Office of Research and DevelopmentNational Risk Management Research Laboratory, Cincinnati, OH 45268

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May 9, 2014

Lewis A. Rossman

SWMM 5 – A Case Study of Model Redevelopment

What is SWMM?

2

SWMM is a public domain, distributed, dynamic hydrologic - hydraulic -water quality model used for continuous simulation of runoff quantity and quality from primarily urban areas.

3

Precipitation

Snowmelt

SurfaceRunoff

Evaporation/Infiltration

Groundwater

Overland Flow

Channel, Pipe &Storage Routing

Washoff

SanitaryFlows

RDII

Treatment / Diversion

Buildup

SWMM’s Process Models

What is it Used For?

4

Design and sizing of drainage system components including detention facilities.

Control of combined and sanitary sewer overflows.

Modeling I&I in sanitary sewer systems.

Generating non-point source pollutant loadings for waste load allocation studies.

Evaluating BMPs and LIDs for sustainability goals.

Flood plain mapping of natural channel systems.

How had it evolved?

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Version Year Contributors Comments

SWMM I 1971 Metcalf & Eddy, Inc.

Water Resources

Engineers

University of Florida

First version of SWMM; focus

was CSO modeling; few of its

methods are still used today.

SWMM II 1975 University of Florida First widely distributed version

of SWMM.

SWMM 3 1981 University of Florida

Camp Dresser & McKee

Full dynamic wave flow routing,

Green-Ampt infiltration, snow

melt, and continuous simulation

added.

SWMM 3.3 1983 EPA First PC version of SWMM.

SWMM 4 1988 Oregon State University

Camp Dresser & McKee

Groundwater, RDII, irregular

channel cross-sections and other

refinements added over a series

of updates throughout the

1990’s.

Why Redevelop SWMM

• Archaic file structure & linking

• No graphical user interface

• 50,000+ lines of sparsely documented FORTRAN

code

• Problematic flow routing performance (at times)

• Outdated process models (not really)

• Uneven user documentation

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What Were Our Goals

• Re-write the SWMM engine using an object-based

approach

• Provide SWMM with a graphical user interface

• Improve key computational aspects

• Maintain compatibility with SWMM 4

• Provide a complete set of documentation

• Do all this with no expenditure of extramural funds

7

• Formed an advisory panel to get direction and buy-in from SWMM gurus

• Entered into a no-cost CRADA with CDM-Smith to benefit from their long-term use & knowledge of SWMM

• Re-programmed all hydrology and hydraulics algorithms in house

• Used a previously developed GUI (for water distribution systems) as a template for the SWMM GUI

• Developed a Quality Assurance Plan to formalize code testing procedures

• Conducted beta testing with a select group of users

How Did We Do It

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EPA Staff CDM Staff

Lew Rossman – code developer Bob Dickinson – consultant / tester

Trent Schade – quality assurance Carl Chan – SWMM4 converter

Dan Sullivan – project manager Ted Burgess – project manager

Wayne Huber – special consultant

What Was the Result

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Step 1. Import a backdrop image of the study site

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Step 2. Draw in sub-catchments and drainage channels

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Step 3. Add a rain gage and rainfall data source

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Step 4. Enter parameter values for each object

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Step 5. Set simulation options

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Step 6. Run the simulation

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Step 7. View results in a variety of formats

Key Hydrologic Features

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Spatial Representation User-defined subcatchment areas

Rainfall User supplied

Interception/Evaporation User supplied

Hargreaves Formula

Infiltration Horton Curve, Green-Ampt Method

SCS Curve

Overland Flow Nonlinear Reservoir (Chen and

Shubinski, 1971)

Groundwater Localized Two-Zone Flux Model (Dawdy

and O’Donnell, 1965)

Snowmelt Heat Balance/Degree Day Model

(NWS SNOW-17)

Key Hydraulic Features

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Drainage Elements Nodes (Junction, Storage, Outfall)

Links (Conduits, Pumps, Regulators)

Conduit Shapes 20 common shapes + irregular open channels

+ custom closed conduits

Flow Routing Kinematic Wave (Huber, 1971)

Modified Dynamic Wave (based on Roesner

et al., 1981)

Controls Rule-Based Controls

Modulated Controls

Variable Speed Gate Opening

Flooding Overflow or Ponding

Other Inlet Controlled Culverts (FHWA-HDS5)

Key Water Quality Features

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Pollutant Buildup Power, exponential or saturation

function of time

Pollutant Washoff Rate proportional to runoff and buildup

or can use an EMC

BMP Removal User-assigned percent reduction

Non-Runoff Loads User-defined, Sanitary DWF, RDII inflow

Drainage System Routing CSTR model

Drainage System Treatment User-defined functions

Engine Improvements

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Unified object-based representation of a watershed

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6,695 Nodes6,769 Links

No pre-set limits on number of objects

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Well structured and commented source code written in ANSI-standard C

Flow

Routing

Runoff

Quality

Routing

Improved dynamic wave flow routing

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02/22/2002 00:21:00

Distance (ft)

1,0009008007006005004003002001000

Ele

vatio

n (

ft)

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20

19

18

17

16

15

14

13

12

11

10

9

0 1 2 3 4 5 6 7 8 9

10

Flow at Outfall

SWMM5 SWMM4

Elapsed Time (hours)

14121086420

Flo

w (

CF

S)

45.0

40.0

35.0

30.0

25.0

20.0

15.0

10.0

5.0

0.0

Flow at Outfall

SWMM 5 SWMM 4

Elapsed Time (hours)

14121086420

Flo

w (

CF

S)

100.0

80.0

60.0

40.0

20.0

0.0

∆∆∆∆t = 5 sec ∆∆∆∆t = 10 sec

Easy integration into third-party apps

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Measures of Success

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Enthusiastically adopted by the user community

0

500

1000

1500

2000

2500

3000

August September October November December January

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Downloads between August 2011 and January 2012

Also adopted by commercial vendors

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Approved by FEMA for the NFIP

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Used in a large number of CSO-LTC plans

30Indianapolis Seattle

CincinnatiPhiladelphia

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On-Going Development – LID Modeling

Disconnection

Infiltration Trench

Infiltration Basin

Cistern Green Roof

Rain Garden

Porous Pavement Vegetative Swale Street Planter

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0

20

40

60

80

100

0 5 10 15 20 25 30 35 40

mm

/h

r

Surface Infil. Soil Perc. Bottom Infil. Drain Outflow

0

0.2

0.4

0.6

0.8

1

0 5 10 15 20 25 30 35 40

Vo

lum

e F

ract

ion

Hours

Ponded Depth Soil Moisture Storage Depth

1 2 3 4 5

1. Wetting

2. Percolation

3. Saturation

4. Draining

5. Drying

Detailed Bio-Retention Cell Behavior

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New Tools Development

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Locate your site using Bing Maps

Display soil properties obtained from

querying the NRCS SSURGO

database

Select a source of long term hourly

rainfall data from a nearby rain gage

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Specify the site’s land cover and select a set of LID controls to employ.

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Run SWMM to generate daily rainfall/runoff statistics.

Keys to Successful Model Redevelopment (on a budget)

• Have a vision of the new model’s structure and the

kind of GUI it will require

• Try to keep code development in-house

• Have staff on hand who can answer users’ questions

• Weigh the merits of maintaining backwards

compatibility versus improving process models

• Budget twice as much time as you think it will take

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www.epa.gov/nrmrl/wswrd/wq/models/swmm

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THANK YOU

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Sub-Area Percent

Impervious

Public

Porous

Pavement

Public

Street

Planters

Private

Rain

Gardens

101 55 10 10 15

102 35 10 5 15

103 28 10 5 15

104 55 10 10 20

105 22 10 5 15

106 31 10 5 15

107 46 10 10 15

108 38 10 5 15

109 35 10 5 15

110 75 20 20 10

111 17 0 5 25

112 59 15 10 10

113 39 10 5 15

114 29 10 5 15

LID Impervious Treatability Table

Examples of SWMM 5’s Versatility

• Hydrologic and Hydraulic CSO Modeling (with LIDs)

• Modeling Snow Melt at Logan Airport

• Modeling Die-Off of Fecal Coliforms in the Hudson R.

• Small Site Hydrology Using a SWMM/Bing

Maps/SSURGO/BASINS Mashup

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Example 1:Hydrologic& Hydraulic

CSO Modeling

Combined SewerService Area #1

0

20

40

60

80

100

0 1 2 3 4

Storage Volume (Mgal)

% Reduction in CSO Volume

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5%

10%15%

Add LID practices (public / private scenarios)

Develop Gray/Green Trade-Offs

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0

10

20

30

40

50

60

70

80

90

100

0 0.5 1 1.5 2 2.5 3 3.5 4

% R

ed

uc

tio

n in

Ove

rflo

w V

olu

me

Gray Storage Volume (Mgal)

Gray Only Gray + Public Green Gray + Full Green

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Example 2: Snow Melt

Model Inputs:

• Removal depth

• Fractions transferred to:

• pervious area

• immediate melt

•other catchments

•Melt coefficients

•Base-pack temperature

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Snow Melt Results for Logan Airport

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Example 3. Coliform Die-Off in the Hudson R.