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

What WinSLAMM is: Brief Summary of • Urban stormwater model (does not address agricultural areas, etc.) WinSLAMM Features and • Designed as multi-scale model (individual lots to whole communities) Uses • 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: Robert Pitt Dept. of Civil, Construction, and Environmental Engineering Wet detention ponds Street cleaning University of Alabama Tuscaloosa, AL 35487 Biofiltraiton and Cisterns and rain barrels for bioretention devices water reuse John Voorhees PV and Associates Catchbasins Grass swales Madison, WI Proprietary devices Rain gardens Porous pavements Development options (pavement and roof disconnections, etc.) WinSLAMM Weaknesses: Applications of WinSLAMM • Not used for peak flow predictions or flood analyses. • Permit Compliance – Municipal Pollutant Loadings and Discharge Reductions • Can be integrated with other models and tools to address fate and transport in • Evaluate Alternative Stormwater Controls: receiving waters (such as QUAL2E, HSPF) City-wide – • Doesn’t calculate construction erosion, Watershed – Site Development but does calculate rainfall energy for post – • Identify critical drainage areas processing • Doesn’t include snowmelt ID critical land uses – ID critical source areas • Can be used with SWMM to evaluate – Assist with cost-sharing combined sewer – Identify the most cost-effective stormwater – • Is not a lifestyle, but can be integrated control and development scenarios with models that are connected to Youtube, etc ☺ 1

Background & History Background & History – Development Began – Mid-1980’s: in mid-1970’s • Model expanded to • Early EPA street include more cleaning and receiving management options water projects beyond street cleaning • San Jose and Coyote • Nationwide Urban Creek (CA) Runoff Program (NURP) projects provided large – Primary Purpose: data set for model, • Identify Sources of especially: Alameda Co. CA; Bellevue, WA; and Urban Stormwater Milwaukee, WI Pollutants • Ontario Ministry of the • Evaluate Efficiency of Environment (Ottawa) Control Practices Model Applications Background & History Large Scale, City-wide Analysis Example – 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 of Jefferson County, AL; the TVA, Economic Development group; WI DNR; and the USGS) City-wide sediment load and runoff volume analysis for Wausau, WI (EarthTech) 2

Model Applications Model Applications Detailed Practice Analysis Examples Site Development Analysis Example Wet Detention Pond – Analyze Porous Pavement Catchbasin with Sump the performance of a specific Biofilter Grass Swales Infiltration/Detention Pond 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 WinSLAMM integrates site and We are using CFD (Fluent 6.2 and Flow 3D) to determine development information: scour from stormwater controls; results being used to expand WinSLAMM analyses Soil Type This is an example of the effects of the way that water enters Runoff a sump on the depth of the water jet and resulting scour Landuse Area Volume and WinSLAMM Pollutant Rainfall Loads Development Characteristics Control Practices 3

Important WinSLAMM Features Residential Land Use Residential Land Use Source Areas Source Areas Pitched Roofs Pitched Roofs Driveways Driveways • Hydrology stresses small and intermediate-scaled Sidewalks Sidewalks Small Landscaped Areas Small Landscaped Areas processes that are most important for water quality analyses. Medium Density Residential • Sediment accumulation and washoff processes based on Low Density Residential huge number of field observations from throughout North Storm Sewer America. • Stormwater control performance calculations based on extensive field observations; most are driven by site hydraulics and sediment characteristics. Shopping Center Commercial • Stormwater controls can be evaluated in many combinations and located at many areas. Park • Construction and operating costs of stormwater controls are calculated for most US locations. • Model output can be exported to support further post- Commercial Land Use Other Urban processing (integrated with detailed drainage system Land Use Source Areas models, receiving water models, and decision analyses Flat Roofs Source Areas Parking Playground models). Driveways Sidewalks Sidewalks Large Landscaped Outfall Small Landscaped Areas Areas Many types of runoff monitoring used to calibrate and verify Probability WinSLAMM, from small source areas to outfalls. 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) 0.5” 3” 8” >8”: <0.1% of rains (2% of runoff) 4

Example runoff plot for small paved area. Infiltration Rates in Disturbed Urban Soils Street dirt washoff and runoff (AL tests) test plot, Toronto 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 1987 Pitt, et al. 1999 Pitt 1987 Infiltration Measurements for Noncompacted, Infiltration Measurements for Compacted, Sandy Soils Sandy Soils Pitt, et al. 1999 Pitt, et al. 1999 5

A Nice Example of Runoff Model Verification using WinSLAMM Observed vs. Predicted Runoff at Madison Maintenance Yard Outfall 3.0 2.5 Predicted Runoff (in) 2.0 1.5 1.0 0.5 - - 0.5 1.0 1.5 2.0 2.5 3.0 Observed Runoff (in) Pitt, et al. 2003 Pollutant Probability Distributions (used in Another Good Verification Example Monte Carlo Calculations) • Depicts the pollutant concentrations for source areas and land uses Bannerman, et al. 1983 6

WinSLAMM uses an Extended Rainfall Period, Measured Street Particulate Loading , Keyes – Usually from One Year to Several Decades Long Smooth Asphalt Test Area Street cleaning days Changes in particle sizes Street dust and dirt loading saw-tooth pattern Pitt 1979 Observed Particulate Removal by Street Observed Washoff of Street Dirt by Cleaning Particle Size, Bellevue, WA Referential removal of large particulates by street cleaners Preferential removal of 60 60 2000-6370 small particles by rains Percentage of Particle Sizes Removed by Street Percentage of Particle Sizes Removed by Street 850-2000 >6370 50 50 600-850 >6370 250-600 Overall 40 40 2000-6370 106-250 45-106 30 30 Sweeping Sweeping 20 20 850-2000 Overall <45 106-250 600-850 250-600 45-106 10 10 <45 0 0 -10 -10 Smooth Streets Very Rough Streets -20 -20 Particle Sizes Ranges Particle Sizes Ranges (microns) (microns) Pitt 1985 7

Wisconsin DNR and USGS Recent Street Cleaning Tests Particle Resuspension of Street Dirt Caused by High-Frequency Broom Vehicle Passage for an Asphalt Road Control Fugitive dust losses from Low-Frequency Broom streets account for excessive material that is not washed off during rains. Air Sweeper Bedload sampler installations. About 5% of annual sediment was in bedload fraction. Measured Versus Modeled Street Loads With Mechnical Broom Street Cleaning - Residential 2004 2,500 Pre Sw eeping Post Sw eeping 2,250 Modeled 2,000 1,750 1,500 lb/curb-m ile 1,250 1,000 750 500 250 0 38047 38077 38107 38137 38167 38197 38227 38257 38287 8

Annual TSS Reductions, %, for Vacuum Pollutant Control in Grass Swales Assisted Cleaner With & Without Parking Control Runoff from Pervious/ Land Use Parking With Parking Without Parking impervious Trapping sediments Density Controls Controls Reducing runoff area and associated pollutants velocity 1 \ Week 1\ Month 1 \ Week 1 \Month Med. Den Med. 20 7 8 2 Res. High Den Med. 17 6 7 2 Sediment Res. particles Strip Comm Med. 19 7 8 3 Downtown Exten 17 6 13 4 Reduced volume and treated runoff Light Indus. Med. 9 3 3 1 Infiltration Date: 10/11/2004 Settling of Different Sized Particulates as a Function of Flow Characteristics (depth and velocity), Particle Settling 116 ft Characteristics and Grass Type and Height TSS: 10 mg/L 75 ft 100 TSS: 20 mg/L 90 25 ft 80 Ratio: 0 - 1.0 TSS: 30 mg/L 70 Percent reduction (%) 6 ft 60 Ratio: 1.0 - 1.5 50 3 ft TSS: 35 mg/L Ratio: 1.5 - 4 40 2 ft TSS: 63 mg/L 30 Total Dissolved Solids 20 (<0.45 µm) Head (0ft) 10 TSS: 84 mg/L 0 0.00001 0.0001 0.001 0.01 0.1 1 10 100 TSS: 102 mg/L Settling frequency 9