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Non-Point Source Pollutant Modeling

Non-Point Source Pollutant Modeling. Analysis and Prediction David Munn. Non-Point Source Pollution. Does not come from a single source Results from pollutants being washed out of large areas during storms Difficult to model without use of GIS or current NPSP models. Goals.

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Non-Point Source Pollutant Modeling

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  1. Non-Point Source Pollutant Modeling Analysis and Prediction David Munn

  2. Non-Point Source Pollution • Does not come from a single source • Results from pollutants being washed out of large areas during storms • Difficult to model without use of GIS or current NPSP models

  3. Goals • Predicting pollutant runoff loads • Defining problem areas within the Watershed • Determine what factors effect pollutant loading • Determine streams with highest impact • Pollutants considered: • BOD • Suspended Solids • Total Phosphorous • Total Nitrogen

  4. Study Area • Brazos County • Buffered boundary

  5. Process Overview • Gather data • Data preparation • Reproject grids and shapefiles • Clip themes and set analysis extents • Calculate curve numbers • Delineate watersheds • Calculate pollutant contribution • Determine weighted accumulation • Analyze data

  6. Data/Themes • DEM • TNRIS • Soil Classification • STATSGO • County Boundaries • ESRI, Tiger files • Land Use/Land Cover • Txdata, Provided by Dr. Olivera • Precipitation • Txdata, Annual and Monthly • LULC Pollutant Contribution Data • Cornell University Hydraulics Study

  7. Reprojecting • Reprojected grids using ArcInfo-Workstation • Reprojected geographic shapefiles using CRWR-Vector • Data Already in a Projection was reprojected using ArcCatalog • Final Projection: State Plane 1927 • Central Texas, Zone 5376 • Units = feet

  8. CRWR-Prepro Burned in Streams Filled Sinks Determined Flow Direction Determined Flow Accumulation Defined Streams Segmented Streams Defined Outlets Delineated Watersheds Vectorized Grids Delineating Watersheds

  9. Curve Numbers • Used to determine runoff • STATSGO data spatially documents soil types (component makeup) • Scripts provided by CVEN 689 Website • Soilgrp script – calculates % of hydrologic groups per soil type • cn script – creates curve numbers based on soil composition

  10. Rainfall given per month (January) Calculate Run-off (mm) using SCS method Map Calculator combined formulas with rainfall and CN Created new grid giving run-off depth per cell Run-off

  11. Pollutant Contributions Q (mm) Cell size (ft2) Pollutant Concentration (mg/l) = Mass (mg) * Map Calculator

  12. Pollutant Flow/Accumulation • Weighted flow accumulation • Executed in ArcInfo • Assigns weights to cells based on a Grid Weights Direction Accumulation

  13. Analysis • Determine what land-uses and soil types contribute the largest amount of pollutants • Determine what rivers suffer the greatest impact • Locate areas that contribute large masses of pollutants

  14. Land Use Relationships (Zonal Summaries)

  15. Soil Type Relationships(Zonal Summaries)

  16. Impacted Rivers • Method • Map query • Changed to shapefile • Results too dependent on general accumulation • More statistical work needed

  17. Areas of Concern * TP / TN * BOD / SS

  18. Conclusions • Urban areas contributed the largest mass of BOD and suspended solids per unit area • Agricultural areas contributed the largest mass of Nitrogen and Phosphorous / area • Rivers > 700,000 cell accumulation were impacted • Soil types differed in impact between pollutants • Nutrients: Crocket-Luling-Benchley & Zack-Zulch-Booneville • BOD and Suspended Solids Zack-Zulch-Booneville

  19. Future Applications • Determining Pollutant Concentrations • Calculate run-off volume using weighted accumulation • Sum run-off volumes with base flows • Calculate in-stream concentrations • Better Statistical Analyis of Impacted Rivers

  20. Problems • REPROJECTING!!!!!!! • Calculating pollutant contributions (map calculator) • Floating point analysis

  21. QUESTIONS What up?

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