1 / 22

GIS Modeling of Source Areas of Nonpoint Source Pollution

GIS Modeling of Source Areas of Nonpoint Source Pollution. James Zollweg, Ph.D. SUNY-Brockport Earth Sciences Water Resources Program Geographic Information Systems Program. Overview. Brief Biography Mapping and Illustration Using GIS Computation of P-Index

jenna
Download Presentation

GIS Modeling of Source Areas of Nonpoint Source Pollution

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. GIS Modeling of Source Areas of Nonpoint Source Pollution • James Zollweg, Ph.D. • SUNY-Brockport Earth Sciences • Water Resources Program • Geographic Information Systems Program USDA Conesus Lake Project

  2. Overview • Brief Biography • Mapping and Illustration Using GIS • Computation of P-Index • Runoff and Soil Moisture Modeling with SMR • Hydrologic and Chemical Controls on P Export • previous results • new directions USDA Conesus Lake Project

  3. Overview • Brief Biography • Mapping and Illustration Using GIS • Computation of P-Index • Runoff and Soil Moisture Modeling with SMR • Hydrologic and Chemical Controls on P Export • previous results • new directions USDA Conesus Lake Project

  4. Brief Biography • 1994: Ph.D. (Cornell University) – “Effective Use of GIS in Rainfall-Runoff Modeling” • 1993-96: USDA – ARS - Pasture Systems and Watershed Management Research Lab – “Optimizing Nutrient Management to Sustain Agricultural Ecosystems and Protect Water Quality” • 1996-present: SUNY-Brockport – GIS and Water Resources (wetlands, flood forecasting) USDA Conesus Lake Project

  5. USDA Conesus Lake Project

  6. Overview • Brief Biography • Mapping and Illustration Using GIS • Computation of P-Index • Runoff and Soil Moisture Modeling with SMR • Hydrologic and Chemical Controls on P Export • previous results • new directions USDA Conesus Lake Project

  7. Mapping / Illustration Using GIS • Reports and Presentations • Public information • www.blackcreekwatershed.org • Data Explorations • Visualization • discovery • insight USDA Conesus Lake Project

  8. Mapping / Illustration Using GIS USDA Conesus Lake Project

  9. Overview • Brief Biography • Mapping and Illustration Using GIS • Computation of P-Index • Runoff and Soil Moisture Modeling with SMR • Hydrologic and Chemical Controls on P Export • previous results • new directions USDA Conesus Lake Project

  10. Soil Erosion Irrigation Erosion Runoff Class Soil P-Test P Fertilizer Appl. Rate P Fertilizer Appl. Method Organic P Source Appl. Rate Organic P Source Appl. Method Computation of P-Index • Preservation of spatial variability • Computational efficiency • Visualization of results • Facilitates improved understanding of physical interactions Phosphorus Index USDA Conesus Lake Project

  11. Overview • Brief Biography • Mapping and Illustration Using GIS • Computation of P-Index • Runoff and Soil Moisture Modeling with SMR • Hydrologic and Chemical Controls on P Export • previous results • new directions USDA Conesus Lake Project

  12. Runoff and Soil Moisture Modeling with SMR • Variable Source Area Hydrology • Critical Source Areas for Nonpoint Source Pollution USDA Conesus Lake Project

  13. Runoff and Soil Moisture Modeling with SMR • SMR – The Soil Moisture Routing Model • Product of Zollweg’s Thesis • GIS is the Ideal Environmental Modeling Platform • Spatially-distributed, Physically-based USDA Conesus Lake Project

  14. Runoff and Soil Moisture Modeling with SMR Private Function HM_NeighborFlow(sStorage As String, _ pInterflowRaster As IRaster, ierr As Integer) As Boolean '----------------------------------------------------------------------------- ' The storage is adjusted for the amount leaving, the interflow and the amount ' entering from neighbor cells. The maps north, northeast, east, southeast, ' south, southwest, west and northwest represent the fraction of flow heading ' in 'that' direction from the current cell. Therefore to find the amount ' entering the current cell one needs to look at the neighbor cells and the ' corresponding maps which point to the current cell. For example, if the ' current cell is (i,j) and one looks to the north (i-1,j) one would use the ' south map to get the fraction of flow since the current cell is south of its ' north neighbor. ' --------------------------------------------------------------- ' | cell: (i-1, j-1) | cell: (i-1, j) | cell: (i-1, j+1) | ' | map: southeast | map: south | map: southwest | ' --------------------------------------------------------------- ' | cell: (i-1, j) | cell: (i, j) | cell: (i+1, j+1) | ' | map: east | map: none | map: west | ' --------------------------------------------------------------- ' | cell: (i+1, j-1) | cell: (i+1, j) | cell: (i+1, j+1) | ' | map: northeast | map: north | map: northwest | ' --------------------------------------------------------------- • Coded and Running in Lennon Hall Using Visual BASIC within ArcGIS 8.2 • Complete Control of Code • Easy to Integrate Additional Environmental Modeling Concepts USDA Conesus Lake Project

  15. Overview • Brief Biography • Mapping and Illustration Using GIS • Computation of P-Index • Runoff and Soil Moisture Modeling with SMR • Hydrologic and Chemical Controls on P Export • previous results • new directions USDA Conesus Lake Project

  16. (1996) USDA Conesus Lake Project

  17. Brown Watershed – Tributary of WD38, Klingerstown, PA USDA Conesus Lake Project

  18. USDA Conesus Lake Project

  19. USDA Conesus Lake Project

  20. Overview • Brief Biography • Mapping and Illustration Using GIS • Computation of P-Index • Runoff and Soil Moisture Modeling with SMR • Hydrologic and Chemical Controls on P Export • previous results • new directions USDA Conesus Lake Project

  21. More Concepts to Try • Chemical dynamics of P Export • Transport processes • Erosion modeling and sediment transport • Pathogen transport USDA Conesus Lake Project

  22. Goals • Support “mechanics” of project • Better understanding of watershed P dynamics • Continue my work and achieve mutual benefit! USDA Conesus Lake Project

More Related