Date of this Version
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 previously developed to estimate landscape vulnerability to pesticide runoff and leaching at a watershed or regional scale using Soil Survey Geographic (SSURGO) data. Because mitigation of contamination requires implementation of best management practices, the model was adapted to the field scale. The field-scale model was developed based on a Digital Elevation Model (DEM) with 5 ´ 5 m resolution for a research site in Boone County, Missouri. The model uses inputs and functions associated with hydrologic and pesticide dissipation processes. These include saturated hydraulic conductivity of the soil, pH, organic matter, clay content, clay mineralogy, slope, unfilled pore volume above a restrictive layer, and soil moisture content along with pesticide adsorption intensity, relative persistence, and susceptibility to abiotic hydrolysis. Input data were obtained from field measurements, Agricultural Policy/Environmental eXtender (APEX) model soil moisture output, the Soil Survey Geographic (SSURGO) database (flooding frequency class), and pesticide property references. The hydrologic component of the model was converted to a dynamic function using APEX estimates of soil moisture and the model was coded into the ESRITM (Environmental Systems Research Institute, Inc., Redlands, CA) ArcGIS (10.0) Model Builder. Sensitivity analyses were performed to assess the weighting of the restrictive layer modifier of the Index Surface Runoff (ISRO) function and to evaluate the hydrolysis time frame. Model estimates of atrazine remaining in the field (assuming no previous runoff or leaching losses) were significantly related to measurements of atrazine in runoff made at the field outlet for odd (corn) years from 1993 to 2001. However, estimates of remaining pesticide exceeded field measurements. The model can be used to identify vulnerable areas within agricultural fields and target sites for implementation of best management practices (BMPs) and regulatory strategies to effectively address water quality issues.
Advisor: Patrick J. Shea