Utilizing simulated weather patterns to predict runoff exceedence probabilities for highly sorbed pesticides

Weather patterns have tremendous variability from year-to-year which subsequently influences yearly edge-of-field surface runoff for entrained agrochemicals. Pesticide behavior at a specific field is often predicted using an environmental model(s) with multiple years of weather to deduce annual exceedence probability curves for chemical exposure. The likelihood for a given simulation year to exceed a threshold value at any given field can be computed based upon analysis of hundreds to thousands of model results where only yearly weather patterns are allowed to change. Although effective, this approach often cannot be used in regional exposure analysis due to the prohibitively large combination of fields and weather scenarios requiring simulation. A simple regression method has been developed to reduce modeling runs required for regional assessments through ranking of annual precipitation patterns for exceedence probability predictions with respect to edge-of-field pesticide runoff. A weather year can then be picked from a weather library and used with a deterministic model to estimate edge-of-field runoff at a certain yearly exceedence probability for the specific field in question. This methodology has proven robust enough for successful extrapolation to other states having diverse weather conditions without further calibration. Examples using the USDA model GLEAMS are presented.