Field-Scale Adaption of a Process-Based Index Model for Landscape Vulnerability to Surface and Ground Water Contamination.

Identifying vulnerable areas within agricultural fields through conventional data collection methods is highly labor intensive, time-consuming, and cost-prohibitive. To promote efficient agrichemical use and protect water resources, a process-based index model was developed. The model applies mathematical functions based on the NRCS County Soil Survey Geographic database (SSURGO) to assess landscape vulnerability to ground and surface water contamination from agrichemicals on a watershed level. Landscape characteristics for the watershed model include saturated hydraulic conductivity, slope, slope length, and erodibility. Physicochemical properties of pesticides, including adsorption (organic carbon partition coefficient), relative persistence (half-life), and susceptibility to abiotic hydrolysis are used to evaluate and compare losses among pesticides. By adapting the model to the field scale, we can identify locations that contribute most to agrichemical loss, so appropriate best management practices can be implemented. Hydrologic functions for surface soil (15 cm), soil organic matter and pH, are coupled with landscape properties to identify areas within the field most prone to leaching and runoff. Landscape characteristics are extracted based on digital elevation model (DEM) data at a 1-10 m resolution. Where field-scale data are unavailable, values are assigned based on SSURGO data, within a realistic range, and model output is generated. All equations used in the model were imported into ArcGIS and vulnerable areas within a field are identified by stacking maps generated in GIS.