Brief Summary of Urban stormwater model (does not address - - PowerPoint PPT Presentation

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Brief Summary of WinSLAMM Features and Uses

Robert Pitt

• Dept. of Civil, Construction, and Environmental Engineering

University of Alabama Tuscaloosa, AL 35487 John Voorhees PV and Associates Madison, WI

What WinSLAMM is:

• Urban stormwater model (does not address agricultural

areas, etc.)

• Designed as multi-scale model (individual lots to whole

communities)

• Annual or seasonal pollutant loads and event pollutant

probability distributions using long-term rainfall records

• Evaluates individual or multiple stormwater control

scenarios (source area, land use, drainage, outfalls), such as: Development options (pavement and roof disconnections, etc.) Porous pavements Rain gardens Proprietary devices Grass swales Catchbasins Cisterns and rain barrels for water reuse Biofiltraiton and bioretention devices Street cleaning Wet detention ponds

WinSLAMM Weaknesses:

• Not used for peak flow predictions or

flood analyses.

• Can be integrated with other models and

tools to address fate and transport in receiving waters (such as QUAL2E, HSPF)

• Doesn’t calculate construction erosion,

but does calculate rainfall energy for post processing

• Doesn’t include snowmelt
• Can be used with SWMM to evaluate

combined sewer

• Is not a lifestyle, but can be integrated

with models that are connected to Youtube, etc☺

Applications of WinSLAMM

• Permit Compliance – Municipal Pollutant

Loadings and Discharge Reductions

• Evaluate Alternative Stormwater Controls:

– City-wide – Watershed – Site Development

• Identify critical drainage areas

– ID critical land uses – ID critical source areas – Assist with cost-sharing – Identify the most cost-effective stormwater control and development scenarios

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Background & History

– Primary Purpose:

• Identify Sources of

Urban Stormwater Pollutants

• Evaluate Efficiency of

Control Practices

– Development Began in mid-1970’s

• Early EPA street

cleaning and receiving water projects

• San Jose and Coyote

Creek (CA)

– Mid-1980’s:

• Model expanded to

include more management options beyond street cleaning

• Nationwide Urban

Runoff Program (NURP) projects provided large data set for model, especially: Alameda Co. CA; Bellevue, WA; and Milwaukee, WI

• Ontario Ministry of the

Environment (Ottawa)

Background & History

– Mid-1980’s - Model used in Agency Programs:

• Toronto Area Watershed Management Strategy
• Wis. Dept. of Natural Resources: Priority Watershed Program

– First Windows Version Developed in 1995 (Currently developing Windows version 9.4) – Continuously being updated based on user needs and new research (recent and current support from Stormwater Management Authority

• f Jefferson County, AL; the TVA, Economic Development group; WI

DNR; and the USGS)

Background & History Model Applications

Large Scale, City-wide Analysis Example

City-wide sediment load and runoff volume analysis for Wausau, WI (EarthTech)

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Model Applications

Site Development Analysis Example

Porous Pavement Biofilter Infiltration/Detention Pond Catchbasin with Sump Grass Swales

Model Applications

Detailed Practice Analysis Examples

Wet Detention Pond – Analyze the performance of a specific pond for a specific site (WinSLAMM or WinDETPOND) Develop and analyze new controls – this inlet has a prototype upflow filter installed CFD Modeling to Calculate Scour/Design Variations

We are using CFD (Fluent 6.2 and Flow 3D) to determine scour from stormwater controls; results being used to expand WinSLAMM analyses This is an example of the effects of the way that water enters a sump on the depth of the water jet and resulting scour

WinSLAMM integrates site and development information:

WinSLAMM

Soil Type Landuse Area Rainfall Development Characteristics Control Practices Runoff Volume and Pollutant Loads

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Residential Land Use

Source Areas Pitched Roofs Driveways Sidewalks Small Landscaped Areas

Residential Land Use

Source Areas Pitched Roofs Driveways Sidewalks Small Landscaped Areas

Commercial Land Use

Source Areas Flat Roofs Parking Driveways Sidewalks Small Landscaped Areas

Other Urban Land Use

Source Areas Playground Sidewalks Large Landscaped Areas Outfall

Storm Sewer

Medium Density Residential Low Density Residential Shopping Center Commercial Park

Important WinSLAMM Features

• Hydrology stresses small and intermediate-scaled

processes that are most important for water quality analyses.

• Sediment accumulation and washoff processes based on

huge number of field observations from throughout North America.

• Stormwater control performance calculations based on

extensive field observations; most are driven by site hydraulics and sediment characteristics.

• Stormwater controls can be evaluated in many

combinations and located at many areas.

• Construction and operating costs of stormwater controls

are calculated for most US locations.

• Model output can be exported to support further post-

processing (integrated with detailed drainage system models, receiving water models, and decision analyses models).

Probability distribution of rains (by count) and runoff (by depth). Birmingham Rains:

<0.5”: 65% of rains (10% of runoff) 0.5 to 3”: 30% of rains (75% of runoff) 3 to 8”: 4% of rains (13% of runoff) >8”: <0.1% of rains (2% of runoff)

0.5” 3” 8”

Many types of runoff monitoring used to calibrate and verify WinSLAMM, from small source areas to outfalls.

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Street dirt washoff and runoff test plot, Toronto

Pitt 1987 Example runoff plot for small paved area.

Pitt 1987

Infiltration Rates in Disturbed Urban Soils (AL tests)

Sandy Soils Clayey Soils

Field research has shown that the infiltration rates of urban soils are strongly influenced by compaction, probably more than by moisture saturation.

Pitt, et al. 1999

Infiltration Measurements for Noncompacted, Sandy Soils

Pitt, et al. 1999

Infiltration Measurements for Compacted, Sandy Soils

Pitt, et al. 1999

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Pitt, et al. 2003

A Nice Example of Runoff Model Verification using WinSLAMM

Observed vs. Predicted Runoff at Madison Maintenance Yard Outfall

• 0.5

1.0 1.5 2.0 2.5 3.0

• 0.5

1.0 1.5 2.0 2.5 3.0 Observed Runoff (in) Predicted Runoff (in)

Another Good Verification Example

Bannerman, et al. 1983

Pollutant Probability Distributions (used in Monte Carlo Calculations)

• Depicts the pollutant concentrations for source areas and land uses

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WinSLAMM uses an Extended Rainfall Period, Usually from One Year to Several Decades Long

Measured Street Particulate Loading , Keyes – Smooth Asphalt Test Area

Pitt 1979

Street dust and dirt loading saw-tooth pattern Changes in particle sizes Street cleaning days

Observed Particulate Removal by Street Cleaning

Referential removal of large particulates by street cleaners

<45 45-106 106-250 250-600 600-850 850-2000 2000-6370 >6370 Overall

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• 10

10 20 30 40 50 60 Particle Sizes Ranges (microns) Percentage of Particle Sizes Removed by Street Sweeping Very Rough Streets Overall >6370 2000-6370 850-2000 600-850 250-600 106-250 45-106 <45

• 20
• 10

10 20 30 40 50 60 Particle Sizes Ranges (microns) Percentage of Particle Sizes Removed by Street Sweeping Smooth Streets

Observed Washoff of Street Dirt by Particle Size, Bellevue, WA

Pitt 1985

Preferential removal of small particles by rains

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Particle Resuspension of Street Dirt Caused by Vehicle Passage for an Asphalt Road

Fugitive dust losses from streets account for excessive material that is not washed off during rains. High-Frequency Broom Low-Frequency Broom Control Air Sweeper

Wisconsin DNR and USGS Recent Street Cleaning Tests

Bedload sampler installations. About 5% of annual sediment was in bedload fraction. Measured Versus Modeled Street Loads With Mechnical Broom Street Cleaning - Residential 2004

250 500 750 1,000 1,250 1,500 1,750 2,000 2,250 2,500

38047 38077 38107 38137 38167 38197 38227 38257 38287

lb/curb-m ile

Pre Sw eeping Post Sw eeping Modeled

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Annual TSS Reductions, %, for Vacuum Assisted Cleaner With & Without Parking Control

1 3 3 9 Med. Light Indus. 4 13 6 17 Exten Downtown 3 8 7 19 Med. Strip Comm 2 7 6 17 Med. High Den Res. 2 8 7 20 Med.

• Med. Den

Res. 1 \Month 1 \ Week 1\ Month 1 \ Week Without Parking Controls With Parking Controls Parking Density Land Use

Runoff from Pervious/ impervious area Trapping sediments and associated pollutants Reducing runoff velocity

Infiltration

Reduced volume and treated runoff

Sediment particles

Pollutant Control in Grass Swales

Head (0ft)

Date: 10/11/2004

2 ft 25 ft 6 ft 3 ft 116 ft 75 ft

TSS: 10 mg/L TSS: 20 mg/L TSS: 30 mg/L TSS: 35 mg/L TSS: 63 mg/L TSS: 84 mg/L TSS: 102 mg/L

10 20 30 40 50 60 70 80 90 100 0.00001 0.0001 0.001 0.01 0.1 1 10 100 Settling frequency Percent reduction (%) Ratio: 0 - 1.0 Ratio: 1.0 - 1.5 Ratio: 1.5 - 4 Total Dissolved Solids (<0.45 µm)

Settling of Different Sized Particulates as a Function of Flow Characteristics (depth and velocity), Particle Settling Characteristics and Grass Type and Height

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Low Flow vs. Historical Stillwater, OK, Retardance Curves

From such graphs swale hydraulic characteristics can be predicte From such graphs swale hydraulic characteristics can be predicted on the d on the basis of flow rate, cross sectional geometry, slope, and vegetat basis of flow rate, cross sectional geometry, slope, and vegetation type. ion type.

Kirby 2006 Relatively short urban landscaping grasses (2 to 6 inches tall)

Three Components to Modeling Wet Detention Ponds

1. Pond Geometry 2. Flow, Initial Stage and Particle Size Data 3. Outlet Information

Wet Detention Pond Data Entry Form

• particle size distribution
• stage-area info
• initial stage conditions
• inflow hydrograph

shape factors or actual hydrograph in DETPOND)

• many outlet options

(including conventional hydraulic outlets, beneficial use withdrawals, seepage, evaporation, pumped

• utlet, stone weepers,

etc.)

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Measured Particle Sizes, Including Bed Load Component, at Monroe St. Detention Pond, Madison, WI

Suspended Solids Control at Monroe St. Detention Pond, Madison, WI (USGS and WI DNR data)

Consistently high TSS removals for all influent concentrations (but better at higher concentrations, as expected)

Vortechs Monitoring Site

Proprietary devices modeled using basic settling methods with bypass; scour currently being added to model.

TSS Load Reduction Results Used for Model Verification

• Sum of Loads; TSS Loads, kg

895 939 Stormceptor (15 events, bypass) 51 63 Vortechs (18 events, no bypass)

Effluent Influent

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Biofilter Data Entry Form

Sources of Cost Data

• Pre-Determined Costs

– SEWRPC 1991 Cost Report – Costs Updated Using ENR Cost Indices – Cost Indices Available for 20 Cities

Atlanta, GA Baltimore, MD Birmingham, AL Boston, MA Chicago, IL Cincinnati, OH Cleveland, OH Dallas, TX Denver, CO Detroit, MI Kansas City, MO Los Angeles, CA Minneapolis, MN New Orleans, LA New York, NY Philadelphia, PA Pittsburgh, PA San Francisco, CA Seattle, WA St.Louis, MO 2000 4000 6000 8000 10000 12000 Cost Index Value

Construction Cost Index by City

1989 2005

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WinSLAMM v 9.2 Output Summary

• Runoff volume
• Particulate solids concentration
• Particulate solids yield
• Pollutant concentration
• Pollutant yield
• Many export options to link to other

models

Detailed Model Input/Output Data Available for: Model Input/Output

Example plots showing runoff percentage contributions from different source areas.

Example Flow Duration Curves

Use these curves to compare the attenuation of the control practices at the

• utfall to a no controls condition.

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Example Flow-Duration Curves for Different Stormwater Conservation Design Practices

20 40 60 80 100 120 140 0.1 1 10 100

% Greater than Discharge Rate Discharge (cfs) Top Set: No Controls Swales Bottom Set: Biorentention Swales and Bioretention Pond and Bioretention Pond, Swales and Bioretention

Flow Duration Curves are Ranked in Order of Peak Flows

Middle Set: Pond Pond and Swales

Example Cost Effectiveness Plot of Stormwater Control Practices for Runoff Volume Reductions

Swales and Bioretention Pond and Bioretention Bioretention Pond, Swales and Bioretention Pond Pond and Swale Swale

10 20 30 40 50 60 70 80 20 40 60 80

Max % Runoff Reduced $/1000 cu. Ft Reduced

Current and Planned Expansions to WinSLAMM

Based on recent research results and field verification

• Expand full routing capabilities in grass swales and

incorporate advanced particulate trapping algorithms (current). Will expand to grass filtering stormwater controls.

• Add more detailed ET analyses and pollutant trapping

processes to bioretention and biofiltration devices (current). Will expand to green roofs.

• Adding scour removal of particulates from hydrodynamic

devices (current). Will expand to ponds.

• Currently developing drag and drop front-end to model

to enable more flexible placement of controls.

• Other enhancements as requests, data, and resources

allow!

Selected WinSLAMM General Descriptions

• Pitt, R. and J. Voorhees. “Using decision analyses to select an urban runoff control

program” Chapter 4 in: Contemporary Modeling of Urban Water Systems, ISBN 0- 9736716-3-7, Monograph 15. (edited by W. James, E.A. McBean, R.E. Pitt, and S.J. Wright). CHI. Guelph, Ontario. pp 71 – 107. 2007.

• Pitt, R., R. Bannerman, S. Clark, and D. Williamson. “Sources of pollutants in urban

areas.” In: Effective Modeling of Urban Water Systems, Monograph 13. (edited by W. James, K.N. Irvine, E.A. McBean, and R.E. Pitt). CHI. Guelph, Ontario, pp. 465 – 530. 2005.

• Pitt, R., D. Williamson, and J. Voorhees. “Review of historical street dust and dirt

accumulation and washoff data.” Effective Modeling of Urban Water Systems, Monograph 13. (edited by W. James, K.N. Irvine, E.A. McBean, and R.E. Pitt). CHI. Guelph, Ontario, pp 203 – 246. 2005.

• Pitt, R. and J. Voorhees. “SLAMM, the Source Loading and Management Model.” In:

Wet-Weather Flow in the Urban Watershed (Edited by Richard Field and Daniel Sullivan). CRC Press, Boca Raton. pp 103 – 139. 2002.

• Pitt, R. “Small storm hydrology and why it is important for the design of stormwater

control practices.” In: Advances in Modeling the Management of Stormwater Impacts, Volume 7. (Edited by W. James). Computational Hydraulics International, Guelph, Ontario and Lewis Publishers/CRC Press. 1999.

• Pitt, R. “Unique Features of the Source Loading and Management Model (SLAMM).” In:

Advances in Modeling the Management of Stormwater Impacts, Volume 6. (Edited by

• W. James). Computational Hydraulics International, Guelph, Ontario and Lewis

Publishers/CRC Press. pp. 13 – 37. 1997.

• Pitt, R. “The Incorporation of Urban Runoff Controls in the Wisconsin’s Priority

Watershed Program.” In: Advanced Topics in Urban Runoff Research, (Edited by B. Urbonas and L.A. Roesner). Engineering Foundation and ASCE, New York. pp. 290-

• 313. 1986.