Submitted to: American Water Resources Association Spring Specialty Conference
Publication Type: Abstract only
Publication Acceptance Date: 11/20/2012
Publication Date: 3/25/2013
Citation: Shea, P.J., Milner, M., Hosseini, A., Lerch, R.N., Baffaut, C., Walter-Shea, E.A. 2013. Process-based modeling of landscape vulnerability to off-site pesticide transport. American Water Resources Association Spring Specialty Conference. 1. Interpretive Summary:
Technical Abstract: Identifying areas vulnerable to off-site agrichemical movement and surface and ground water contamination through conventional data collection is labor-intensive, costly and time-consuming. To promote efficient pesticide use and protect water resources, a process-based index model was developed to assess landscape vulnerability to pesticide runoff and leaching. The model is based on the physicochemical properties of the pesticide, including adsorption (organic carbon partition coefficient), relative persistence (half-life), and susceptibility to abiotic hydrolysis, along with landscape characteristics, including the soil saturated hydraulic conductivity, organic matter, clay content, pH, depth to restrictive layer, soil texture, clay mineralogy, whole fraction erodibility, drainage class, flooding frequency and slope. The watershed-scale (regional) model incorporates pesticide dissipation and hydrologic functions and utilizes the 1:24,000-scale USDA-NRCS Soil Survey Geographic Database (SSURGO). Because mitigation of contamination requires implementation of best management practices, the model was adapted to a field scale for a research site in Boone County, Missouri. Available field-scale data included saturated hydraulic conductivity, pH, organic matter, 5 x 5 m resolution elevation from which slope was derived, and Agricultural Policy/Environmental eXtender (APEX)-modeled daily moisture content. Mathematical functions were imported into ArcGIS v10.0 Model Builder. Validation of the field-scale model using five years of atrazine transport data demonstrated its application to estimate losses in runoff. The regional and field-scale models can help identify vulnerable areas within watersheds and agricultural fields to target and prioritize sites for implementation of best management practices and regulatory strategies that effectively address water quality issues.