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Characterizing agrochemical patterns and effective BMPs for surface waters using mechanistic modeling and GIS

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Abstract

Monitoring programs in the agriculturally intense San Joaquin River Valley of California have periodically found organophosphate (OP) insecticide concentrations, predominantly chlorpyrifos, diazinon and methidathion, at levels high enough to cause mortality for the aquatic invertebrate Ceriodaphnia dubia. These detections are likely the result of off-site movement from treated fields. However, the relative significance and magnitude of off-site transport pathways cannot be readily deduced from monitoring data alone. Therefore, a comprehensive modeling system has been constructed to estimate temporal and spatial pesticide source magnitudes and to follow the pesticide dissipation pathways once in surface water. The USEPA models HSPF and PRZM3 were used for the hydrology and non-point source predictions, respectively. Spray drift was accounted for using the mechanistic model AgDrift. The Orestimba Creek Watershed in the San Joaquin Valley was characterized and used as a typical watershed for this region. Representative transport pathways were ranked and quantified, and numerical implementation of best management practices (BMPs) determined which practice may have the highest likelihood for reducing pesticide loadings. Approximately 85% of the predicted chlorpyrifos mass detected between May 1, 1996, and April 30, 1997 resulted from drift, with the largest contributions coming from walnut orchards immediately adjacent to Orestimba Creek. Various simulated drift mitigation measures suggest chlorpyrifos mass loadings can be decreased by over 90% depending upon the type of mitigation chosen. Imposed drift BMPs should be effective in reducing chlorpyrifos levels found in surface waters of the San Joaquin valley if the Orestimba creek watershed is considered representative of watersheds found in this area of California.

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Cryer, S.A., Fouch, M.A., Peacock, A.L. et al. Characterizing agrochemical patterns and effective BMPs for surface waters using mechanistic modeling and GIS. Environmental Modeling & Assessment 6, 195–208 (2001). https://doi.org/10.1023/A:1011978420760

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