This information can be obtained from good aerial photographs for existing areas, or from project. This area is entered into the main land use screen,

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Module 4: WinSLAMM and Stormwater Controls Robert Pitt University of Alabama, Tuscaloosa, AL Porous pavement and bioretention controls for roof and parking lot runoff, Portland, OR The first step in using WinSLAMM for an area is to gather the needed data, especially the areas for the different surfaces. This information can be obtained from good aerial photographs for existing areas, or from project maps for proposed areas. This area is entered into the main land use screen, divided into major categories. See the basic WinSLAMM module for a review http://unix.eng.ua.edu/~rpitt/class/stormwaterman agement/m5%stormwater%models/m5%in ternet%material/mainswm5.htm Some of the other land uses and source areas included in WinSLAMM

Lincoln Cr. Watershed, Milw. University of Cape Town, South Africa One of many neighborhood volcanoes, Auckland, NZ University of Alabama at Birmingham

Different land uses have different surface characteristics which affect runoff characteristics Bochis 5 Possible to obtain surface area data for proposed developments from site maps.6. Landscaped areas Subtotals.75.7.4 3.96.68..7 Skinny streets Disconnected roof drains Pollution prevention through material substitution Compost-amended soils to enhance infiltration Directly connected roof drains Some of the basic site characteristics that can be investigated by WinSLAMM Total area: 5.6 acres.7.6 Sidewalks..9 Undeveloped area.5 Driveways.5 Total area.57.39 Roofs Small lots Streets Large lots Area (acres) Residential Area Source Areas 3

Impacts of Imperviousness on Surface Water and Groundwater Quantities Pheasant Branch Creek, WI Type of Water Resource Stream Baseflow Impervious Increase from % to 8% -% Impervious Increase from % to 6% Dry Stream Surface Runoff +9% +485% Regional Groundwater -% -55% Can we reverse these problems with stormwater controls? Stormwater Control Categories in the International Stormwater BMP Database: Structural Controls: Detention ponds Grass filter strips Infiltration basins Media filters Porous pavement Retention ponds Percolation trenches/wells Wetland basins Wetland channels/swales Hydrodynamic devices Non-Structural Controls: Education practice Recycling practice Maintenance practice Source controls General Approach for Stormwater Management Minimize directly connected impervious areas Use a combination of infiltration and sedimentation practices May need a combination of source area/preventative practices and end-of-pipe treatment Fit the practices into the landscape Roof Paved parking/storage Unpaved parking/storage Playgrounds Drivew ays Sidew alks/w alks WinSLAMM Treatment Practices Infiltration Trenches Biofiltration/Rain Gardens Cisterns/ rain barrels Wet detention pond Grass Drainage Swale Street Cleaning Catchbasins Porous Pavement Streets/alleys Undeveloped areas Small landscaped areas Other pervious areas Other impervious areas Freew ay lanes/shoulders Large turf areas Large landscaped areas Drainage system Plus, we now have upflow filters and hydrodynamic devices, and are working on other media filters and combination controls Outfall Drainage Disconnection 4

WinSLAMM Summary Data Outputs Runoff Volume (ft 3, percent reduction; and Rv, runoff coefficient), particulate solids (lbs and mg/l), for: - source area total without controls - total before drainage system - total after drainage system -total after outfall controls Total control practice costs: - capital costs - land cost - annual maintenance cost - present value of all costs -annualized value of all costs Receiving water impacts due to stormwater runoff: - calculated Rv with and without controls - approximate biological condition of receiving water (good, fair, or poor) - flow duration curves (probabilities of flow rates for current model run and without controls) Detailed Data Outputs for Each Event Runoff Volume (ft 3 ), source area contributions, particulate solids (lbs and mg/l), pollutants (lbs and mg/l) - by source area for each rain event - land use total - summary for all rains - total for land use and for each event - outfall summary, before and after drainage system and before and after outfall controls - Rv (runoff volume only) - total losses (runoff volume only) - calculated CN (runoff volume only) 5

The WinSLAMM batch editor can be used to automatically run a large number of files, usually for integration into a GIS-based map. RR6 NL9 RR9 NL RR 8 RR6 SL6 RR5 4 SL5 RR5 3 RR3 RR37 SL5 RR375 SL9 SL36 SL35 SL39 SL36 SL3 SL33 Critical Loading Rates High Subbasins MH Water Moderate ML Corporate Limits Low 4347 November, Critical Loading Rates Stormwater Investigation City of Racine, Wisconsin 6 6 3 48 Feet Additional Details Available for Each Event (with summaries) rain duration (hours), rain interevent period (days), runoff duration (hours), rain depth (inches), runoff volume (ft 3 ), Rv, average flow (cfs), peak flow (cfs), suspended solids (lbs and mg/l) WinSLAMM can also calculate life-cycle costs and compare different control programs to obtain unit removal costs File Name Runoff Volume (cf) Partic. Solids Yield (lbs) Sub Basin Capital Sub Basin Land Sub Basin Maint. Sub Basin Total Annual Sub Basin Total Present Value % Part. Solids Reduc. per lb Sediment Reduced Example - Base Case No Controls 546545 3743 % n/a Example - G 33646 34 99 9 8658 355 4% $.4 Example - P percent 44557 376 68686 34 58 7433 8% $ 8.74 Example - P 5 percent 39338 784 745 8555 4536 889 44% $ 8.74 6 RR7 PR RR3 P R8 PR7 PR8 PR8 PR8 Nonreg RR375 P R83 RR373 SL 335 RR373 RR57 RR37 6 RR376 SL33 SL334 RR37 S L38 RR 53 RR5 RR56 RR37 RR37 SL333 P R RR54 SL336 RR3 RR5 RR379 S L36 RR 58 RR6 RR59 RR374 SL33 RR37 4 RR37 SL3 4 SL3 S L37 SL35 N RR 8 RR Nonreg RR RR RR RR374 RR378 SL3 3 PR RR SL3 Nonreg Non re g RR 5 RR56 RR 57 SL33 PR3 RR378 RR37 Non re g RR RR RR5 RR55 RR37 SL3 RR376 SL3 RR378 SL 33 P R4 Nonreg NL83 RR37 9 RR37 3 RR379 SL3 PR64 RR3 RR5 NL5 RR4 RR4 RR5 RR5 RR373 RR377 SL34 PR P R RR5 RR SL38 SL38 SL34 PR64 SL34 SL34 PR64 Nonreg NL8 NL8 NL84 NL8 RR53 RR5 SL95 NL8 RR6 RR7 RR37 RR3 75 RR377 S L37 SL 37 PR63 PR5 PR6 NL88 NL 87 NL83 RR RR4 SL 3 NL89 NL8 NL87 RR6 S L96 NL 36 NL8 RR9 PR6 NL86 NL88 NL89 RR6 RR46 4 RR NL64 NL63 IW RR463 RR RR Nonreg RR7 RR38 RR377 SL35 PR 6 RR39 RR4 SL94 NL86 NL 84 RR3 NL35 NL85 RR4 SL4 RR5 NL6 NL3 RR46 RR9 RR 8 RR3 PR9 RR4 SL34 NL85 NL83 RR46 RR33 RR3 SL93 S L3 SL39 SL3 RR47 NL3 NL34 NL6 NL7 NL8 NL RR46 RR44 RR3 4 RR35 RR4 SL9 RR36 SL3 SL3 NL3 NL RR36 RR36 SL3 RR47 RR47 RR45 Non re g NL33 NL 8 SL 9 SL SL3 NL7 RR43 NL4 NL6 NL RR4 8 NL8 RR5 RR49 NL3 RR57 RR59 RR56 RR55 RR58 RR5 4 SL7 SL7 SL8 S L3 SL S L SL4 SL7 SL SL NL NL Nonreg

Decision Analysis With so much data available, and so many options that can be analyzed, how does one select the best stormwater control program? The least costly that meets the objective? If multiple goals, then possibly not as clear and need a more flexible approach. Consider the following example (a conservation design industrial park in Huntsville, AL): Possible, if only have one numeric standard: If 8% SS reduction goal, the least costly would be wet detention. In this example, grass swales, street cleaning, and catchbasins cannot reach this level of control. If 4% SS reduction goal, then grass swales wins. This site was divided into four subareas, one area has 3 industrial lots (about.6 acres each), plus a large undeveloped area (6. acres) and isolated sinkholes (4.6 acres). The developed area is divided into the following: Roofs plus paved parking:.7 acres Streets (.7 curb-miles): 3. acres Small landscaped areas (B, or sandy-loam soils, but assumed silty soils due to compaction):. acres Conventional drainage system costs (5% over yrs) were estimated to be: Capital cost of project = $96,4 (5) Annual maintenance cost = $,96/year (5) Annual cost of conventional drainage = $6,85 per year 7

WinSLAMM Input Screen for Biofilters Parking lot biofilter example, Portland, OR Top area: 44 ft Bottom area: ft Depth: ft Seepage rate: in/hr Peak to average flow ratio: 3.8 Typical width: ft Number of biofilters: 3 (one per site) Biofilters to drain site runoff (paved parking and roofs) to regional swales: Length: 653 ft infiltration rate in the swale: in/hr swale bottom width: 5 ft 3H:V side slopes longitudinal slope:.6 ft/ft Manning s n roughness coefficient:.4 typical swale depth: ft Regional swales to collect site runoff and direct to wet detention ponds: Cisterns collecting roof runoff at Great Barrier Reef airport, Auckland, NZ Large swale at MS industrial site WI swale having conventional curbs and gutters Rain garden in Madison, WI Another Portland, OR, parking lot biofilter Other Types of Biofilters that can be Evaluated by WinSLAMM 8

WinSLAMM Input Screens for Grass Swales WinSLAMM Input Screens for Wet Detention Ponds Percolation pond, Berlin, Germany Richmond, CA Wet Detention Pond to Treat Runoff from Area Pond Elevation (ft) 3 4 5 6 7 8 9 Full-Sized Pond Area (acres).5.5.5.75. (normal pool elevation, and invert elevation of 3 o v-notch weir).5.5 (invert elevation of flood flow broad-crested weir). Normal maximum elevation during one and two year rains. 3. (approximate maximum pond elevation, or as determined based on flood flow analysis). Additional storage and emergency spillway may be needed to accommodate flows in excess of the design flood flow. Madison, WI Other types of wet ponds and percolation basins that can be evaluated by WinSLAMM: Shopping center, Birmingham, AL Industrial site, Birmingham, AL Percolation pond, Madison, WI Percolation pond, WI 9

Outlet Devices Available in WinSLAMM:. Sharp Crested Weirs. V-Notch Weir 3. Orifice 4. Seepage Basin 5. Natural Seepage 6. Evaporation 7. Other Outflow 8. Water Withdrawal 9. Broad Crested Weir. Vertical Stand Pipe Additional Batch Processor Data (cont.) Stormwater Treatment Option Base, No Controls Option Pond Part. Phos Yield (lbs/yr) 74 5 Volum. Runoff Coeff. (Rv) (est. bio. cond.).9 (poor).9 (poor) % of time flow > cfs 4.5 4 % of time flow > cfs.3.5 SS conc. (mg/l) 4 3 Part. P conc. (mg/l).5.73 Zn conc. (µg/l) 359 8 Option Reg. Swale 79.5 (fair). 78.43 39 Option 3 Site Biofilter Option 4 Small pond Option 5 Pond and reg. swale Option 6 Pond, swale, biofilter Option 7 Small pond and swale Option 8 Small pond, swale and biofilter 7 4 5.5 7.4 (fair).9 (poor).5 (fair).6 (good).5 (fair).7 (good) 4.5.8...5 48 48 3 9 39 53...57.73.95.3 696 5 3 386 39 Batch Processor Data for Combinations of Above Controls Stormwater Treatment Option Annual Total SW Treat. ($/yr) Annual Addit. Drain. System ($/yr) Total Annual ($/yr) Land Needs for SW mgt (acres) Runoff Volume (cf/yr) Part. Solids Yield (lbs/yr) Reduc in SS Yield (%) Base, No Controls 64,3 64,3 5,6, 7,375 n/a Option Pond 9,34 64,3 83,364 4.5 5,57,,9 86 Option Reg. Swale 3,58 6,85 3,8,96, 3,3 55 Option 3 Site Biofilter 3,33 37,38 69,7,75, 68,89 Option 4 Small pond,9 64,3 74,439.3 5,557, 9,55 73 Option 5 Pond and reg. swale Option 6 Pond, swale, biofilter Option 7 Small pond and swale Option 8 Small pond, swale and biofilter,9 54,6 3,367 45,698 6,85 6,85 49,4 54,6 4,7 45,698 4.5 4.5.3.3,844,,3,,887,,53, 4,33,83 6,937 4,5 94 97 9 94 Decision Analysis Approaches ) Specific criteria or limits that must be met. It is possible to simply filter out (remove) the options that do not meet all of the absolutely required criteria. If the options remaining are too few, or otherwise not very satisfying, continue to explore additional options. This example only considers combinations of 3 types of stormwater control devices, for example. There are many others that can also be explored. If the options that meet the absolute criteria look interesting and encouraging, then continue.

Option Pond Option 3 Site Biofilter Control Options Meeting 8% SS Reduction Requirement, Ranked by Stormwater Treatment Option Option Regional Swale Option 4 Half-sized pond Option 5 Pond and reg. swale Option 6 Pond, reg. swale and biofilter Total Annual ($/yr) 83,364 3,8 69,7 74,439 49,4 54,6 Reduction in SS Yield (%) 86 55 73 94 97 Meet 8% particulate solids reduction goal? Yes No No No Yes Yes Rank based on annual cost 5 n/a n/a n/a 3 4 Option 7 Small pond and reg. swale 4,7 9 Yes Option 8 Small pond, reg. swale and biofilter 45,698 94 Yes Attribute Value Ranges, plus Example Ranks and Trade-offs (ranks and trade-offs could vary for different interested parties) Rv Attribute Total annual cost ($/year) Land needs (acres) % of time flow > cfs % of time flow > cfs Particulate solids yield (lbs/yr) Part. Phosphorus yield (lbs/yr) Range of attribute value for acceptable options $4,7 to 83,364.3 to 4.5 acres.6 to.9.5 to 4 % to.5 %,83 to,9 lbs/yr 5.5 to 5 lbs/yr Attribute ranks for selection (after absolute goals are met) 5 7 3 6 4 Trade-offs between remaining attributes..8.3.5.8.7. Sum =. ) Goals that are not absolute (based on methods developed by Keeney, R.L. and H. Raiffa. 976. Decision Analysis with Multiple Conflicting Objectives. John Wiley & Sons. New York.) Utility curves and tradeoffs can be developed for the remaining attributes, after all the absolutely required goals are met. The above example includes attributes of several different types: - costs - land requirements - runoff volume (volumes, habitat responses, and rates) - particulate solids (reductions, yields and concentrations) - particulate phosphorus (reductions, yields and concentrations) - total zinc (reductions, yields and concentrations) Utility Curves for Different Attributes (technically based, would not vary for different interested parties) Volumetric runoff coefficient (Rv) as an indicator of habitat quality and aquatic biology stress: Attribute Expected Utility Value Habitat Value Condition <. Good.. to.5 Fair.75.6 to.5 Poor.5.5 to. Really lousy

.9.8.7.6.5.4.3.. Directly Connected Imperv Area (%) Relationship Between Directly Connecting Impervious Area (%) and the Calculated Rv for Each Soil Type.9.8.7.6.5.4.3.. Directly Connected Impervious Area (%) Rv (sandy soils) Rv Example Utility Values for Other Attributes: Total annual cost: straight line, with $83,364 = and $4,7 =.. % of time flow > cfs Utility value <.5..5 -.75..5.5 >.5 Good Fair Poor Sandy Soil Rv Silty Soil Rv Clayey Soil Rv Example Utility Values for Other Attributes (cont): Part. Phosphorus yield (lbs/yr): straight line, with 5 lbs/yr = and 5.5 lbs/yr =. Land needs (acres): straight line, with 4.5 acres = and.3 acres =. Particulate solids yield (lbs/yr): straight line, with,9 lbs/yr = and,83 lbs/yr =. % of time flow > cfs Utility value <. 3.75 3..5 >

Attribute Values and Associated Utilities for Example Stormwater Control Option Tradeoff Value Option Pond Option 5 Pond and reg. swale Option 6 Pond, reg. swale and biofilter Option 7 Small pond and reg. swale Option 8 Small pond, reg. swale and biofilter Total Annual ($/yr) 83,364 49,4 54,6 4,7 45,698..79.67.87 Land Needs for SW mgt (acres) 4.5 4.5 4.5.3.3 Land.8 Part. Solids Yield (lbs/yr),9 4,33,83 6,937 4,5 Part. Solids.7.76..4.76 Part. Phos. Yield (lbs/yr) 5 5.5 7 Phos...77..4.77 Calculation of Factors for Each Option (Attribute Utility times Attribute Trade-off) Stormwater Control Option Tradeoff Value. factor Land.8 Land factor Part..7 Part. factor Phos.. Phos factor Option Pond Option 5 Pond and reg. swale Option 6 Pond, reg. swale and biofilter Option 7 Small pond and reg. swale Option 8 Small pond, reg. swale and biofilter.79.67.87.58.34..74.8.8.76..4.76.53.7.9.53.77..4.77.9..49.9 Attribute Values and Associated Utilities for Example (cont.) Stormwater Control Option Tradeoff Value Option Pond Option 5 Pond and reg. swale Option 6 Pond, reg. swale and biofilter Option 7 Small pond and reg. swale Option 8 Small pond, reg. swale and biofilter Volumetric Runoff Coefficient (Rv).9.5.6.5.7 Rv.3.5.75..75. % of time flow > cfs 4.5.8 Mod flow.5.5.75..75. % of time flow > cfs.5.5 High flow.8.75...75. Calculation of Factors for Each Option (cont.), Sum of Factors, and Overall Rank Stormwater Control Option Tradeoff Value Rv.3 Rv factor Mod flow.5 Mod flow factor High flow.8 High flow factor Sum of factors Overall Rank Option Pond Option 5 Pond and reg. swale Option 6 Pond, reg. swale and biofilter Option 7 Small pond and reg. swale Option 8 Small pond, reg. swale and biofilter.5.75..75..75.5.3.5.3.5.75..75..5.375.5.375.5.75...75..35.8.8.35.8.5.7455.854.7555.99 5 4 3 3

Many Other Stormwater Controls included in WinSLAMM Maintenance practices (street cleaning) Drainage elements (catchbasins and hydrodynamic devices) Proprietary (manufactured) devices Porous pavement Catchbasins and Catchbasin Cleaning Vactor TM used to clean sewerage and inlets Modified inlet to create catchbasin, Ocean County, NJ Street Cleaning Manual leaf removal, San Jose, CA Street cleaner at the Palace of Engineers, St. Petersburg, Russia Proprietary Stormwater Controls (Hydrodynamic Devices) that use Settling for Treatment and have been Successfully Modeled in WinSLAMM Downstream Defender Vortechs Stormceptor 4

New porous pavement WinSLAMM option currently being developed. Should not use for street or parking lot pavements where groundwater contamination is likely, but for walkways near buildings. HydroInternational UpFlo TM Select bypass option in catchbasin controls to describe hydrodynamic device bypass Upflow Filter can be evaluated in WinSLAMM Essen, Germany Conclusions Madison, WI Calibrated and verified stormwater models can be used to develop a great deal of information concerning many different stormwater management options. Regulations and criteria also need to have different formats to acknowledge site specific problems and objectives. The use of clear and flexible decision analysis techniques, as outlined in this presentation, is therefore important when selecting the most appropriate stormwater control program for a site. 5

Acknowledgements The author would like to acknowledge the support of the Tennessee Valley Authority (TVA), Economic Development Technical Services, and the Center for Economic Development and Resource Stewardship (CEDARS) of Nashville, TN, which has allowed us to develop extensions to WinSLAMM to enable the use of a decision analysis framework in evaluating alternative stormwater management options. The Stormwater Management Authority of Jefferson County, AL, is also acknowledged for their recent support that enabled the cost analyses to be added to WinSLAMM 6