1 / 38

Objective

Water Quality Modeling: Estimating Pollutant Load Reductions for Project Reporting Scott Daly Utah Division of Water Quality 801.536.4333 sdaly@utah.gov. Objective. UAFRRI – Utah Animal Feedlot Runoff Risk Index Overview Data Inputs STEPL – Spreadsheet Tool for Estimating Pollutant Loads

arch
Download Presentation

Objective

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Water Quality Modeling:Estimating Pollutant Load Reductions for Project ReportingScott DalyUtah Division of Water Quality801.536.4333sdaly@utah.gov

  2. Objective • UAFRRI – Utah Animal Feedlot Runoff Risk Index • Overview • Data Inputs • STEPL – Spreadsheet Tool for Estimating Pollutant Loads • Overview • Data Inputs • Model Setup • Limitations • Data Sources • WQ Models and Project Planning • Discussion

  3. Utah Animal Feedlot Runoff Risk Index (UAFRRI) • MS Excel spreadsheet • Nutrient loading and load reduction estimates (N, P, and BOD5) • Feedlot Risk Assessment

  4. Spreadsheet Tool for Estimating Pollutant Loads(STEPL) • MS Excel spreadsheet • Easy to use • Inputs can be modified by user (optional) • Calculates nutrient (N, P, and BOD5) and sediment loads by land use type • Calculates expected load reductions • Data driven and highly empirical

  5. STEPL Process Processes Load User Input Land Uses Runoff BMPs/LIDs Nitrogen Animals Groundwater Sheet/Rill Erosion Phosphorus • Precipitation • Irrigation Load Reduction BOD Soil and USLE Parameters Gully/ Streambank Erosion Sediment • Septic Systems • Direct Discharges Pollutant Transport

  6. STEPL Web Site Link to download URL: http://it.tetratech-ffx.com/stepl

  7. STEPL Main Program • Run STEPL executable program (STEPL.exe) • Start All Programs STEPL

  8. STEPL Spreadsheet Composed of four worksheets

  9. Data Input

  10. Universal Soil Loss Equation (RUSLE) • USLE = R*K*LS*C*P Where: • R = rainfall and runoff factor • K = soil erodibility factor • LS = slope length and steepness factor • C = cover management factor • P = support practice factor

  11. USLE – LS Factor

  12. Typical USLE C and P Values Support Practice Factor

  13. Optional Input Data

  14. SCS Curve Number – Hydrologic Soil Group • Group A –Low overland Flow; high infiltration capacity; well-drained (Sand and Gravel) • Group B –Moderate minimum infiltration capacity; moderately- to well- drained; moderately-course grained (Sandy Loam) • Group C – Low minimum infiltration capacity; moderately fine- to fine-grained soils • Group D – very low infiltration capacity; high overland flow potential (Clay)

  15. Curve Numbers for Arid and Semi-arid Rangelands Hydrologic Soil Hydrologic Land Use/Cover Condition Group A B C D ------------------------------------------------------------------------------------------------------------------------------------------- Herbaceous - grass, weeds & low- Poor /a - 80 87 93 growing brush; brush the minor Fair - 71 81 89 component Good - 62 74 85 Oak/aspen - oak brush, aspen, Poor - 66 74 79 mountain mahogany, bitter brush, Fair - 48 57 63 maple and other brush Good - 30 41 48 Pinyon/juniper - pinyon, juniper or Poor - 75 85 89 both; grass understory Fair - 58 73 80 Good - 41 61 71 Sagebrush with grass understory Poor - 67 80 85 Fair - 51 63 70 Good - 35 47 55 Desert scrub - saltbush, greasewood, Poor 63 77 85 88 creosotebrush, blackbrush, bursage, Fair 55 72 81 86 palo verde, mesquite and cactus Good 49 68 79 84 ------------------------------------------------------------------------------------------------------------------------------------ a. Poor: < 50% ground cover (litter, grass and brush overstory); Fair: 50 to 75% ground cover; Good: 75% ground cover. • SCS Curve Number Computations.pdf Appendix A Table 2-2

  16. CN - Antecedent Moisture Conditions

  17. Populate STEPL Input Tables

  18. BMPs

  19. Urban BMP Tool

  20. Gully/Streambank Loading

  21. Add New Data to BMP List • In STEPL customized menu, click “View/Edit BMP List” • BMP List worksheet is shown, add or delete BMPs

  22. BMP Efficiency Calculator

  23. Add New Data to BMP List Update BMP button (BMPList worksheet) • Click “Update BMP Data” button to update the BMP selections in the BMPs worksheet • Click “Save Updates” to save changes to text files (comma delimited) • C:or D:\Stepl\Support\AllBMPstepl.csv • C: or D:\Stepl\Support\AllBMP.csv New BMP added! (BMPs worksheet) New BMP added!

  24. STEPL BMP Calculator • Calculates combined efficiency of a BMP train for a given land use.

  25. Series Reduced tillage Parallel Conventional tillage Reduced tillage Conventional tillage Reduced tillage Filter strip Settling Basin Combination STEPL BMP Calculator Filter strip

  26. STEPL BMP Calculator • Describe schematically BMP configuration • Number and linkages • BMP type and efficiency • Land use area • Calculate combined efficiency • Enter calculated efficiency in table 7 on the BMP tab 4. Calculate combined efficiency 1. Add BMP box 5. Delete Connection 2. Draw Connection 3. Move BMP box

  27. BMP Calculator - Series 3 1 2 Reduced Tillage Filter Strip Load

  28. BMP Calculator - Parallel 3 1 2 Each box represents 100 ac Streambank Stabilization Contour Farming Load

  29. Populate STEPL BMP Tables

  30. Total Load

  31. Graphs

  32. Other Ways to Use STEPL • Model changes in land use and runoff before and after BMPs instead of modeling efficiencies • Estimate BMP efficiencies BMP efficiency = (Pre BMP load – Post BMP load) / Pre BMP load • Project planning

  33. STEPL as a Project Planning Tool • Compare two projects to determine which has the most potential for load reduction • Compare multiple BMPs within the same project area

  34. Model Limitations • Driven by empirical relationships • Emphasis for project-specific data • Model calibration/validation • Not easy to calibrate • Designed to produce “rough” loading estimates, NOT accurate or precise estimates

  35. Discussion

  36. Data Resources • Table 1. Input watershed land use area (ac) and precipitation (in) • 1. Precipitation: (a). Local observation (b). http://www.wrcc.dri.edu/ • (c). http://www.wcc.nrcs.usda.gov/snow/ (d). nws.noaa.gov • Table 4. Modify the Universal Soil Loss Equation (USLE) parameters • K Factor - http://websoilsurvey.nrcs.usda.gov/app/HomePage.htm • LS Factor – Field measurements for slope length (L) and slope (S), then consult the following tables. USDA Agricultural Handbook 703: Tables 4-1 through 4-9. • Cover Management Factor – USLE Appendix A - Cover Managment Factor.doc and http://www.iwr.msu.edu/rusle/doc/cfactors.pdf • Support Practice Factor – http://www.omafra.gov.on.ca/english/engineer/facts/00-001.htm Table 5 • Table 5. Select average soil hydrologic group (SHG) • Soil Hydrologic Group = Hydrologic Soil Group • http://websoilsurvey.nrcs.usda.gov/app/HomePage.htm

  37. Data Resources • Table 6. Reference runoff curve number (may be modified) 1. SCS Runoff Curve Number Computations.pdf, Appendix A Table 2-2

More Related