shows the post-development layout of the site analyzed in Example 2. 

Example 2 modeled the drainage system with open channels and culverts whose invert 

elevations were the same as the ground surface elevations found on the site contour map. 

A series of below ground pipes will be added to the site that share inlets with the open 

(surface) channel running through the park. Gutters will also be added to the upstream 

section of the study area. The cross sections of these gutters will be that of a typical 

street, representing the surface “channel” through which water would flow if the pipe 

system surcharged and flooded the street. Thus, in this example the pipes and flow in 

gutters represent the minor system, and the channel in the park and the flow in streets 

represent the major system. The pipe system will be sized for the 2-yr event and its 

behavior observed during the major storm (100-yr event). 

7.2 System Representation 

Example 2 introduced junction nodes and conduit links as the basic elements of a 

drainage network. An example of the parallel pipe and gutter conveyance arrangement 

that will be used in this example is shown in Figure 7-2. It consists of a below-grade 

circular pipe connected to manhole junctions on either end, plus an above grade street 

and gutter channel also connected to the same two manhole junctions. The details of the 

gutter inlet and drop structures that make the actual connection with the manholes are not 

117 
important for our purpose. The parameters needed to characterize this type of node-link 

arrangement are as follows: 

Figure 7-1. Post-development site with simple drainage system 

Figure 7-2. Parallel pipe and gutter conveyance 

118 
• Manhole Invert Elevation 

The invert elevation of the manhole junction is the elevation of the bottom of the 

manhole relative to the model’s datum (such as mean sea level). The invert elevation 

establishes the junction’s vertical placement in the SWMM model. 

• Manhole Maximum Depth 

The maximum depth of the manhole junction is the distance from its invert to the 

ground surface elevation where street flooding would begin to occur. If this 

maximum depth is left set at zero, SWMM automatically uses the distance from the 

junction’s invert to the top of the highest connecting link, which would be the top of 

the gutter/street channel in this particular example. 

• Surcharge Depth 

The surcharge depth of a junction is the additional depth of water beyond the 

maximum depth that is allowed before the junction floods. SWMM uses this depth to 

simulate pressurized conditions at bolted manhole covers or force main connections 

but it will not be used in this example. Different types of surcharge will be discussed 

later in this example. 

• Conduit Offsets 

The inlet offset for a conduit is the distance that its inlet end lies above the invert of 

the junction that it connects to. A similar definition applies to the offset for the outlet 

end of a conduit. In the parallel pipe and gutter system, the elevations of the gutters 

are set above the pipes using their inlet and outlet offsets (Figure 7-2). 

Note that because this representation of a dual drainage system has more than one 

conduit exiting a junction node, Dynamic Wave flow routing must be used to analyze it 

hydraulic behavior. An alternative way to represent these systems is to use the Overflow 

variety of Flow Divider nodes to connect pairs of pipes and gutter channels together. This 

scheme can be analyzed using the simpler Kinematic Wave method, where any flow in 

excess of the sewer pipe capacity would be automatically diverted to the gutter channel. 

The disadvantage of this approach is that cannot model a two-way connection between 

the pipes and gutters/streets, nor can it represent the pressurized flow, reverse flow and 

backwater conditions that can exist in these systems during major storm events. 

Drainage System Criteria 

The general drainage system criteria that will be used in this example are listed 

below. These criteria are based on those defined for the city of Fort Collins (City of Fort 

Collins, 1984 and 1997). Figure 7-3 shows the different elements of the street considered 

in these criteria. Two storms will be used to design the drainage system: a minor or initial 

storm (2-yr) and a major storm (100-yr). The initial storm is one that occurs at fairly 

regular intervals while the major storm is an infrequent event. In this example, the streets 

are classified as “collectors”. Note that the general drainage criteria presented here apply 

only to this example and will change depending on the location of the system being 

designed. The criteria are: 

119 
Street 

1 Sx 

Roadway Sidewalk Crown 

Lane 1 Lane 2 

1 

SL 

Curb Sidewalk 

SL = Gutter grade	 Sx = Cross slope 

•	 The minimum gutter grade (SL in Figure 7-3) shall be 0.4%, and the maximum shall 

be such that the average flow velocity does not exceed 10 ft/sec. 

•	 The cross-slope (Sx in Figure 7-3) of all streets will be between 2% and 4%. 

•	 The encroachment of gutter flows onto the streets for the initial storm runoff will not 

exceed the specification presented in the second column from the left in Table 7-1. 

The encroachment of gutter flows on the streets for the major storm runoff will not 

exceed the specification presented in the third column from the left in Table 7-1. 

•	 The pipe system should carry the 2-yr storm and work as an open channel system. 

Figure 7-3. Elements of streets defined in the drainage criteria 

120 
 

 

Table 7-1. General drainage system criteria for Fort Collins (City of Fort Collins, 1984 and 1997) 

Street 

classification Initial storm Major storm 

Local (includes 

places, alleys 

and marginal 

access) 

No curb-topping. Flow may 

spread to crown of street 

Residential dwelling and other dwelling cannot be 

inundated at the ground line. The depth of water over 

the crown cannot exceed 6 inches. 

Collector 

No curb-topping. Flow spread 

must leave at least one lane 

width free of water 

Residential dwelling and other dwelling cannot be 

inundated at the ground line. The depth of water over 

the crown cannot exceed 6 inches. The depth of water 

over the gutter flowline cannot exceed 18 inches. (The 

most restrictive of the last two conditions governs) 

Major Arterial 

No curb-topping. Flow spread 

must leave at least one-half 

of roadway width free of 

water in each direction 

Residential dwelling and other dwelling cannot be 

inundated at the ground line. The street flow cannot 

overtop the crown. The depth of water over the gutter 

flowline cannot exceed 18 inches. (The most 

restrictive of the last two conditions governs) 

7.3 Model Setup 

Figure 7-4 shows the layout of the dual drainage system with the pipes, streets 

and swales that will be included in the model. Note that runoff from subcatchments S1 

and S2 is introduced first to the street system (gutters) through nodes Aux1 and Aux2, and 

then enters the storm sewers through inlet grates represented by nodes J1 and J2a. For the 

rest of the system the runoff is assumed to enter directly into the pipe system. The 

following steps are used to build the complete dual drainage model starting from the 

layout defined in the input file Example2_Post.inp. 

Surface Elements 

1.	 The first step is to add the additional junction nodes Aux1, Aux2 and J2a, shown in 

Figure 7-4. The invert elevations of these nodes for now are simply their surface 

elevations (Aux1 = 4975 ft, Aux2 = 4971.8 ft, and J2a = 4970.7 ft). 

2.	 Next the additional gutters C_Aux1, C_Aux1to2, C_Aux2, and C2a are added into 

the model and their lengths are determined using the Auto-Length option. These 

gutters have a roughness coefficient of 0.016. 

3.	 Instead of the trapezoidal cross section used in Example 2, irregular shapes will be 

used to represent the cross sections of the gutter conduits. The transects that define 

these shapes are created using SWMM’s Transect Editor (see the sidebar “Defining 

Channel Cross Sections as Irregular Channel Transects”). The transect Full_Street 

shown in Figure 7-5 is used to represent the entire section of all streets within the 

study area. A cross-slope Sx = 4% is used to define this section. The transect 

Half_Street depicts only half of the Full_Street section, from the sidewalk to the 

crown of the street. It is used to represent the north-south street that runs down the 

121 
40 ft 

1.3 ft 

0.5 ft 0.8 ft 

20 ft 

east side of the development because its crown is considered to be the boundary of 

the catchment. The station and elevation data for both cross sections are listed in 

Table 7-2. 

4.	 The two types of transect cross-sections just created are then assigned to the 

corresponding street conduits shown in Figure 7-4. Conduits C_Aux1, C_Aux1to2, 

and C_Aux2 represent streets that have the Full_Street section. C2a and C2 represent 

streets that have the Half_Street section. 

Figure 7-4. Three-dimensional layout of the site's dual drainage system 

Figure 7-5. Full_Street cross section. The Half_Street section is half of this section. 

122 
 

Defining Channel Cross Sections as Irregular Channel Transects 

Channel cross sections can be assigned to each channel using the Cross 

Section Editor as was shown in Example 2 or by defining a general cross section 

Transect object. The main advantages of using a Transect are: 1) the shape of a 

channel cross section can be entered into the model once and then assigned to 

multiple channels that share the same shape, 2) changes to channels with the same 

cross section (e.g. in Mannings roughness and depth) can be made more efficiently 

through the Transect Editor and 3) any channel cross section shape can be entered. 

Transects are generally used to model natural irregular channel shapes in SWMM 

but they can also be used to model gutter cross sections as well. The process used to 

add a new Transect object to a project is: 

1.	 Open the Transect Editor by selecting Hydraulics | Transects | “+” in the 

Data Browser. 

2.	 Enter a name for the new Transect. 

3.	 Define the shape of the Transect’s cross section by entering Stations 

(distance from the left edge of the Transect) and their corresponding 

Elevations into the editor’s data grid. 

4.	 The location of the left bank, the right bank and the channel section is 

defined by entering the corresponding station locations in the Bank Stations 

entry fields. In this example, there is no left or right bank so the Left and 

Right bank stations are set to zero. 

5.	 The Mannings roughness values are defined for the cross section’s left bank, 

right bank and channel sections. No values are required for the bank 

roughness if they are not modeled. 

To assign a specific Transect object to a conduit’s cross-section: 

1.	 Open the Property Editor for the conduit. 

2.	 Click the ellipsis button next to the Shape property to bring up the CrossSection Editor. 

3.	 Select Irregular for the choice of cross-sectional shape and then select the 

Transect of choice from the Transect Name combo box. 

123 
Table 7-2. Cross section data for street transects 

Full Station -40 -20 -20 0 20 20 40 

Street 

HalfElevation 

Station 

1.3 

-40 

0.5 

-20 

0 

-20 

0.8 

0 

0 

0 

0.5 

-

1.3 

-

Street Elevation 1.3 0.5 0 0.8 1.3 - -

Below-Ground Elements 

The changes made so far have been to surface elements of the watershed. Now the 

pipes below the streets will be added to the drainage system and the invert elevations of 

the surface conduits will be re-defined. 

1.	 Conduit C1 is replaced with a pipe (P1) and two pipes are added between nodes J2a 

and J2 (pipe P2) and J2 and J11 (pipe P3). The roughness of these three pipes is 

0.016 and their diameter is 1 ft. As usual, the lengths of the pipes are calculated 

automatically with the Auto-Length tool. 

2.	 At this point there are pairs of parallel links connected to the same input and output 

nodes (for example C2a and P2; C2 and P3). Right now, they are located at the same 

elevation (the surface elevation). These elevations must be adjusted so that the subsurface pipes lie below the surface gutters. This is done by decreasing the invert 

elevation of J1 and J5 by 4 ft (J1 = 4969 ft and J5 = 4965.8 ft), and raising the outlet 

offset of C_Aux1 to 4 ft and the inlet offset of C_Aux1to2 to 4 ft. Then, the invert 

elevations of J2a and J2 are decreased by 4 ft (J2a = 4966.7 ft and J2 = 4965 ft), an 

outlet offset of 4 ft is given to C_Aux2, an inlet and outlet offset of 4 ft is given to 

C2a, and an inlet offset of 4 ft and outlet offset of 6 ft to C2. 

3.	 The properties of the different elements of the model should be those listed in Tables 

7-3 and 7-4. Table 7-3 summarizes the junction inverts; Table 7-4 shows the conduit 

shapes and their inlet and outlet offsets. 

Park Area Elements 

The next phase is to add the series of pipes that drain the park area containing the 

natural channel swales, shown in Figure 7-4. This process consists of the following steps. 

1.	 A new node, Aux3, is added to the model with an invert elevation of 4974.5 ft. A new 

swale, C_Aux3, is defined connecting nodes Aux3 and J3. Its roughness is 0.05 and 

its cross section is the same as the cross section used in Example 2 for swales (for 

instance, the cross section of conduit C4). 

2.	 Next the series of pipes that drain the park area is created as shown in Figure 7-4. 

These pipes (P4, P5, P6, P7 and P8) connect with the surface system at junctions 

Aux3, J4, J5, J7, J10, and J11. The latter represent inlet grate structures in the surface 

swales. The roughness coefficient of these pipes is 0.016. 

3.	 The pipes underneath the park have an initial diameter of 3 ft and lie 6 ft below the 

invert elevation of the natural channel through the park. These pipes are 2 ft deeper 

124 
than the pipes buried below the streets to avoid giving P5 an adverse slope. The 

junctions where the swales and the pipe system connect together are assigned invert 

elevations that are 6 ft below the ground surface. The invert elevations of these 

junctions (in feet) become: Aux3 = 4968.5, J4 = 4965, J7 = 4963.5, J10 = 4957.8, J11 

= 4957 and O1 = 4956. 

4.	 As currently defined, one pipe in the model, P6, has an adverse slope. This negative 

slope is corrected by lowering the invert elevation of J7 from 6 ft below the surface to 

8 ft (elevation J7 = 4963.5 ft). 

5.	 The next step is to set the inlet and outlet offsets of the surface conduits where they 

share nodes with the series of pipes to maintain their surface elevations. The inlet and 

outlet offset elevations of C_Aux3, C4 and C10 are 6 ft and 0 ft, 6 ft and 4 ft, and 6 ft 

and 6 ft, respectively. Additionally, the inlet offset of C5 and C6 are increased to 4 ft 

and 8 ft respectively, and the outlet offset of C3 and C9 are increased both to 6 ft. 

These new offsets are defined to keep the swale at the surface. Note that the depths of 

the gutters are assumed negligible in this example. The depths of the swales (3 ft) are 

not considered negligible but were accounted for in Example 2 when their invert 

elevations were modeled. 

6.	 The invert elevation of junctions J3, J6, J8 and J9 defined in Example 2 remain the 

same for this example. The final layout should look like the one shown in Figure 7-6. 

The final invert elevations of the junctions as well as the size, inlet and outlet offsets 

of the conduits are summarized in Tables 7-3 and 7-4. 

Parallel System 

(C2a&P2) and (C2&P3) 

Half_Street 

Parallel System 

(C10&P8) 

Full_Street 

Shared junctions 

Park Pipe System 

Parallel pipes 

Swales 

Figure 7-6. Post-development site with dual drainage system 

125 
Table 7-3. Junction invert elevations for dual drainage system 

Junction Surface Elev. Change for Final Invert 

ID Elevation (ft) Parallel Pipe (ft) Elevation (ft) 

J1 4973.0 4 4969.0 

J2a 4970.7 4 4966.7 

J2 4969.0 4 4965.0 

J3 4973.0 0 4973.0 

J4 4971.0 6 4965.0 

J5 4969.8 4 4965.8 

J6 4969.0 0 4969.0 

J7 4971.5 8 4963.5 

J8 4966.5 0 4966.5 

J9 4964.8 0 4964.8 

J10 4963.8 6 4957.8 

J11 4963.0 6 4957.0 

Aux1 4975.0 0 4975.0 

Aux2 4971.8 0 4971.8 

Aux3 4974.5 6 4968.5 

O1 4962.0 6 4956.0 

Table 7-4. Conduit shapes and offsets for dual drainage system 

Conduit 

ID Type Initial Depth or Diameter (ft) 

Length 

(ft) 

Inlet Offset 

(ft) 

Outlet Offset 

(ft) 

C2a 

C2

C3 

C4

C5

C6

C7 

C8

C9

C10 

C11 

C_Aux1

C_Aux2

C_Aux1to2 

C_Aux3

P1 

P2 

P3 

P4 

P5 

P6 

P7 

P8 

Half_Street 

 Half_Street 

Culvert 

 Swale 

 Swale 

 Swale 

Culvert 

 Swale 

 Swale 

Swale 

Culvert 

 Full_Street 

 Full_Street 

Full_Street 

 Swale 

Pipe 

Parallel Pipe 

Parallel Pipe 

Pipe 

Pipe 

Pipe 

Pipe 

Parallel Pipe 

1.3 

1.3 

2.25 

3 

3 

3 

3.5 

3 

3 

3 

4.75 

1.3 

1.3 

1.3 

3 

1 

1 

1 

3 

3 

3 

3 

3 

157.48 

526.00 

109.00 

133.00 

207.00 

140.00 

95.00 

166.00 

320.00 

145.00 

89.00 

377.31 

239.41 

286.06 

444.75 

185.39 

157.48 

529.22 

567.19 

125.98 

360.39 

507.76 

144.50 

4 

4 

0 

6 

4 

8 

0 

0 

0 

6 

0 

0 

0 

4 

6 

0 

0 

0 

0 

0 

0 

0 

0 

4 

6 

6 

4 

0 

0 

0 

0 

6 

6 

0 

4 

4 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

126 
Conduit 

Surcharge 

Ground surface 

Invert Elevation 

Open 

channel 

(a) (b) (c) (d) 

Conduit surcharge, Node surcharge Node Node surcharge 

no node surcharge = node flooding surcharge & node flooding 

 

7.4 Model Results 

General System Behavior 

The first step in analyzing this dual drainage system is to run the model in its 

preliminary sized state for the 2-yr storm with Dynamic Wave routing to check its general 

performance. The hyetographs for both the 2-yr and 100-yr storms are the same as those 

used in Example 1. For this run the reporting and wet-weather time steps were set to 1 

minute, the routing time step to 15 seconds and the dry-weather runoff time step to 1 

hour. In addition, the “Report Input Summary” check box on the General page of the 

Simulation Options dialog was checked so that the slopes computed for all of the 

system’s conduits would be displayed in the run’s Status Report. The input data file for 

this initial system design is named Example7-Initial.inp. 

After running this model, the resulting Status Report shows that no nodes are 

either surcharged or flooded (see the Node Surcharge Summary and Node Flooding 

Summary sections of the report). However, conduits P1, P2, and P3 were all surcharged 

(see the Conduit Surcharge Summary section) indicating that the system was undersized. 

The differences in these surcharge reports illustrate that node surcharge and 

conduit surcharge are two different behaviors. Figure 7-7 shows several examples of 

surcharge and flooding. Figure 7-7a shows conduit surcharge; Figure 7-7b shows conduit 

surcharge, node surcharge and node flooding; Figure 7-7c shows conduit surcharge and 

node surcharge; and Figure 7-7d shows conduit surcharge, node surcharge and node 

flooding. Note that in the case of the open channel (Figures 7-7a and 7-7b) node 

surcharge occurs simultaneously with node flooding. 

Figure 7-7. Examples of surcharge and flooding 

127 
Table 7-5. Calculated gutter grades 

Conduit ID Length (ft) Slope (%) 

C2a 157 1.1 

C2 526 1.1 

C_Aux1 377 0.5 

C_Aux2 239 0.5 

C_Aux1to2 286 0.4 

The drainage criteria in Section 7.3 also require a minimum gutter grade of 0.4% 

and maximum average flow velocity of 10 ft/sec. Therefore, it is required to check that 

the minimum slope of the conduits representing gutters is larger than 0.4%. Table 7-5, 

taken from the Link Summary table of the Status Report, shows the slopes of the conduits 

representing the gutters. All the gutters have a longitudinal grade of 0.4% or greater and 

thus meet the design standards considered for this example. The velocities in the gutters 

and all the conduits will be checked once the pipes of the system are properly sized. 

Design for the 2-yr Storm 

The next step of the analysis is to size the pipes so that they can carry the 2-yr 

storm without surcharging. In addition, the design criteria listed in Section 7.3 require the 

collector streets to be sized so there is no curb topping and at least one lane remains free 

of water. This phase of the analysis is carried out as follows: 

1.	 The sizes of the pipes are iteratively modified, and the model run, until the Status 

Report’s Conduit Surcharge Summary shows that no conduits are surcharged and that 

the values of the Max/Full Depth ratio in the Link Flow Summary are close to 0.85 for 

all the pipes (a safety factor of 15% is considered to reduce the risk of surcharging). 

Table 7-6 lists the standard pipe sizes that were used in this process. Table 7-7 shows 

the results from three iterations, including the final one. Note how increasing the size 

of the upstream pipes allows some of the downstream pipes to be reduced in size (but 

made no smaller than the upstream ones). 

2.	 Using the final pipe sizing from the previous step (Trial 3 in Table 7-6), the peak 

velocities in the conduits representing the streets are checked in the Link Flow 

Summary section of the Status Report. The peak velocity for all these conduits is less 

than 10 ft/sec, the maximum allowed by the drainage criteria. 

3.	 According to the drainage criteria, no curb-topping should occur for the minor storm 

in any street. Figure 7.5 shows that curb-topping implies a Max/Full Depth ratio of 

0.5/1.3 = 0.38. The Link Flow Summary in the Status Report for the final pipe sizing 

shows that the highest value of the Max/Full Depth ratio for the street conduits is 0.29 

for conduit C_Aux2. Thus, the final design of the system is appropriate in terms of the 

flows in the streets. 

The input file with the final pipe sizes for this example is named Example7-Final.inp. 

128 
Table 7-6. Available drainage pipe sizes 

in. ft in. ft in. ft in. ft 

6 0.5 18 1.5 24 2 38 3.17 

12 1 20 1.67 28 2.33 42 3.5 

16 1.33 22 1.83 36 3 48 4 

Table 7-7. Iterations for 2-yr storm pipe sizing 

Pipe 

Trial 1 Trial 2 Trial 3, final 

Size 

(ft) Surcharged Max/Full Depth 

Size 

(ft) Surcharged Max/Full Depth 

Size 

(ft) Surcharged Max/Full Depth 

P1 1 yes 0.85 1.33 no 0.69 1.33 no 0.71 

P2 1 yes 1 1.33 yes 0.90 1.5 no 0.67 

P3 1 yes 1 1.33 no 0.90 1.5 no 0.80 

P4 3 no 0.27 2 no 0.52 1.67 no 0.64 

P5 3 no 0.29 2 no 0.58 1.83 no 0.65 

P6 3 no 0.36 2 no 0.71 2 no 0.72 

P7 3 no 0.48 2 no 0.81 2 no 0.81 

P8 3 no 0.53 3.17 no 0.51 3.17 no 0.51 

Major Storm Performance 

Finally, the model is run for the 100-yr storm by changing the rainfall time series 

used by its rain gage. The Status Report’s Node Surcharge Summary and Node Flooding 

Summary tables show that no nodes are surcharged or flooded during the 100-yr storm. 

Additionally, the Conduit Surcharge Summary shows that, as expected, all of the pipes 

are surcharged. According to the Link Flow Summary table, the highest velocities occur 

in conduits C7, C11 and P8 (11.25, 11.93 and 10.76 ft/sec respectively), all of them over 

10 ft/sec. Standard drainage criteria define a maximum allowable velocity in pipes and 

culverts of 15 to 18 ft/sec (CCRFCD, 1999; Douglas County, 2008). Thus, the maximum 

velocities predicted for pipe P8 and culverts C7 and C11 are acceptable, and no re-sizing 

of the conveyance system is required. Finally, the Link Flow Summary table shows that 

the Max/Full Depth value of all street conduits is less than one. Therefore the water depth 

in the streets never reaches the crown or the highest point of the sidewalks, and the 

requirements for the 100-yr storm are successfully satisfied. 

To illustrate the complex flow conditions that can occur in these systems, Figure 

7-8 shows the hydrographs in pipes P5 and P6 under the 100-yr storm. Negative flows 

caused by backwater effects occur in both pipes after 30 minutes of simulation. These 

special flow conditions can be only simulated when Dynamic Wave routing is used, 

which demonstrates the capabilities of this method. These negative discharges do not 

occur for the 2-yr storm. This shows that the behavior of a system under a minor and a 

major event can be quite different. In this case, the runoff generated by subcatchment S4 

into junction J7 for the 100-yr storm is large enough to cause a backwater effect that 

generates these negative flows. 

129 
Link P6 Link P5 

0 0.5 1 1.5 2 2.5 3

Flow (CFS) 

15.0 

10.0 

5.0 

0.0 

-5.0 

-10.0 

Elapsed Time (hours) 

Figure 7-8. Flows in pipes P5 and P6 during the 100-yr storm 

Another way to visualize the behavior of the dual drainage system is with Profile 

Plots. Figure 7-9 contains two such plots stacked on top of one another. They depict the 

surcharge condition that occurs between nodes J2a, J2, and J11 at 34 minutes into the 

100-yr storm. The lower plot applies to the below-ground sewer pipes P2 and P3 and 

shows that both pipes are surcharged. The upper plot is for the streets C2a and C2 that lie 

above P2 and P3. The water levels at junctions J2a and J2 are high enough to cause 

water to flow out of the sewer pipe P2 and onto the street, but not high enough to flood 

the street. On the other hand, the invert elevation of junction J11 is low enough so that 

the surcharged pipe P3 does not create street flooding and instead, street flow re-enters 

the sewer system there. (The plot makes it appear that the flow at the downstream end of 

street C2 is zero, but this is just an artifact of the way that SWMM draws the water 

surface profile within a conduit (by connecting the water elevations between its end 

nodes without allowing the profile to cross either its bottom or top surface)). 

7.5 Summary 

This example built on the simple drainage system modeled in Example 2. It 

converted some of the open surface channels used in that example to parallel pipe and 

gutter systems and added a new series of pipes to drain the downstream section of the 

park. The system was sized for a minor (2-yr) storm event and its behavior was also 

analyzed under a major (100-yr) storm event. The key points illustrated in this example 

were: 

130 
Figure 7-9. Surcharge behavior along the eastern boundary of the site 

1.	 The three-dimensional structure of dual drainage systems can be modeled by using 

manhole junctions set below ground that connect parallel pairs of sewer pipes and 

gutter/street channels, where the latter are offset to ground elevation. 

2.	 These systems are designed so that the below-ground sewer system will flow only 

partly full during the more frequent minor storm events and will surcharge into the 

street channels during the larger, less frequent major events without causing any 

overtopping of the street. 

3.	 An iterative process can be used to properly size the sewer pipe elements to meet both 

the small storm and large storm design criteria. 

4.	 Most of the results needed to evaluate the performance of a dual drainage system can 

be found in the various tables produced by SWMM’s Status Report. 

As this example shows, dual drainage system models require a significant amount 

of additional effort to set up. The need to represent both the minor and major portions of 

a drainage system will depend on the objectives set forth for the analysis and on the level 

of detail required from the model. 

131 
Example 8. Combined Sewer Systems 

This example demonstrates how to model systems that convey both sanitary 

wastewater and stormwater through the same pipes. Systems like these are known as 

combined sewer systems and are still quite common in older communities and cities. 

During periods of moderate to heavy rainfall the capacity of these systems to convey and 

properly treat the combined flow can be exceeded, resulting in what are known as 

Combined Sewer Overflows (CSOs). CSO discharges can cause serious pollution 

problems in receiving waters. Contaminants from these discharges can include 

conventional pollutants, pathogens, toxic chemicals and debris. 

This example will use SWMM to analyze the occurrence of overflows in a 

combined sewer system. Particular attention is paid to properly representing the flow 

regulators that divert flow between collection sewers, treatment plant interceptors and 

CSO outfalls. In addition, the example shows how to model a pump station that conveys 

the intercepted flow through a force main pipeline to the headworks of a treatment 

facility. Although the focus of this example is on combined systems, many of the same 

modeling elements it employs (wastewater inflows, pump stations, and force mains) can 

also be used to model separate sanitary sewer systems. 

8.1 Problem Statement 

Rather than being a new development, the 29 acre urban catchment studied in 

Example 2 is now assumed to be an older area that is served by an existing combined 

sewer system. The hydraulic behavior of this combined system, including the magnitude 

of any overflows, will be analyzed for several different size storms. These include the 

0.23 in. water quality storm defined in Example 3 as well as the 1.0 in., 2-yr and 1.7 in., 

10-yr storms used throughout the previous examples. 

Combined sewer pipes conveying both wastewater and stormwater flows 

generated within different sewersheds (i.e., areas that contribute wastewater flows to a 

single point) will be added to the model. Constant wastewater flows (also known as dryweather flows) will be based on average generation rates per capita. An interceptor pipe 

will be sized to convey both the base dry weather flow and a portion of the combined 

stormwater flow to a pump station that pumps to the headworks of a wastewater 

treatment plant (WWTP) through a force main. Various combinations of orifices, weirs 

and pipes will be used to represent different types of flow diversion structures located 

within the interceptor. The CSOs that cannot be diverted by these devices will discharge 

directly into the stream running through the site’s park area. 

The schematic representation of the combined sewer system modeled in this 

example is shown in Figure 8-1. It includes the combined sewer pipes (in green) that 

drain the subcatchments (or sewersheds) S1, S2, S3, S4 and S5, the stream (in blue), the 

interceptor (in brown), the flow regulators (red boxes), and the pump station. 

132 
I4

Or2

Pump1

J1

We

C3 

C4 

C5 

C6 

C7 

C8 

C9 

C10 

C11 

C_Aux3 

P1 

P2 

P3 

P4 

P5 

P6 

I1 

I2 

I5 I3

I6 

I7 

I8 

Or1 

W1 

W2 

W3 

W4 

J2a 

J2 

J3 

J4 J5 

J6 

J7 

J8 

J9 

J10 

J11 

J12 

J13 

Aux3 

JI1 

JI2 

JI3 

JI4 

JI5 

JI6 

JI7 

JI8 

JI9 

O1 O2 

ll 

S1 

S2 

S3 

S4 

S5 

S6 

S7 

Wastewater & 

stormwater 

discharges 

Pump 

Well 

To WWTP 

Stream 

Culvert in the stream 

Interceptor 

Combined sewer pipes 

Flow regulators 

R1 

R3 

R5 

R2 

R4 

Wastewater & 

stormwater 

discharges 

Wastewater & 

stormwater 

discharges 

Wastewater & 

stormwater 

discharges 

Wastewater & 

stormwater 

discharges 

Outlet 

I9 

Figure 8-1. Combined sewer system study area 

8.2 System Representation 

Combined sewer systems are systems that convey both sanitary sewerage and 

stormwater through the same pipes. Interceptors are pipes designed to capture 100% of 

the sanitary flows during dry weather periods and convey them to a WWTP. During 

periods of moderate or heavy rainfall, however, the wastewater volume in the combined 

sewer system can exceed the capacity of the interceptor or the WWTP. For this reason, 

combined sewer systems are designed to discharge the excess wastewater directly to a 

nearby stream or water body through diversion regulators. Figure 8-2 shows a schematic 

representation of a combined sewer system and CSO occurring in the system. The figure 

shows how for wet-weather flows the interceptor at the bottom is able to convey only part 

of the flow into the WWTP and CSOs occur. 

133 
Figure 8-2. Conceptual representation of overflows in a combined system (Field and Tafuri, 1973) 

Dry Weather Flows 

To create a combined sewer system in SWMM one adds dry weather wastewater 

flows into the appropriate nodes of a previously created stormwater conveyance system. 

These nodes typically represent locations where collector sewers discharge into trunk 

sewers. Their number and location will depend on the level of aggregation used to 

combine individual wastewater sources (homes, businesses, etc.) together. The sidebar 

below explains how to use a node’s Inflow Editor to specify the time series of dry 

weather flow entering the node. 

134 
 

Adding Dry Weather Flows into SWMM 

This example requires that dry weather flows representing the wastewater 

discharges be added into the combined sewer system model. The Dry Weather page 

of the Inflow Editor is used to specify a continuous source of dry weather flow or 

any pollutant entering a specific node of the drainage system. The Inflow Editor is 

accessed through the Inflows property of the node for which the flow is being 

defined. Dry weather flows in SWMM are characterized by an average (or baseline) 

value and up to four optional time patterns (TP) that can represent monthly, daily 

and hourly (for both weekday and weekend) variations. Dry weather flows are then 

computed as shown below: 

Dry weather flow at time t = (average value)*(TP 1t)*(TP 2t)*... 

where TP1t is the multiplier for time pattern 1 at time t, TP2t is the multiplier for 

time pattern 2 and so on. 

If no time patterns are defined then the dry weather flow entering the node is 

simply the average value. The Inflow Editor for the dry weather flow at a particular 

node is shown below. 

Flow Regulator Structures 

Flow regulators (or diversion structures) are used to control the flow between 

collection sewers and the interceptor. These regulators allow the conveyance of 

wastewater to treatment facilities during dry weather conditions. During wet weather 

conditions the regulators divert flows away from the interceptor and discharge directly 

into a water course to avoid surcharge and flooding of the combined sewer system. Flow 

regulator devices include side weirs, leaping weirs, transverse weirs, orifices and relief 

siphons. Metcalf & Eddy, Inc. (1991) presents a detailed description of these different 

devices. This particular example will use the transverse weir with orifice type of 

regulator illustrated in Figure 8-3. In this regulator there is a weir or a small plate placed 

directly across the sewer perpendicular to the line of flow. Low flows are diverted to the 

interceptor through an orifice located upstream of the weir. During periods of high flow, 

the weir is overtopped and some flow is discharged through the overflow outlet, 

eventually reaching a CSO outfall. 

135 
Overflow 

outlet 

Combined 

sewer flow 

Pipe or orifice 

diversion to 

interceptor 

Transverse weir 

To the 

interceptor 

J

J

O

W

J

J

J

W

J

W

O

J

J

J

J

(a) (b) (c) 

Combined

sewer flow

To 

interceptor

To stream

Combined 

sewer flow

To 

interceptor

To stream

Transverse Weir

Bottom Orifice

Junction

Combined sewer

Interceptor

Stream

Combined

sewer flow

To 

interceptor

To stream

Regular conduit

Different 

inlet offset

J 

J 

O 

W 

J 

Combined 

sewer flow 

To 

interceptor 

To stream 

J 

J 

W 

J 

Combined 

sewer flow 

To 

interceptor 

To stream 

W 

O 

J 

Transverse Weir 

Bottom Orifice 

Junction 

Combined sewer 

Interceptor 

Stream 

J 

J 

J 

Combined 

sewer flow 

To 

interceptor 

To stream 

Regular conduit 

Different 

inlet offset 

Figure 8-3. Transverse weir flow regulator 

A transverse flow regulator can be represented in SWMM by using weir and 

orifice elements. Because these elements correspond to hydraulic links, additional 

junction nodes must be added into the model. A schematic representation of three 

possible definitions of a transverse flow regulator in SWMM is shown in Figure 8-4. 

Each of these three configurations will be used in this example. Configurations (a) and 

(b) both contain the weir shown in Figure 8-3, but use different elements to divert to the 

interceptor: (a) uses a bottom orifice while (b) uses a pipe. Finally, the third configuration 

(Figure 8-4c) uses neither a weir nor an orifice. Instead, it simply diverts flow by using 

different inlet offsets for the pipes that convey flows to the interceptor and to the stream. 

The first pipe has an inlet offset of zero while the pipe linked to the stream has a larger 

invert elevation. 

Figure 8-4. Alternative ways to represent tranverse weir flow regulators in SWMM 

136 
 

This example uses each of these regulator configurations for purely illustrative 

purposes. The choice of a particular configuration to use in a real application will depend 

on the specific conditions encountered in the field and on how numerically stable the 

resulting model will be. Some unwanted hydraulic phenomena that can be artificially 

introduced into the model by these different representations include surcharged weirs, 

instabilities caused by short pipes and excessive storage associated with large pipes. 

Pump Stations 

Pumps are devices used to lift water to higher elevations. They are defined in the 

model as a link between two nodes and can be in-line or off-line. The principal input 

parameters for a pump include the identification of the inlet and outlet nodes, its pump 

curve, initial on/off status and startup and shutoff depths. A pump’s operation is defined 

through its characteristic curve that relates the flow rate pumped to either the water depth 

or volume at its inlet node or to the lift (i.e., hydraulic head) provided. Its on/off status 

can be controlled dynamically by defining startup and shutoff water depths at the inlet 

node or through user-defined control rules. A pump is defined in the model in the same 

fashion as any other link, while the pump curve is created using the Pump Curve Editor 

and is linked to the pump by the latter’s Pump Curve property as shown in Figure 8-5. 

(a) (b) 

Figure 8-5. (a) Pump Property Editor and (b) Pump Curve Editor 

8.3 Model Setup 

Preliminaries 

Figure 8-6 shows the system to be modeled in this example. Example 7 

(Example7-Final.inp) is the starting point for the model setup, although major changes 

are required. Because combined sewer systems are no longer used for new developments, 

this example assumes that the combined sewer system being modeled has been in place 

for many years. 

137 
J5 

W2 

W 

O 

J 

Transverse Weir 

Bottom Orifice 

Junction 

Combined sewer 

Interceptor 

Stream 

P2 

J3 

Aux3 

J4 

JI2 

W1 

JI6 

O1 

JI1 J1 

JI7 

J13 

J7 

J6 

JI3 

J8 

J9 

J10 

JI4 

W3 

JI8 

J12 

J2a 

J2 

J11 

W4 

JI5 

O1 

Well Pump1 O2

P4 

P5 

P6 

I5 

I4 

I3 

I2 

P1 

I1 

I8 

I6 

I7 

P3 

C_Aux3 

C3 

C6 

C5 C4 

C7 

C10 

C9 

C8 

C11 

JI9 

R1 R2 

R3 

R4 

R5 

Flow 

Regulator 

I9 

Diversion Junctions 

Figure 8-6. Schematic representation of the combined sewer system 

In modifying the model of Example 7, the gutter elements will be removed as will 

the pipes along the stream running through the park. A new interceptor sewer will be 

placed along the north side of the stream, as illustrated in Figure 8-1. This interceptor will 

convey wastewater flows to a pump station comprising a storage unit, which represents a 

wet well, and a pump. The pump discharges through a force main line to a constant head 

outfall (O2) representing the inlet to a hypothetical WWTP. New pipes representing the 

combined sewer system need to be added as well as several weirs and orifices that define 

the flow regulators. The streambed for this example is lowered by 5 ft compared to the 

original stream bottom elevations used in Example 2 so that backwater from the stream 

will not flood the regulators in the combined sewer system. 

These modifications are made by removing junctions Aux1 and Aux2 as well as 

conduits C2a, C2, C_Aux1, C_Aux2, C_Aux1to2, P5, P6, P7 and P8. Then, the elevations 

of the nodes and the inlet/outlet offsets of the links that comprise the stream in the park 

must be changed as well. The new invert elevations of the nodes in the stream (Aux3, J3, 

J4, J5, J6, J8, J9, J10, J11 and outlet O1 which are colored blue in Figures 8-1 and 8-6) 

are listed in Table 8-1. Their maximum depths are set to zero so that the program will 

automatically adjust their depths to match the top of the highest connecting stream 

conduit. The remaining junctions (J1, J2, J2a, and J7) have their depths set equal to the 

ground elevation minus their invert elevation. The offsets of the swales and culverts that 

run through the park (links C3 through C11) are set back to their original values of zero. 

Combined Sewer Pipes 

The next step is to create the combined sewer pipes, shown in green on Figure 8-6 

and identified with the letter P. All of them have a roughness coefficient of 0.016. Pipes 

P1, P2, P3 and P4 were defined already in Example 7 and two more combined sewer 

pipes are added; P5 will convey flows from subcatchment S4 and P6 from subcatchment 

138 
Table 8-1. Properties of the combined sewer system nodes1 

Node ID Invert 

Elevation (ft) 

Maximum 

Depth (ft) Node ID Invert Elevation (ft) 

Maximum 

Depth (ft) 

J1 

J2a 

J2 

J3 

J4 

J5 

J6 

J7 

J8 

J9 

J10 

J11 

J12 

4969.0 

4966.7 

4965.0 

4968.0 

4966.0 

4964.8 

4964.0 

4960.0 

4961.5 

4959.8 

4958.8 

4958.0 

4968.0 

4.2 

4.0 

4.0 

0.0 

0.0 

0.0 

0.0 

12.0 

0.0 

0.0 

0.0 

0.0 

4.2 

J13 

Aux3

JI1 

JI2 

JI3 

JI4 

JI5 

JI6 

JI7 

JI8 

JI9 

O1 

Well 

4968.0 

 4968.5 

4958.0 

4957.0 

4955.0 

4952.0 

4950.0 

4967.0 

4967.0 

4962.0 

4960.0 

4957.0 

4945.0 

4.8 

0.0 

16.0 

15.8 

16.0 

14.0 

16.0 

7.2 

6.0 

6.2 

5.2 

-

14.0 

S5. The upstream nodes (or inlet nodes) for these pipes, J13 and J12, are added to the 

model as well. The properties of these junctions are shown in Table 8-1. The properties 

of the combined sewer pipes are shown in Table 8-2. 

1

 Colors indicate whether the nodes belong to the stream (blue), the sewer pipes (green), the 

interceptor (brown) or they are the diversion junction (grey) 

Subcatchment Outlets 

With the sewer pipes entered in the model, it is necessary now to redefine the 

outlet nodes of the different subcatchment. These nodes will receive the stormwater 

runoff generated by the subcatchments as well as the flows corresponding to the 

wastewater flows, defined later in this section. In other words, the subcatchments used for 

drainage are also defined as sewersheds in this example. No other changes to the 

properties of the subcatchments are required. Table 8-3 shows the new outlets for the 

subcatchments. 

Interceptor Pipe 

An interceptor line is now added to the model that runs along the north side of the 

stream and conveys all wastewater flows to the pump station located on the east side of 

the study area. Its pipes are identified with the letter I and brown color, as shown in 

Figure 8-6. Conduits I1, I2, I3, I4 and I9 are the main pipes of the interceptor. The new 

nodes belonging to the interceptor are identified with the letters JI with the last node 

being the pump’s wet well which is a storage unit named Well. Properties of the nodes 

and pipes of the interceptor are summarized in Tables 8-1 and 8-2. Figure 8-7 displays 

how the combined sewer system looks before the interceptor is connected to the rest of 

the system with flow regulators and the pump station is defined. 

139 
Table 8-2. Properties of the combined sewer system conduits1 

Pipe ID Shape Inlet 

Node 

Outlet Length h or d Rough. 

Node (ft) (ft) 2 Coeff. 

b (ft) 3 Z1 4 Z2 5 Inlet 

Offset (ft) 

Outlet

Offset (ft) 

C3

C4

C5

C6

C7

C8

C9

C10 

C11 

C_Aux3

P1 

P2 

P3 

P4 

P5 

P6 

I1 

I2 

I3 

I4 

I5 

I6 

I7 

I8 

I9 

 Circular 

 Trapezoidal 

 Trapezoidal 

 Trapezoidal 

 Circular 

 Trapezoidal 

 Trapezoidal 

Trapezoidal 

Circular 

 Trapezoidal 

Circular 

Circular 

Circular 

Circular 

Circular 

Circular 

Circular 

Circular 

Circular 

Circular 

Circular 

Circular 

Circular 

Circular 

Circular 

J3 

J4 

J5 

J7 

J6 

J8 

J9 

J10 

J11 

Aux3 

J1 

J2a 

J2 

Aux3 

J13 

J12 

JI1 

JI2 

JI3 

JI4 

JI7 

J7 

JI8 

JI9 

JI5 

J4 

J5 

J6 

J6 

J8 

J9 

J10 

J11 

O1 

J3 

JI7 

J2 

JI9 

JI6 

J7 

JI8 

JI2 

JI3 

JI4 

JI5 

JI2 

JI3 

JI4 

JI5 

Well 

109.00 

133.00 

207.00 

140.00 

95.00 

166.00 

320.00 

145.00 

89.00 

444.75 

185.39 

157.48 

529.22 

567.19 

377.76 

498.42 

150.36 

230.38 

578.27 

124.45 

10.65 

153.02 

32.88 

47.72 

100 

2.25 

3 

3 

3 

3.5 

3 

3 

3 

4.75 

3 

1.33 

1.5 

1.5 

1.67 

1.67 

1.67 

1 

1 

1.5 

1.5 

0.33 

0.66 

0.5 

0.5 

2 

0.016 

0.05 

0.05 

0.05 

0.016 

0.05 

0.05 

0.05 

0.016 

0.05 

0.016 

0.016 

0.016 

0.016 

0.016 

0.016 

0.016 

0.016 

0.016 

0.016 

0.016 

0.016 

0.016 

0.016 

0.016 

0 

5 

5 

5 

0 

5 

5 

5 

0 

5 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

5 

5 

5 

0 

5 

5 

5 

0 

5 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

5 

5 

5 

0 

5 

5 

5 

0 

5 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

5 

0 

0 

0 

0 

0 

6 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

4 

Table 8-3. Subcatchment outlets 

Subcatchment Outlet Node 

S1 J1 

S2 J2a 

S3 Aux3 

S4 J13 

S5 J12 

S6 J11 

S7 J10 

1

 Colors indicate whether the pipes belong to the stream (blue), the sewer pipes (green) or the
 

interceptor (brown)

2 h or d corresponds to the depth (Trapezoidal shape) or diameter (Circular shape)
 3 b corresponds to the bottom width (Trapezoidal shape)

4, 5 Z1 and Z2 correspond to the left and right slope (Trapezoidal shape) 

140 
C7 

S1 J2a 

S2 

S3 

S4 

S5 

S6 

S7 

C3 

C4 

C5 C6 

C8 

C9 

C10 

C11 

C_Aux3 

P1 

P2 

P3 

P4 

P5 

P6 

I1 

I2 

I3 

I4 

I9 

J1 

J2 

J3 

J4 J5 

J6 

J7 

J8 

J9 

J10 

J11 

Aux3 

J13 

J12 

JI1 JI2 

JI3 

JI4 

JI5 

O1 

Well 

Stream 

Sewer 

Interceptor 

Figure 8-7. Layout of the combined sewer system before adding regulators and pump 

Flow Regulators 

The flow regulator structures are the next elements to be represented in the model. 

Five regulators identified with the letter R will be used to control the flows from the five 

combined sewers (P1, P3, P4, P5 and P6) into the interceptor. These identifiers 

(R1,...,R5) are given only for reference purposes in the text; in the actual model 

regulators are not defined as elements directly, but rather through a combination of 

orifices, weirs and pipes (i.e., in the model there is no element named R1), as seen in 

Figure 8-6. The steps needed to create each of these regulators are as follows: (Note: it is 

recommended that SWMM’s Auto-Length feature be turned off so that conduit 

lengths are not altered as connections are made to the flow regulators.) 

Regulator R1: 

1. Place a new junction named JI6 somewhere between J4 and JI1. 

2. Change the downstream node of pipe P4 to JI6 (using the pipe’s Property Editor). 

3. Add a weir link W1 connecting JI6 to J4. 

4. Add a bottom orifice link O1 connecting JI6 to JI1. 

141 
Regulator R2: 

1. Place a new junction JI7 somewhere between J5 and JI2. 

2. Change the downstream node of pipe P1 to JI7. 

3. Add weir link W2 connecting JI7 to J5. 

4. Add a new pipe I5 connecting JI7 to JI2. 

Regulator R3: 

1. Add a new pipe I6 between J7 and JI3. 

Regulator R4: 

1. Place a new junction JI8 somewhere between J10 and JI4. 

2. Change the downstream end of pipe P6 to JI8. 

3. Add a weir link W3 that connects JI8 to J10. 

4. Add a pipe I7 connecting JI8 to JI4. 

Regulator 5: 

1. Place a new junction JI9 somewhere between J11 and JI5. 

2. Change the downstream node of pipe P3 to JI9. 

3. Add a weir link W4 that connects JI9 to J11. 

4. Add a pipe I8 that connects JI9 to JI5. 

The resulting layout of the combined system with the regulators added is shown 

in Figure 8-6. Note that adding the regulator junctions JI6, JI7, JI8, and JI9 required 

changing the discharge nodes of combined sewer pipes P4, P1, P6, and P3, respectively, 

from their original stream junctions to their respective regulator junctions. 

To complete the process of adding in the regulators, the properties of the new 

junctions (JI6, JI7, JI8, and JI9) must be set using the data from Table 8-1. The same 

holds true for the new interceptor pipes (I5, I6, I7, and I8) whose properties are listed in 

Table 8-2. The dimensions and offsets for the newly added weirs and orifices (W1, W2, 

W3, W4, and O1) are listed in Table 8-4. Note that for each weir, the sum of its inlet 

offset and its opening height is smaller than the depth of the corresponding inlet node, 

defined in Table 8-1. The discharge coefficient for each of the weirs is 3.3 and is 0.65 for 

the orifice. In addition to these newly added elements, it is necessary to set the inlet offset 

for stream channel C6 to 5 ft higher than the invert of junction J7 so that it can serve as 

an overflow diversion while the new pipe I6, with no offset, connects J7 to the 

interceptor (see Table 8-2) 

142 
Table 8-4. Properties of the regulator structures 

Flow 

regulator 

Sewer 

pipe 

controlled 

Inlet 

node 

Discharge into stream Discharge into interceptor 

ID Height 

(ft) 

Length 

(ft) 

Inlet 

offset 

Outlet 

node Type ID Diameter (ft) 

Outlet 

node 

R1 P4 JI6 W1 6.5 3 0.4 J4 Orifice Or1 0.5 JI1 

R2 P1 JI7 W2 5.5 5 0.33 J5 Pipe I5 See Table 8-2 

R3 P5 J7 C6 Pipe, see Table 8-3 Pipe I6 See Table 8-2 

R4 P6 JI8 W3 5 4 0.4 J10 Pipe I7 See Table 8-2 

R5 P3 JI9 W4 4.5 4 0.35 J11 Pipe I8 See Table 8-2 

JI13, 4970.4 ft O2, 4968 ft 

Well 

JI10, 4947 ft 

JI12, 4962.6 ft 

JI11, 4954.8 ft 

Pump1 

I10 

I13 

I12 

I11 

Fixed stage, 

4970 ft 

Pump Station and Force Main 

To complete the combined system model the pump station and force main must 

be added at the downstream end of the interceptor. As described earlier, node Well will 

serve as the wet well for the pump station. It is represented by a storage node with an 

invert elevation of 4945 ft, a maximum depth of 14 ft, an initial depth of 3 ft, and has a 

surface area of 300 ft2

 that remains constant over its entire height. To specify the latter, 

the Storage Curve entry in the node’s Property Editor is set to Functional, the 

Coefficient and Exponent entries are zero and the entry for the Constant field is 300. 

To make room for the force main on the study area map, the map’s dimensions 

must be expanded. Select View | Dimensions from the main menu bar. In the Map 

Dimensions dialog that appears enter -235.8, -70.2 for the Lower Left coordinate and 

1960.5, 1514.2 for the Upper Right coordinate. Do not select the “Re-compute all lengths 

and areas” option which will appear if the Auto-Length option is currently on. 

There should now be room to add a series of four junctions downstream of the 

wet well node that defines the path of the force main (JI10, JI11, JI12, and JI13) along 

with the final outfall node (O2) that represents the WWTP (see Figure 8-8). The invert 

elevations of these nodes are 4947.0, 4954.8, 4962.6, 4970.4, and 4968.0 ft, respectively. 

As explained in the sidebar “Defining a Force Main Pipeline” all of the junction nodes in 

the main are assigned zero maximum depth and a surcharge depth of 265 ft so that they 

can pressurize (to at least 115 psi) without flooding. The outfall O2 is of type Fixed, with 

a fixed stage elevation of 4970.0 ft. 

Figure 8-8. Force main line 

143 
Table 8-5. Properties of the force main line 

Pipe ID Shape Inlet Node1

 Outlet Node1 Length Diameter Rough. 

(ft) (ft) Coeff. 

Inlet Outlet

Offset (ft) Offset (ft) 

I10 Circular JI10 (4947 ft) JI11 500 2 0.016 0 0 

I11 Circular JI11 (4954.8 ft) JI12 500 2 0.016 0 0 

I12 Circular JI12 (4962.6 ft) JI13 500 2 0.016 0 0 

I13 Circular JI13 (4970.4 ft) O2 (4968) 500 4 0.016 0 0 

Defining a Force Main Pipeline 

The junctions used to connect sections of a closed 

force main together are typically welded or bolted fittings 

that do not allow water to escape the junction when it 

becomes surcharged. This type of junction can be 

modeled in SWMM by using a junction node whose 

maximum depth is zero and whose surcharge depth is set 

to an arbitrarily high number (such as the burst pressure 

of the main). Using a maximum depth of zero means that 

the actual depth will equal the distance from the node’s 

invert to the top of the highest connecting conduit. A high 

surcharge depth is required to allow the node to remain in 

a pressurized state without causing any flooding. 

Any of SWMM’s closed conduit shapes can be used for the cross-section of 

a force main, although circular pipes are most commonly used. SWMM also 

provides a special circular shape named Force Main which uses either the HazenWilliams or the Darcy-Weisbach formulas to compute friction losses during 

pressurized flow instead of the Manning equation as would otherwise be the case. 

Some engineers prefer to use one of the former two head loss formulas instead of 

the Manning equation for pipes that are known to have pressurized flow almost all 

of the time. In the current example, the force main consists of simple circular pipes 

and the Manning equation is used throughout to compute losses. 

After these nodes are created, a set of force main pipes I10, I11, I12 and I13 are 

added between nodes JI10, JI11, JI12, JI13, and O2, respectively (refer to Figure 8-8). 

The properties of these pipes are listed in Table 8-5. 

1

 Number in parenthesis indicates the invert elevation of the node. 

The final step is to add a pump link named Pump1 between the nodes Well and 

JI10. The pump curve (yet to be defined) associated with this pump is also named 

Pump1, the initial status is OFF, and the startup depth is 5 ft while the shutoff depth is 2 

ft. This means that the pump turns on when the water depth in the wet well reaches 5 ft 

and it shuts down when the depth drops to 2 ft. 

144 
Table 8-6. Pump curve data 

Head (ft) 11 12 13 14 15 16 17 18 19 20 21 22 23 24 

Discharge (cfs) 7.2 6.9 6.5 6.1 5.7 5.2 4.7 4.1 3.6 2.9 2.3 1.5 0.8 0 

Each pump added to a SWMM model is required to have a curve that defines how 

the pump’s discharge flow rate depends on the volume, depth or head added at its inlet 

(suction) side. This example will use a Type 3 pump curve where discharge varies 

inversely with the head (or lift) added by the pump between its inlet and outlet nodes. 

This type of curve provides the most realistic representation of how pumps actually 

behave and is usually available from the pump’s manufacturer. The head-discharge data 

that define the pump curve used here are listed in Table 8-6. To add this curve to the 

model: 

1. In the Data Browser, select the Pump Curve sub-category. 

2. Click the + button to bring up the Pump Curve Editor dialog. 

3. Enter Pump1 as the name of the curve and select Type3 as the type. 

4. Enter the Head-Discharge data from Table 8-6 into the grid on the form. 

Dry Weather Flows 

Wastewater flow from the sewersheds is added into the model using SWMM’s 

Dry Weather Inflow tool (see the sidebar “Adding Dry Weather Flows into SWMM”). 

This example assumes that the individual subcatchments in the model also represent the 

individual sewersheds. Only average daily dry weather inflows will be used to keep 

things simple. In reality, peak daily flows can be two to four times greater than the 

average. Therefore, if a more accurate analysis is required, a diurnal time pattern should 

be used to capture the full range of dry weather inflows. This, together with a continuous 

rainfall record, would allow one to simulate the dynamic performance of the system 

under all types of events. 

Typical per capita domestic wastewater generation rates vary between 40 gpd 

(gallons per day) for apartments and 150 gpd for luxury residences and estates (Nicklow 

et al., 2004). ASCE (1992) defines a range of average per capita domestic loading rates 

between 50 gpd and 265 gpd. Based on these ranges and an estimate of 3 to 5 inhabitants 

per lot, an average domestic loading rate per lot of 300 gpd is assumed. In addition to the 

domestic rates, the discharge rates from the commercial areas in subcatchments S5 and S6 

also need to be included. These are estimated to be 2850 gpd in subcatchment S5 and 

8100 gpd in subcatchment S5. The dry-weather flows for the subcatchments are then 

computed as the sum of the domestic loading rate and the commercial rate. Table 8-7 

summarizes this computation, showing the number of residential lots in each 

subcatchment (sewershed), the corresponding dry weather flows (in gpd and cfs) and the 

nodes that receive these inflows. Note that no dry weather flows are used in 

subcatchments S6 and S7 because they contain no residential or commercial lots. 

145 
Table 8-7. Summary of dry weather flows 

Subcatchment Node Number of 

residential lots 

Commercial dry 

weather inflow 

Dry weather Inflow 

gpd cfs 

S1 J1 17 - 5100 0.008 

S2 J2a 22 - 6600 0.010 

S3 Aux3 10 - 3000 0.004 

S4 J13 17 2850 5100+2850 0.0123 

S5 J12 - 8100 8100 0.0125 

S6 J11 - - 0 0 

S7 J10 - - 0 0 

0

Precipitation Data and Simulation Options 

The 0.23 inches storm defined previously in Table 5-1, Example 5, and both the 

2-year and 10-year storms will be used to evaluate the performance of the combined 

sewer system. The 0.23 in. storm is added to the model by creating a new time series 

called 0.23-in. with the corresponding values of time and intensity. Dynamic Wave flow 

routing with a time step of 15 s, a 1 minute wet weather runoff time step, a 1 hr dry 

weather runoff time step, a 1 minute reporting time step and a total duration of 12 hours 

will be used in all the simulations. All the information for the model has been 

summarized in Tables 8-1 to 8-7. The complete model input data can be found in the file 

named Example8.inp and the study area map should resemble that shown in Figure 8-9. 

C3 

C4 

C5 C6 

C7 

C8 

C9 

C10 

C11 

C_Aux3 

P1 

P2 

P3 

P4 

P5 

P6 

I1 I2 

I3 

I4 

I5 

I6 

I7 

I8 I9 

I10 

I11 

I12 I13 

Pump1 

Or1 

W1 W2 

W3 

W4 

J1 

J2a 

J2 

J3 

J4 J5 

J6 

J7 

J8 

J9 

J1 

J11 

J12 

J13 

Aux3 

JI1 JI2 

JI3 

JI4 

JI5 

JI6 JI7 

JI8 

JI9 

JI10 

JI11 

JI12 

JI13 

O1 

O2 

Well 

S1 

S2 

S3 

S4 

S5 

S6 

S7 

Figure 8-9. Final combined sewer system model layout 

146 
1 

0.9 

0.8 

0.7 

Q (cfs) 

0.6 

0.5 

0.4 

0.3 C_Aux3 C4 

0.2 C5 C7 

0.1 C10 C11

0 

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 

time (hh:mm) 

8.4 Model Results 

0.23 in. Storm 

The model is first run for the 0.23 in. storm event. Viewing the Link Flow 

Summary of the resulting Status Report shows that there is no flow in any of the links that 

divert water from the combined sewers into the stream (W1, W2, W3, W4 and C6). Thus 

no CSOs occur for this size storm. Figure 8-10 shows the flow through each channel of 

the stream. The only channel with any flow is C11 which receives only stormwater runoff 

(and no wastewater flow) from subcatchment S7. Flows in any other of the stream’s 

conduits would imply that CSOs are occurring somewhere in the system. 

Figure 8-10. Flow (Q) along sections of the stream for the 0.23 in. storm 

Figure 8-11 shows the flows through each section of the interceptor for the 0.23 

in. storm. Note how the peak discharges and volumes increase in the downstream 

direction (from I1 to I9) as the different combined sewer pipes discharge into the 

interceptor through the flow regulators, as illustrated in Figure 8-12. The latter figure 

shows that all the orifices and pipes that connect the combined sewers to the interceptor 

are contributing flows to the interceptor. In this figure, the first ID identifies the link of 

the regulator that carries the diverted flow; the second ID corresponds to the flow 

regulator to which it belongs. 

2-yr Storm 

Results obtained for the 2-yr storm (with a volume of 1.0 in.) are now presented. 

Figures 8-13 and 8-14 show the flows through the various stream and interceptor 

sections, respectively. Note that for this larger storm, flow occurs in all sections of the 

stream. The Link Flow Summary of the Status Report shows that CSOs occur and all the 

147
flow regulators start discharging flow into the stream once the capacity of diversion into 

the interceptor has been reached. The irregular fluctuations in flow through the 

interceptor seen in Figure 8-14 are caused by fluctuations in the flow pumped into the 

force main at the pump station. 

7.5 

Q (cfs) 

7 

6.5 

6 

5.5 

5 

4.5 

4 

3.5 

3 

2.5 

2 

1.5 

1 

0.5 

0 

I1 

I2 

I3 

I4 

I9 

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 

time (hh:mm) 

Figure 8-11. Flow (Q) along sections of the interceptor for the 0.23 in. storm 

2.5 

2.25
 

2
 

1.75 

1.5 

Or1, R1 I5, R2 

I6, R3 I7, R4 

I8, R5 

0:00 1:00 2:00 3:00 4:00 5:00 6:00 

time (hh:mm) 

Q (cfs) 1.25 

1 

0.75 

0.5 

0.25 

0 

Figure 8-12. Flow (Q) diverted from each regulator to the interceptor for the 0.23 in. storm 

148 
Q (cfs)

22 

20 

18 

16 

14 

12 

10 C_Aux3 C4 

8 C5 C7 

6 C10 C11

4 

2 

0 

0:00 1:00 2:00 3:00 4:00 

time (hh:mm) 

10 

I1 

I2 

8 I3 

I4 

6 

I9

Q (cfs) 

4 

2 

0 

0:00 1:00 2:00 3:00 4:00 

time (hh:mm) 

Figure 8-13. Flow (Q) along sections of the stream for the 2-yr storm 

Figure 8-14. Flow (Q) along the sections of the interceptor for the 2-yr storm 

Figure 8-15 compares the flows that are diverted into the interceptor and to the 

stream CSO for flow regulators R1 and R4. The interceptor diversions are from orifice 

Or1 and conduit I7, while the CSO discharges are from weirs W1 and W3. The regulators 

are able to convey the discharges into the interceptor for a while, but at a certain point the 

maximum capacity is reached and a CSO occurs. Note that the durations of CSOs are 

149
smaller than those of the discharges into the interceptor; however, the peak discharge is 

larger. 

0 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

Q (cfs) 

R1, flow to interceptor 

R1, flow to stream 

R4, flow to interceptor 

R4, flow to stream 

0:00 1:00 2:00 3:00 4:00 5:00 6:00 

time (hh:mm) 

Figure 8-15. Flows (Q) in regulators R1 and R4 for the 2-yr storm 

Pump Station Behavior 

Figure 8-16 shows how the pump in this combined system behaves under the 0.23 

in. event. Part (a) of the figure plots the water depth in the pump’s wet well and part (b) 

shows the pump’s discharge flow rate. The startup and shutoff depths are shown with 

dashed lines. At the start of the simulation the water depth is 3 ft and the pump is initially 

off (Point 1). The pump turns on once the startup depth of 5 ft is reached (Point 2). Inflow 

to the pump station is large enough so that the pump continues working and the wet well 

water depth stays above the shutoff level. The water depth eventually reaches a maximum 

(Point 3) and then starts decreasing until reaching the 2 ft shutoff depth at which time the 

pump stops operating (Point 4). After the runoff flow ceases some 2+ hours into the 

simulation, only wastewater flows are received at the wet well, and the water depth 

increases slowly again until reaching the startup depth (Point 5); the pump turns on but 

rapidly stops when the shutoff depth is reached (Point 6). From hereafter pumped 

discharges fluctuate between the startup and shutoff limits 

150 
Depth (ft) 

8.0 

7.5 

7.0 

6.5 

6.0 

5.5 

5.0 

4.5 

4.0 

3.5 

3.0 

2.5 

2.0 

1.5 

1.0 

0.5 

0.0 

1 

2 

4 

5 

6 

(a) 

3 

0 2 4 6 8 10 12
 

Elapsed Time (hours)
 

8.0 

Flow (CFS) 

7.0 

6.0 

5.0 

4.0 

3.0 

2.0 

1.0 

0.0 

5 6 

3 

(b) 

0 2 4 6 8 10 12
 

Elapsed Time (hours) 

1 2 4 

Figure 8-16. Pump behavior for the 0.23 in. storm: (a) wet well water depth, (b) pump flow 

151
 
Table 8-8. Summary of system performance for different storm events 

Node ID 0.23 in. 2-yr (1.0 in.) 10-yr (1.7 in.) 

Max. wet well water depth (ft) 5.35 13.49 13.86 

Max. interceptor pump flow (cfs) 7.2 7.2 7.2 

Max. flow at stream outfall O1 (cfs) 0.88 20.02 45.65 

Max. overflow at regulator R1 (cfs) 0 3.11 5.92 

Max. overflow at regulator R2 (cfs) 0 5.88 8.76 

Max. overflow at regulator R3 (cfs) 0 7.13 13.44 

Max. overflow at regulator R4 (cfs) 0 9.35 13.44 

Max. overflow at regulator R5 (cfs) 0 6.60 8.72 

Overall Performance 

Table 8-8 compares the main results for the 0.23 in., 2-yr, and 10-yr storms. No 

CSOs occur for the 0.23 in. storm and all the wastewater flow is diverted into the 

interceptor. For the 2- and 10-yr storms, all the regulators are releasing discharges into 

the stream. Note how the occurrence of CSOs is reflected in the large increase in peak 

discharge at the receiving stream outfall O1. The peak discharge changes from 0.88 cfs 

for the 0.23 in. storm to 20.02 cfs for the 2-yr storm and 45.65 cfs for the 10-yr storm. 

Table 8-8 also shows that the maximum discharge conveyed by the interceptor barely 

changes with the magnitude of the storm once all the regulators are discharging CSOs to 

the stream. The maximum water depth in the wet well is practically the same for the 2- 

and 10- year storm. This result clearly shows that flow regulators work in a way such that 

all the flows above the diversion capacity are directly discharged into the water body. 

8.5 Summary 

This example showed how to model a combined sewer system, composed of 

combined sewer pipes, flow regulators, a pump station and a force main line, within 

SWMM. The resulting model was used to determine the occurrence of Combined Sewer 

Overflows (CSOs) under different size storm events. The key points illustrated in this 

example were: 

1.	 The main components of a combined sewer system model are pipes that carry both 

dry weather sanitary and wet weather runoff flows, flow regulators that divide flow 

between an interceptor pipe and a CSO outfall, and, if required, pump stations that 

carry interceptor flows to a treatment facility through a force main. 

2.	 Continuous wastewater flows, which can vary periodically by time of day, day of 

week, and month of the year, are directly added into nodes associated with collector 

sewers that service individual sewersheds. 

3.	 Flow regulators can be represented using a combination of pipes, orifices and weirs. 

The best way to model these regulators will depend on local conditions in the 

combined sewer system under analysis. 

4.	 A pump station can be modeled using a storage unit node to represent the wet well 

that connects a pump link to the inlet node of a force main. The operation of the pump 

152 
is defined through a pump curve and a set of wet well water levels that determine 

when the pump starts up and shuts down. 

5.	 A force main line can be defined by using a set of pipes between junction nodes that 

are assigned a high surcharge depth so that flooding does not occur when the main 

pressurizes. 

6.	 By examining a number of design storms (or by running a continuous simulation as 

described in the next example) one can determine the frequency at which combined 

sewer overflows will occur. In this particular example, the 0.23 in. storm produced no 

overflows while the 2-yr and 10-yr storms did. As shown from an analysis of the 

rainfall record for this site made in Example 9, roughly 1 in 4 storms is larger than 

0.23 in. and would thus have the capability to result in a CSO. 

153 
Example 9. Continuous Simulation 

This example shows how to run a continuous simulation with SWMM using a 

long-term rainfall record. It will analyze the performance of the drainage system and 

BMP detention pond for the 29 acre residential site designed in Example 3. The multipurpose pond was designed to detain a water quality capture volume (WQCV) and 

control peak post-development release rates to their pre-development levels for the 2-yr, 

10-yr and 100-yr design storms. This model will be re-run using a set of monthly average 

evaporation rates and a continuous precipitation record, so that its behavior over a 10­

year period can be studied. The use of SWMM’s Statistics tool for analyzing the results 

of a continuous simulation will also be demonstrated. Because it only takes a few steps to 

set up Example 3 for a continuous simulation, the bulk of this chapter will focus on 

analyzing the results produced by the simulation. 

Continuous simulation is important because it allows actual historic data to be 

used to analyze the performance of drainage systems and their components. Drainage 

systems are typically designed using synthetic design storms. These single event design 

storms do not take into account varying patterns of rainfall duration and intensity, 

variation of time between storms, changing antecedent soil and storage conditions within 

the watershed, and the effect of evaporation. Continuous simulation considers all of these 

factors and allows for a more accurate and robust comparison of the long-term water 

balance and hydrologic performance of alternative stormwater management scenarios. 

9.1 Problem Statement 

Figure 9-1 shows the drainage system model developed in Example 3 for a new 

residential development on a 29 acre site. The system includes a BMP detention pond 

(SU1) that was designed to provide a water quality capture volume for the more 

frequently occurring small storms and also provide peak runoff control for the 2-, 10- and 

100-yr design storms of 2-hr duration. In this example the site will be analyzed using 

continuous rainfall records from the city of Fort Collins, CO that were downloaded from 

the National Climatic Data Center (NCDC) along with a set of monthly average 

evaporation rates (in/day). The performance of the conveyance system and the detention 

pond will be studied over the ten year period of 1968 to 1978. The results of the 

simulation will be analyzed with regard to the following questions: 

•	 Was the flow target used to design the detention pond adequate? 

•	 How significant is evaporation within the overall system water balance? 

•	 How significant are antecedent conditions in affecting system behavior? 

•	 How effective is the detention pond in reducing peak discharges? 

•	 How effective is the pond in capturing the majority of runoff events within its 

water quality control volume? 

154 
• What statistical properties of the rainfall record set it apart from the design storms 

used previously? 

Figure 9-1. Drainage system and detention pond (SU1) designed in Example 3 

9.2 System Representation 

Continuous or long term simulation involves the simulation of multiple events 

over a continuous period of months to years. In single-event simulation the rainfall record 

is first analyzed separately to create an Intensity-Duration-Frequency (IDF) curve from 

which design storms can be chosen; these design storms have a specific duration and 

return period (e.g. the 2-hr 10-yr design storm) and are used within SWMM to generate a 

single runoff hydrograph for design. In comparison, continuous simulation applies a long 

term record of rainfall directly within SWMM to generate a long-term record of 

simulated runoff; statistical analysis is then run on this generated record to characterize 

the long-term performance and achieve a final design. It is advantageous to use 

continuous simulation because it accounts for antecedent soil conditions and other initial 

values of variables, such as the initial water level in storage units, which affect the 

response of the drainage system to individual storm events. It also allows the 

155 
representation of actual storm events of varying magnitudes, durations, and occurrence 

intervals. The main disadvantages of continuous simulation are the additional 

computation time required and the lack of high quality, long-term rainfall records for 

many locations. 

Rainfall 

SWMM can utilize long-term rainfall data stored in external files. The program 

recognizes several different file formats for these data: (1) the National Climatic Data 

Center (NCDC) DSI-3240 format for hourly rainfall and the DSI-3260 format for 15 min 

rainfall (both available from www.ncdc.noaa.gov/oa/ncdc.html), (2) HLY03 and HLY21 

formats for hourly rainfall and the FIF21 format for 15 min rainfall at Canadian stations, 

available from Environment Canada (EC) at www.climate.weatheroffice.ec.gc.ca, and (3) 

a standard user-prepared format as described in the SWMM Users Manual. The quality 

and quantity of the record will vary from station to station, but it is unusual to find long 

precipitation records with no missing or incorrect data. It is very important to check the 

quality of records before using them. 

Evaporation 

Single event simulations are usually insensitive to the evaporation rate. Thus, 

evaporation is typically neglected when a single rainfall event or a synthetic storm is 

simulated. However, this process is more significant when a continuous simulation is 

performed because it is through evaporation that depression storage is recovered and 

water levels in extended detention and wet ponds are reduced; thus it becomes an 

important component of the overall water budget. Several options are available for 

representing evaporation data in SWMM, including: (1) a single constant value, (2) 

historical daily average values stored in an external file, (3) a time series when high 

temporal resolution is available, and (4) monthly averages. Evaporation data are supplied 

on the Evaporation page of SWMM’s Climatology Editor. 

Although conceptually evaporation should also affect the recovery of infiltration 

capacity within the pervious areas of the watershed, SWMM’s infiltration models do not 

explicitly take it into account. Instead, they employ simple empirical functions for this 

purpose. The Horton infiltration model, used in the examples throughout this manual, 

employs an exponential function to restore infiltration capacity during dry periods. The 

rate coefficient in this function is inversely proportional to the soil’s drying time, i.e., the 

number of days it takes a saturated soil to drain completely. A drying time of 7 days is 

used for the site being analyzed, which is a typical value for the silt loam soil that is 

assumed to cover the site (see Example 1). 

156 
How to Load a Continuous Rainfall File into SWMM 

A continuous precipitation record can be supplied to SWMM by using an 

external file as the data source. What follows are the steps used to identify such a 

file to SWMM. 

1.	 Open the Property Editor of the Rain Gage that will use the rainfall data and 

select FILE as the Data Source. 

2.	 Click the ellipsis button in the File Name field. Navigate through your files and 

select the file containing the continuous rainfall data. 

3.	 If the file is in the User-Prepared format then the Rain Format and the Rain 

Interval of the data in the file must be specified in the Property Editor. For data 

from NCDC or EC files, SWMM automatically determines the appropriate rain 

format and rain interval to use, and will override any values specified for these 

properties in the editor. 

4.	 Provide an entry for the Station ID field in the Property Editor. For NCDC and 

EC files any identifier can be used – it need not be the station ID used in the 

file. However for User-Prepared files it must correspond to an ID that appears 

in the file since these files can contain data for more than one station. 

5.	 If a User-Prepared rainfall file is being used then the correct Rain Units for the 

rain depths in the file (inches or millimeters) must be specified. For NCDC and 

EC data files this property is determined automatically. 

6.	 Finally, specify the desired start and end analysis dates in the Simulation 

Options Editor based on the rainfall record. These dates must fall within the 

period of record. Time periods that fall outside those contained in the rainfall 

file will have no rainfall associated with them. 

The Rain Gage Property Editor for Example 9 is shown in the figure below. 

Note that the entry in the File Name property will be different depending on where 

you installed the rainfall file for this example on your computer’s file system. 

157 
Statistical Tools 

The large amount of output produced by a continuous simulation requires 

statistical tools to analyze it in a concise and meaningful manner. SWMM provides an 

interactive statistical query tool that can be applied to any output variable associated with 

any specific object (subcatchment, node, or link) or the system as a whole. The tool 

performs the following steps when analyzing the statistics for a specific output variable: 

•	 It first segregates the simulation period into a sequence of non-overlapping events 

either by day, month, year or cluster of consecutive reporting periods. The occurrence 

of these events is defined by the following minimum threshold values: 

	 Analysis Variable Threshold - the minimum value of the variable under 

analysis that must be exceeded for a time period to be included in an event. 

	 Event Volume Threshold - the minimum flow volume (or rainfall volume) that 

must be exceeded for a result to be counted as part of an event. 

	 Separation Time - the minimum amount of time 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 events formed from consecutive 

reporting periods, not to daily, monthly or annual event periods. 

•	 It then computes a user-specified event statistic for the analysis variable over all 

reporting time periods that fall within each event period. This could be the event 

mean value, the peak value, the total volume, etc. Thus each event is characterized by 

a single value for whatever variable is being analyzed. 

•	 Summary statistics for the event values over the entire set of events are then 

computed. These statistics include the maximum, minimum, mean, standard deviation 

and skewness. 

•	 Finally a frequency analysis for the collection of event values is performed. The 

events are rank ordered by value in a table that lists the event’s date, its duration, its 

event value, its cumulative exceedance frequency, and estimated return period. A 

histogram of event values and a cumulative frequency plot of these values are also 

produced. 

As an example, a typical query might ask SWMM to segregate the output record 

of flows discharged from a particular outfall into periods where the flow is above 0.05 cfs 

and there are at least 6 hours between events, and compute the summary statistics and 

frequency distribution of the peak flows within these events. 

158 
Table 9-1. Monthly evaporation for Fort Collins, CO (Source: Western Regional Climate Center) 

J F M A M J J A S O N D 

Monthly average pan 

evaporation (in) 0.00 0.00 2.5 4.52 5.42 6.32 6.92 6.07 4.74 3.07 1.48 0.00 

Monthly average 

corrected (in) 0.00 0.00 1.75 3.16 3.79 4.42 4.84 4.25 3.32 2.15 1.04 0.00 

Monthly average rate 

(in/day) 0.00 0.00 0.06 0.11 0.12 0.15 0.16 0.14 0.11 0.07 0.03 0.00 

9.3 Model Setup 

Only three steps are required to convert the SWMM input file for Example 3 

(Example3.inp) into one that can be used for continuous simulation. These are: 

1. Add evaporation data: 

In this example evaporation is supplied as monthly averages in units of in/day. 

Table 9-1 shows the monthly averages for the city of Fort Collins that are used in this 

example; the values were obtained from the Western Regional Climate Center 

(www.wrcc.dri.edu/htmlfiles/westevap.final.html#colorado). The first row shows the 

total monthly pan evaporation in inches. These amounts are adjusted in the second row 

by multiplying them by 0.70 to more closely estimate the evaporation from naturally 

existing surfaces, as proposed by Bedient and Huber (2002). Finally, the third row shows 

the daily rates obtained by dividing the monthly totals by the number of days in each 

month. Note that total values from December to February are 0.00. Typically this means 

that the station does not measure pan evaporation during these months. The values in the 

last row are entered on the Evaporation page of SWMM’s Climatology Editor. 

Evaporation from the surface of the site’s detention pond should also be 

accounted for. To do this, open up the Property Editor for the storage unit node SU1 and 

enter a value of 1.0 for the Evap. Factor property. 

2. Specify a rainfall file: 

The 30-year hourly rainfall record provided for Fort Collins is linked into the 

model as explained in the sidebar “How to Load a Continuous Rainfall File into SWMM”. 

The name of this file is Record.dat. Because this file is from the NCDC and adheres to 

the DSI-3240 format there is no need to alter the Rain Format, Rain Interval, or Rain 

Units properties of the model’s single rain gage. The Station ID property can be set to the 

ID associated with the data’s recording station which is 053005. The period of record for 

these rain data extends from 1949 to 1979, but only the 10 year period from 1968 to 1978 

will be simulated. Figure 9-2 shows the precipitation record for this period of time. There 

are many factors to consider when selecting a sub-period of a long-term record, such as 

the quality of the data it contains and how representative it is of both the overall record 

and of current rainfall patterns. 

159 
Figure 9-2. Ten year rainfall record for Fort Collins, CO (Source: National Climatic Data Center) 

3. Revise the simulation options: 

Finally it is necessary to change some of the original simulation options so that 

the correct period of rainfall record is simulated and a manageable amount of output is 

generated. Using the Dates page of the Simulation Options dialog, both the simulation 

start date and reporting start date are set to 01/01/1968. The simulation ending date is set 

to 01/01/1978. Next the following changes are made on the Time Steps page of the 

dialog: reporting step = 15 minutes, wet weather runoff step = 15 minutes, dry weather 

runoff step = 6 hours, and routing step = 60 sec. Note that these time steps are longer than 

those used in most of the previous examples. This is done to cut down on the amount of 

time needed to run the simulation and on the amount of output results that are produced. 

After making these changes the modified input file should be named 

Example9.inp. Running this model will take about three to five minutes on a 2.41 GHz 

computer. Most of this time is consumed by the flow routing computations. In general, 

the run time will depend on the complexity of the watershed being modeled, the routing 

method employed and the size of the routing time step used. The larger the time steps, the 

faster the simulation but the less detailed the results. If accurate simulation of peak flows 

on small watersheds is desired, then smaller time steps must be used. One way to 

determine the proper time step is to simulate a single event at different time steps, then 

choose the longest time step that produces the desired resolution in the hydrograph but 

still produces a stable solution with acceptable continuity error. 

160 
The run time for this example could be cut in half if Kinematic Wave routing were 

used instead of Dynamic Wave routing. This is a viable alternative for long-term 

simulations if one is willing to ignore possible backwater effects and pressurized flows, 

and if the drainage network is not bifurcated. SWMM also has another feature that can 

possibly reduce run times. This is the Skip Steady Periods option that appears on the 

General page of the Simulation Options dialog. When this option is used the simulation 

skips over periods of time when there is no runoff and no changes in flow. The criteria 

used to determine when such periods exist are quite stringent, and for this example it 

resulted in a negligible savings in run time. 

9.4 Model Results 

General Results 

SWMM’s Status Report summarizes overall results for the 10-yr simulation. The 

runoff continuity error is -0.412 %, the flow routing continuity error is –1.557 %, and no 

flooding occurred within the conveyance network (listed as Internal Outflow in the Flow 

Routing Continuity section of the report). This is expected because the conveyance 

system in Example 3 was designed for the 100-yr storm. The Runoff Quantity Continuity 

table shows the significance of evaporation in the total water budget. Almost 20 inches of 

water were evaporated from the depression storage surfaces of the catchment with 

another 1.2 inches evaporated from the pond; this corresponds to 19.2 % of the total rain 

over the 10 years (110.35 inches). 

Detention Pond 

The Status Report section “Node Inflow Summary” shows that the maximum flow 

rate into the detention pond (SU1) was 31.7 cfs. The outflow from the pond never 

exceeded 8.75 cfs (as determined by the maximum inflow for junction J_out in the same 

table). This control occurs over a period of 37 minutes, given that the maximum inflow to 

the pond was at 12:02 AM of day 2781, while the maximum discharge was at 12395 AM 

of the same day. Note that the maximum flow entering the pond is much lower than the 

initial estimate for the 10-yr storm computed in Example 3, 62.1 cfs. Interestingly, 

however, the maximum discharge released by the pond in the continuous simulation (8.48 

cfs) is somewhat larger than 7.34 cfs, the 10-yr peak discharge target used in Example 3. 

In other words, even though the peak flow entering the pond during the 10 year record is 

lower than the design value, the peak outflow is actually larger than its original design 

value. 

To explain this result, consider Figure 9-3 which shows the rainfall hyetograph 

for the storm event that produced the maximum inflow and outflow from the pond. The 

volume of rain that falls in the first two hours is 1.83 in. This is larger than the 1.71 in 

associated with the 10-yr 2-hr design storm used in Example 1, yet the inflow rate into 

the pond is smaller (31.7 cfs versus 62.1 cfs). The main reason for this discrepancy is the 

different rainfall interval used for the two storm events. The 10-yr design storm used a 5 

161 
minute interval and its maximum intensity was 4.87 in/hr (see Figure 1-6 in Example 1); 

in contrast, the rain interval for the storm from the continuous record is only 1 hr and its 

maximum intensity was 1.47 in, 30 % of the maximum intensity of the design storm. 

0 

1.47 

0.36 

0.24 

0.03 0.02 0.01 

0 

0.2 

0.4 

0.6 

0.8 

1 

1.2 

1.4 

1.6 

in/hr 

22:4523:0023:1523:3023:45

0:000:150:300:451:001:151:301:452:002:152:302:453:003:153:303:454:004:154:304:455:005:155:305:456:00 

time (hh:mm) 

Figure 9-3. Rainfall event producing the largest flow rates to the detention pond 

This difference explains the considerably smaller peak runoff discharged into the 

pond for the continuous simulation. The aggregation associated with larger rainfall 

intervals is a critical issue in continuous simulation that affects the performance of the 

model significantly. Peak discharges are very sensitive to high rainfall intensities, which 

typically occur in short periods of time. These high intensities are lost when data are 

aggregated in larger time steps, and the peak discharges are not well simulated. It is 

strongly recommended to use rainfall records with fifteen-minute or less time resolution, 

if available. 

The difference in maximum intensities does not impact the peak discharges 

released by the detention pond. As previously mentioned, the highest peak flow 

discharged by the pond in the continuous simulation was 8.75 cfs, slightly higher than the 

7.34 cfs peak produced from the 10-yr design storm. This is consistent with the fact that 

the storm associated with the continuous simulation peak is larger than the 10-yr design 

storm. The attenuation effect of the pond through time is such that the rainfall intensity is 

not as significant as the volume. 

162 
Antecedent Conditions 

One of the benefits of continuous simulation is that the model accounts for the 

initial state of the catchment and its conveyance network at the beginning of each new 

storm event. For instance, with continuous simulation the model simulates the initial 

water depth in the detention pond at the beginning of a new rainfall event. A high water 

depth will reduce the volume available for controlling the next storm, so that the 

discharges released will be larger than for the case where the pond is empty at the start of 

the storm. 

Figure 9-4 shows the water depth in the pond over a period of 8 days, from day 

3061 to day 3069 (from 5/19/1976 to 5/26/1976). Figure 9-5 shows the inflow and 

outflow rates for the pond over the same period of time. Rainfall is also included in both 

plots. Two storm events separated by 4 dry hours are shown: Event 1 has a maximum 

intensity of 0.24 in/h and a total volume of 0.41 in.; Event 2 has a maximum intensity of 

0.08 in/h and a total volume of 0.33 in. Despite the smaller volume and intensity of the 

second storm, the water depth in the pond reaches 1.33 ft, which is larger than the water 

depth reached with the first event, 1.17 ft. Because of the short dry time in between the 

two events, the water level in the storage unit has only descended to a depth of 0.80 ft 

when the next event stars. The storage available to control the second event is such that 

the smaller peak inflow produced by the second event, 1.25 cfs is controlled to a peak 

outflow of 0.43 cfs, while the larger peak inflow produced by the first event, 3.91 cfs, is 

controlled to an outflow of only 0.39 cfs. 

0 

0.2 

0.4 

0.6 

0.8 

1 

1.2 

1.4 

1.6 

1.8 

2 

Depth (ft) 

0 

0.05 

0.1 

0.15 

0.2 

0.25 

0.3 

0.35 

0.4 

0.45 

0.5 

Rain intensity (in/h) 

Rainfall 

Water depth 

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00 

Time (hh:mm) 

Figure 9-4. Water depth in the detention pond between days 3061 and 3069 

163 
5 

4.5 

4 

3.5 

3 

2.5 

2 

1.5
 Rainfall 

Discharge entering into Storage Unit 

Discharge released by Storage Unit 

0.5 0.45 

0 0.5 

0 

0.05 

0.1 

0.15 

0.2 

0.25 

0.3 

0.35 

0.4
 

Rain intensity (in/h) 

Q (cfs) 

1
 

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00 

Time (hh:mm) 

Figure 9-5. Inflow and outflow (Q) for the detention pond between days 3061 and 3069 

Evaporation 

Finally, another advantage of continuous simulation is the inclusion of 

evaporation in the overall system water balance. Evaporation from both the pervious and 

impervious depression storage areas takes place between rain events. Thus, the amount of 

depression storage available to capture the initial portion of the next storm depends on the 

interval between storms. As an example, Figure 9-6 shows the rainfall and losses 

(infiltration plus evaporation) simulated in subcatchment S1 over the period of time from 

5/19/1976 to 5/26/1976. It is seen that after large events, and once infiltration has 

stopped, the losses stabilize at 0.0021 in/h. These losses are caused by evaporation acting 

over the water stored on the impervious area. To confirm this, consider that the average 

evaporation rate in May is 0.12 in/day or 0.005 in/h; the percent imperviousness of 

subcatchment S1 is 56.8%, and 25% of that area does not have depression storage. 

Therefore, evaporation acts over 0.568 • (1-0.25) = 42.6% of the total area, and so the 

loss rate over the entire subcatchment S1 equals 42.6% • 0.12 in/day = 0.0021 in/hr, the 

same as the loss rate shown in Figure 9-6. 

164 
0 

0.025 

0.05 

0.075 

0.1 

0.125 

0.15 

0.175 

0.2 

0.225 

0.25 

(in/h) 

Losses 

Rainfall 

0.0021 in/h 

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00

12:00

0:00 

Time (hh:mm) 

Figure 9-6. Losses for subcatchment S1 between days 3061 and 3069 

Detention Pond Outflows 

To illustrate the use of SWMM’s Statistics tool, a frequency analysis of the peak 

outflows from the site’s detention pond will be made. The analysis will show how often 

and for what periods of time the pond has a certain discharge and how the magnitudes of 

the peak discharges during these periods are distributed. To begin, one first opens the 

Statistics Selection dialogue by clicking the Statistics icon (∑) on SWMM’s main toolbar 

or by selecting Report | Statistics from the main menu bar. 

Figure 9-7 shows how the dialog should be filled in for this particular query. The 

object to be analyzed is node J_out since it directly receives the outflow that exits the 

pond from each of its outlet devices. The variable to be analyzed for this node is Total 

Inflow. The time period used to define events is Event-Dependent, meaning that 

separate events will be defined by consecutive reporting periods where certain event 

threshold conditions are met. Within each such event period, the statistic to be analyzed is 

the Peak value of total inflow to the node (which is equivalent to the peak pond 

discharge through all of its outlet structures). And finally, the threshold criteria state that 

a new event begins whenever an inflow of at least 0.005 cfs occurs at least 6 hours after 

the last inflow of at least this amount was recorded. The selection of these values will 

affect how many events are counted. In general, larger values of the minimum flow or 

larger values of the time of separation will produce a fewer number of events. 

165 
Figure 9-7. Statistics Selection dialog for analyzing peak pond outflows 

The report generated by running this statistical query contains four sections as 

shown in Figures 9-8 through 9-11. The first section is the Summary Statistics, shown in 

Figure 9-8. According to this summary, 295 events were identified in the record based on 

the thresholds values for flow and inter-event time defined for the frequency analysis; 

these events comprise 13.7 % of the total simulation time. Note the high positive 

skewness coefficient (4.93) which implies a large number of low discharges and few 

large ones. This is confirmed by the small value of the mean peak flow, 0.4 cfs. 

Figure 9-9 shows a portion of the second section of the report, the Event Listing 

for the variable under study. The events are listed in order of decreasing value of the 

event statistic (the peak value) for the variable being analyzed (total inflow rate at node 

J_out). Five fields are included: Start date of the event, duration, value of the variable 

under study (in this case peak flow), the exceedance frequency and an estimation of the 

corresponding return period. Note the length of the events listed in this table; the majority 

of them last longer than 24 hours. This shows that discharges are released quite slowly 

from the pond, as expected based on its design criteria. Moreover, a similar frequency 

analysis for duration instead of the peak discharge would show that the mean event 

duration is 40.7 hours. 

166 
 

Figure 9-8. Summary statistics for peak inflow to node J_out (same as peak pond outflow) 

Figure 9-9. Event listing of peak inflow to node J_out (same as peak pond outflow) 

167
 
 

 

 

Figure 9-10. Histogram of peak inflow to node J_out (same as peak pond outflow) 

Figure 9-11. Cumulative frequency of peak inflow to node J_out (same as peak pond outflow) 

The exceedance frequency and return period displayed in the Event Listing are 

both computed using the Weibull formula for plotting position. Therefore, for a specific 

event the exceedance frequency F and the return period in years T are calculated using 

the following equations: 

m F = (9-1)

nR +1 

168 
 n +1 T = (9-2)

m 

where m is the event’s rank, nR is the total number of events and n is the number of years 

under analysis. For example, for the 4th event occurring on 05/23/1971, the exceedance 

frequency is equal to F4 = 4 / (295 + 1) = 0.0135= 1.35 %, and the return period is equal 

to T4 = (10 + 1)/4 = 2.75 years. 

The event listing also shows that during the 10 years of simulation there were 2 

events where the peak discharge was greater than the 7.34 cfs value that was computed in 

Example 3 when the model was run with the 10-yr design storm. This small discrepancy 

likely reflects the fact that the 10 years of record used here is only one of 29 different 

consecutive 10-year sequences that could have been selected from the 30 years worth of 

rainfall data available. 

The third section of the Statistics report contains a histogram of the event statistic 

being analyzed, as shown in Figure 9-10. For this particular example it shows what 

fraction of all the events had a peak flow of a given size. Note how the figure confirms 

what was said earlier, that the distribution of peak inflows is highly skewed towards the 

low end of the flow scale. Finally, the fourth section of the report, as shown in Figure 9­

11, presents a cumulative frequency plot of the event statistic under study. In this 

particular example, only 10 % of the peak discharges over the 10-yr period exceed 0.5 

cfs, and only 6 % exceed 2 cfs. Note that both the histogram and cumulative frequency 

plots are just graphical representations of the same information as provided in the event 

listing. 

Detention Pond Water Depth 

A second application of the SWMM Statistics tool to this example will analyze 

the maximum depth in the detention pond. This will help verify if the Water Quality 

Capture Volume (WQCV) of the pond was effective in capturing the more frequently 

occurring storms. Recall from Example 3 that the first 1.5 feet of storage volume was 

designated for this purpose. The statistical query used to answer this question is shown in 

Figure 9-12. Note that this time events are defined to consist of all days where the water 

depth in the pond was at least 0.05 ft deep. The “Daily” option is chosen for the Event 

Period because the drawdown time for the WQCV is 40 hours; thus a daily analysis of 

the depth in this portion of the pond is sufficient. Figure 9-13 shows the frequency plot 

that results from this query. On only 7 % of the days when the pond is wet does its depth 

exceed the WQCV. Thus, one can conclude that the large majority of all storms are 

captured within the WQCV and the pond will function as an effective BMP control. 

169 
 

100
 

90
 

80
 

70
 

60
 

50
 

40
 

30
 

20
 

0 

0 0.5 1 1.5 2 2.5 3 3.5 

Daily Peak Depth (ft) 

Exceedance Frequency 

10 

Figure 9-12. Statistical query for daily peak water depth in the detention pond 

Figure 9-13. Frequency plot of daily peak water depth in the detention pond 

170 
Rainfall Statistics 

Another variable typically analyzed using statistics is rainfall. Several quantities 

that characterize storm events for the rainfall record used in this example will be 

examined and compared. These are the event duration, mean intensity, total volume, and 

peak intensity. As before, the record will be separated into a sequence of independent 

storm events of varying magnitude and duration using SWMM’s Statistic tool. Note that 

a rainfall analysis can be made without having to run a complete runoff/routing 

simulation for the entire SWMM model. See the sidebar “Analyzing Stand-Alone Rainfall 

Files with SWMM” for details on how to do this. 

Analyzing Stand-Alone Rainfall Files with SWMM 

Modelers often have a need to statistically analyze a long-term rainfall 

record independently of using it within a particular SWMM model. For example, 

one might want to identify a sub-period of the record that is representative of the 

entire record or identify particular events, extreme or otherwise, that could be used 

for single event analyses. It is quite simple to set up a general SWMM project for 

just this purpose and run it independently for any rainfall file. The steps involved 

are as follows: 

1.	 Create a new project with SWMM that consists of just a single subcatchment 

and associated rain gage and set the outlet of the subcatchment to itself. 

2.	 Save the project with a meaningful name, such as RainStats.inp. 

3.	 Whenever a rainfall file needs to be analyzed, launch SWMM and open this 

special project. (Note that a new SWMM session can be launched while 

other SWMM sessions are still active). 

4.	 Edit the Rain Gage to use the file of interest (remembering to enter 

appropriate values for the Rain Format, Rain Interval, Station ID, and Rain 

Units if a file with the User-Supplied format is being used). 

5.	 Edit the Dates in the Simulation Options dialog to cover the period of 

interest within the rainfall file. Also set the Reporting and Wet Runoff time 

steps to be the same as the Rain Interval used for the rainfall data. 

6.	 Run a simulation and then use the Time Series Graph, Tabular Report, and 

Statistics tools to analyze the System Rainfall variable. 

Regarding the final step of this process, time series plots are useful for 

providing an overall picture of how rainfall varies within a period of several years 

or months, tabular reports can retrieve rainfall hyetographs for specific events that 

can be pasted directly into a SWMM Time Series created in another SWMM 

session, and examples of using the Statistics tool to analyze the rainfall record are 

shown elsewhere in this chapter. 

171 
In rainfall analysis, the separation time used to decide when one event ends and 

another begins is referred to as the Minimum Inter-Event Time (MIT). This is the smallest 

number of consecutive dry periods that must occur before the next wet period is 

considered as a separate event. There is no established “correct” value for the MIT, 

although 3 to 30 hours are often used for rainfall data (Hydroscience, 1979). See Adams 

and Papa (2000) for a detailed discussion on this subject. When storm events are 

characterized as a Poisson process, the time between events follows an exponential 

distribution for which the mean equals the standard deviation (i.e., the coefficient of 

variation (CV) is 1). Thus one suggested approach to choosing a MIT is to find a value 

that produces a CV of 1 for the resulting collection of inter-event times. 

Figure 9-14 shows the statistical query used to test how well a MIT (separation 

time) of 12 hours produces a sequence of events whose inter-event times have a CV of 1 

for the rainfall record used in this chapter. The resulting CV (standard deviation divided 

by the mean) is 211.33 / 195.28 = 1.08, indicating that 12 hours is a reasonable MIT to 

use for this rainfall record. 

Figure 9-14. Selection of an MIT for analyzing a rainfall record 

Next a frequency analysis is made for each of the following rainfall quantities: 

duration, mean intensity, total volume, and peak intensity. Each analysis uses a Statistics 

Selection dialog that looks the same as that in Figure 9-14, except that a different choice 

of event statistic is used for each. Table 10-2 lists the summary statistics found for each 

frequency analysis. The first two properties (number of events and event frequency, or 

percentage of total time in which rainfall is registered) are the same for each rainfall 

property since all of the frequency analyses used the same thresholds to define an event. 

172 
 

Event total rainfall (in) 

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 

0 8 16 24 32 40 48 56 64 72 80 

Event total duration (hr) 

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

100 

Exceedance frequency 

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

100 

Exceedance frequency 

Total rainfall 

Duration 

Table 9-2. Summary statistics for various rainfall event properties 

Event statistic 

Property Duration Mean Intensity Total Volume Peak Intensity 

(h) (in/hr) (in) (in/hr) 

Number of Events 446 446 446 446 

Event Frequency 0.043 0.043 0.043 0.043 

Minimum Value 1.000 0.006 0.01 0.006 

Maximum Value 61.000 0.6900 4.44 1.470 

Mean Value 8.466 0.042 0.247 0.078 

Std. Deviation 10.557 0.058 0.445 0.125 

Skewness Coeff. 2.278 5.642 4.733 5.550 

Figure 9-15 shows the frequency plot produced by this analysis for event duration 

and total rainfall. (This figure was generated by using SWMM’s Edit | Copy To menu 

option to copy the data associated with each frequency plot to the Windows Clipboard 

from which it was pasted into a spreadsheet program and combined together on a single 

graph.) This plot can also be used as a less direct indicator than the pond depth frequency 

analysis performed earlier to see if the Water Quality Capture Volume (WQCV) of 0.23 

inches is sufficient to capture the majority of runoff events. 

Figure 9-15. Frequency plots for event duration and depth 

173 
Table 9-3. Ten most severe events based on duration, depth and intensity 

T Duration (hr) Mean (in/hr) Volume (in) Peak (in/hr) r Rank (year) Start Date Value Start Date Value Start Date Value Start Date Value 

1 11 5/5/1969 61 7/27/1970 0.69 7/24/1977 4.44 8/12/1975 1.47 

2 5.5 10/23/1975 56 7/20/1973 0.39 5/27/1975 3.29 7/19/1970 0.97 

3 3.67 10/10/1969 51 7/16/1969 0.38 5/5/1969 2.98 5/23/1971 0.85 

4 2.75 10/3/1969 51 7/19/1970 0.36 6/10/1970 2.78 7/27/1970 0.69 

5 2.2 3/29/1970 50 5/23/1971 0.36 6/7/1974 2.75 7/24/1977 0.65 

6 1.83 8/2/1976 49 7/28/1974 0.33 8/12/1975 2.25 8/14/1975 0.55 

7 1.57 5/27/1975 49 8/8/1970 0.27 10/3/1969 1.97 6/17/1975 0.52 

8 1.38 5/20/1975 48 5/8/1971 0.22 10/10/1969 1.66 7/28/1974 0.44 

9 1.22 3/9/1968 46 7/24/1977 0.20 4/24/1971 1.62 9/11/1973 0.40 

10 1 6/7/1968 46 8/14/1975 0.19 4/24/1973 1.57 7/20/1973 0.39 

It is seen (blue line) that about 70% of the rainfall events have a total volume 

smaller than 0.23 inches. Even if the watershed were totally impervious with no surface 

retention capacity, the pond would control around 70% of the events according to the 

model. In reality there are infiltration and storage losses so that a larger percentage of the 

rainfall events are controlled by the pond’s volume. Finally, note also that long storms are 

not very frequent, with 50% of them being shorter than 5 hours, and 80% shorter than 14 

hours. Storms longer than one day are very uncommon at this recording station located in 

the Colorado foothills. 

Another use of this type of multi-variate statistical analysis is to study in more 

detail the correspondence between the frequencies of the events based on different 

rainfall characteristics. The largest event is not necessarily the longest one or the most 

intense. It is useful to determine the degree of dependence among storm event 

characteristics in order to see if these characteristics are correlated or not, and to identify 

a subset of the most critical events that could be used for design purposes, depending on 

the objective of the analysis. The intensity of the events is significant in determining peak 

discharge, but the magnitude may be more important when storage control structures are 

designed or evaluated. 

Table 9-3 shows the ten most extreme events according to the four characteristics 

under analysis: duration, mean intensity, volume and peak intensity. The table reveals 

that the peak and mean intensities are closely correlated; seven of the ten events with the 

largest peak intensity are also in the groups of events with a large mean intensity (dates of 

these common events are underlined). There is also a correspondence between duration 

and total volume; four of the longest events are also in the group that contains the largest 

ones (the dates of these common events are in blue). A weaker correlation is observed 

between the mean intensity and volume (one common event in a red box), and between 

volume and peak intensity (two common events in green). 

174 
Table 9-4. Correspondence among the most severe events 

Duration & Duration & Duration & Mean & Mean & Volume & 

Mean Volume Peak Volume Peak Peak 
 

- 1 & 3 - 9 & 1 1 & 4 1 & 5 

- 3 & 8 - - 2 & 10 6 & 1 

- 4 & 7 - - 4 & 2 -

- 7 & 2 - - 5 & 3 -

- - - - 6 & 8 -

- - - - 9 & 5 -

- - - - 10 & 6 -

Table 9-4 shows the ranks of the common events identified in Table 9-3. Numbers 

before and after the “&” symbol indicate the rank according to the variables defined in 

the first row of the table. For example, from the second column, the longest event (61 

hrs) is also the third largest event (2.98 inches), the third longest event (51 hrs) is the 

eighth largest event (1.66 inches), and so on. Note that the two common events identified 

among the most severe in terms of the volume and peak intensity are the same two events 

associated with the largest peak discharges released by the storage unit discussed earlier; 

these are the events of 07/47/1977 and 8/12/1975. Finally, there are no common events 

among the ten most severe in terms of both duration and intensities (both mean and 

peak). This analysis corresponds to a preliminary step in evaluating the correlation 

between storm event characteristics. Other methodologies including the use of scatter 

plots between variables and correlation coefficients can be used. These methods are 

applied to all the events and not only the most severe ones. 

9.5 Summary 

This example demonstrated how to use continuous simulation along with 

statistical analysis to evaluate the long-term behavior of a drainage system. Ten years of 

continuous rainfall data (1-hr resolution) and monthly average evaporation rates were 

used to analyze the performance of the conveyance system and detention pond designed 

in Example 3. The key points illustrated in this example were: 

1.	 Continuous simulation allows modelers to more faithfully represent the behavior of 

drainage systems because it subjects them to a long sequence of actual rainfall events 

of varying magnitudes and durations and also accounts for the variability of 

antecedent conditions that exist from one event to the next. 

2.	 Evaporation is an important component of the long-term water budget that should be 

considered in continuous simulation. In this example it accounted for 19 % of the 

total rainfall input to the catchment. 

3.	 Model setup for continuous simulation is quite straightforward in SWMM, providing 

that reliable long-term rainfall records and evaporation data are available. 

175 
4.	 High time resolution on rainfall data is required if accurate predictions of peak runoff 

flows are needed. The hourly time interval of the rainfall data used in this example 

may cause peak discharges to be underestimated. 

5.	 SWMM’s Statistics tool is a valuable aid in interpreting the large amount of output 

data that can be generated from a long-term continuous simulation. It was used here 

to determine how effective the detention pond was in reducing peak discharges and in 

capturing the majority of runoff events within its water quality control volume. The 

tool was also used to characterize the properties of the most severe rainfall events 

occurring over the 10-year simulation period. 

176 
 

References 

Adams, B.J. and Papa, F. (2000). Urban Stormwater Management Planning with 

Analytical Probabilistic Models, John Wiley & Sons, Inc, New York, NY. 

Akan, A.O. and Houghtalen, R.J. (2003). Urban Hydrology, Hydraulics, and Stormwater 

Quality, John Wiley & Sons, Inc, Hoboken, NJ. 

American Society of Civil Engineering (ASCE) (1992). Design and Construction of 

Urban Stormwater Management Systems, ASCE Manuals and Reports on 

Engineering Practice No. 77 and Water Pollut. Control Fed. Manual of Practice 

RD-20, New York, NY. 

Bedient, P.B. and Huber, W.C. (2002). Hydrology and Floodplain Analysis, 3rd Ed., 

Prentice-Hall, Upper Saddle River, NJ. 

City of Fort Collins (1984). Storm Drainage Design Criteria and Construction 

Standards, Utilities Department, Stormwater Division, Fort Collins, CO. 

(http://www.fcgov.com/stormwater/pdf/sw-manual07.pdf) 

City of Fort Collins (1997). Memorandum: Update to the Stormwater Drainage Design 

Criteria. Memorandum to Storm Drainage Design Criteria Users. April 29, 1997, 

Utilities Department, Stormwater Division, Fort Collins, CO. 

City of Fort Collins (1999). Memorandum: New Rainfall Criteria. Memorandum to Storm 

Drainage Design Criteria Users. April 12, 1999, Utilities Department, 

Stormwater Division, Fort Collins, CO. 

Clark County Regional Flood Control District (CCRFCD) (1999). Hydrological Criteria 

and Drainage Design Manual, Las Vegas, NA. 

(http://acequia.ccrfcd.org/pdf_arch1/hcddm/hcddm.pdf) 

Douglas County (2008). Storm Drainage Design and Technical Criteria Manual, 

Douglas County, Department of Public Works-Engineering Division, Castle 

Rock, CO. 

(http://www.douglas.co.us/publicworks/engineering/Storm_Drainage_Design_and 

_Technical_Criteria_Manual.html) 

Driscoll, E.D., Palhegyi, G.E., Strecker, E.W. and Shelly, P.E. (1989). Analysis of Storm 

Events Characteristics for Selected Rainfall Gauges throughout the United States, 

U.S. Environmental Protection Agency. Washington, DC. 

Field, R. and Tafuri, A.N. (1973). “Storm Pollution Control in U.S”. Combined Sewer 

Overflow Seminar Papers. EPA 670/2-73-077, U. S. Environmental Protection 

Agency, Edison, NJ. 

(http://www.epa.gov/ednnrmrl/publications/conferencepapers/epa670273077) 

Grigg, N.S. (1996). Water Resources Management: Principles, Regulations, and Cases, 

McGraw-Hill, New York, NY. 

177 
Guo, J.C.Y. (2001). “Design of Infiltration Basins for Stormwater.” Stormwater 

Collection Systems Design Handbook. Edited by L. Mays, McGraw-Hill, New 

York, NY. 

Guo, J.C.Y. and Urbonas, B. (1995). Special Report to the Urban Drainage and Flood 

Control District on Stormwater BMP Capture Volume Probabilities in United 

States. Denver, CO. 

Guo, J.C.Y. and Urbonas, B. (1996). “Maximized Detention Volume Determined by 

Runoff Capture Ratio.” Journal of Water Resources Planning and Management, 

122(1):33-39. 

Guo, J.C.Y. and Urbonas, B. (2002). “Runoff Capture and Delivery Curves for Stormwater Quality Control Design.” Journal of Water Resources Planning and 

Management, 128(3):208-215. 

Hydroscience, Inc. (1979). A Statistical Method for the Assessment of Urban Stormwater. 

EPA-440/3-79-023, U.S. Environmental Protection Agency, Cincinnati, OH. 

Huber, W., Clannon, L. and Stouder, M. (2006). BMP Modeling Concepts and 

Simulation. EPA/600/R-06/033, U.S. Environmental Protection Agency (EPA). 

Cincinnati, OH. 

Manning, M.J., Sullivan, R.H. and Kipp T.M. (1977). Nationwide Evaluation of 

Combined Sewer Overflows and Urban Stormwater Discharges – Vol. III: 

Characterization of Discharges. EPA-600/2-77-064c (NTIS PB-272107), U.S. 

Environmental Protection Agency, Cincinnati, OH. 

Metcalf and Eddy, Inc. (1991). Wastewater Engineering: Treatment, Disposal, Reuse, 

McGraw-Hill, Inc., New York, NY. 

Nicklow, J.W., Boulos, P.F. and Muleta, M.K. (2004). Comprehensive Sewer Collection 

System Analysis Handbook for Engineers and Planners, MWH Soft, Inc. 

Pasadena, CA. 

Rossman, L. (2008). Storm Water Management Model User’s Manual Version 5.0. 

EPA/600/R-05/040, U.S. Environmental Protection Agency, National Risk 

Management Research Laboratory, Cincinnati, OH. 

Sansalone, J.J. and Hird, J. (2003). “Treatment of Stormwater Runoff from Urban 

Pavement and Roadways.” Wet-Weather Flow in the Urban Watershed, 

Technology and Management. Edited by R. Field and D. Sullivan. CRC Press 

LLC, Boca Raton, FL. 

Sartor, J.D. and Boyd, G.B. (1972). Water Pollution Aspects of Street Surface 

Contaminants. EPA-R2-72-081 (NTIS PB-214408), U.S. Environmental 

Protection Agency, Washington, DC. 

Urban Drainage and Flood Control District (UDFCD) (2001). Urban Storm Drainage 

Criteria Manual, 2007 revision. Denver, CO. 

(http://www.udfcd.org/downloads/down_critmanual.htm). 

178 
U.S. Environmental Protection Agency (1983). Results of the Nationwide Urban Runoff 

Program, Volume I Final Report. NTIS PB84-185552, U.S. Environmental 

Protection Agency, Washington, DC. 

U.S. Environmental Protection Agency (1986). Methodology for Analysis of Detention 

Basins for Control of Urban Runoff Quality. EPA 440/5-87-001, Office of Water, 

Washington, DC. 

U.S. Environmental Protection Agency (1999). Storm Water Technology Fact Sheet 

Infiltration Trench. EPA 832-F-99-019, U.S. Environmental Protection Agency. 

Washington, DC. 

(http://www.epa.gov/owm/mtb/infltrenc.pdf). 

Vanoni, V.A. (1975). Sedimentation Engineering, ASCE Manual and Report on 

Engineering Practice No. 54, New York, NY. 

Water Environment Federation (1998). Urban Runoff Quality Management, WEF 

Manual of Practice No. 23., ASCE Manual and Reports on Engineering Practice 

No. 87, Water Environmental Federation, Alexandria, VA. 

179