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ARS Home » Midwest Area » St. Paul, Minnesota » Soil and Water Management Research » Research » Publications at this Location » Publication #340054

Title: Mechanistic modeling & effectiveness of buffer strips for pesticide regulatory frameworks

item PEREZ-OVILLA, OSCAR - Bayer Cropscience
item MUNOZ-CARPENA, RAFAEL - University Of Florida
item Rice, Pamela
item MCCONNELL, LAURA - Bayer Cropscience
item XU, TIANBO - Bayer Cropscience

Submitted to: American Chemical Society Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 4/24/2017
Publication Date: 8/20/2017
Citation: Perez-Ovilla, O., Munoz-Carpena, R., Rice, P.J., Mcconnell, L., Xu, T. 2017. Mechanistic modeling & effectiveness of buffer strips for pesticide regulatory frameworks. American Chemical Society. August 20-24, 2017, Washington, DC. 92:60..

Interpretive Summary:

Technical Abstract: Vegetative Filter Strips (VFS) have been used as an effective conservation practice in agricultural areas for controlling and mitigate the effect of sediment, nutrients and pesticides loads into water bodies. In addition to the agricultural sector, another important use of VFS for controlling plagues is in golf courses. However, very limited literature is available about their effectiveness in turf-type grasses. An experiment was designed to explore the effectiveness of turf-like VFS for controlling two pesticides with different sorption properties. The effect of two buffer lengths of 25 and 50 ft and a 1-in-10 year storm event with duration of 2 hours was also explored. Results showed a ranged of removal efficacy from 50-80%. A piecewise approach using the mechanistic model VFSMOD helped to explain the results. First, an inverse calibration procedure was used for the out hydrographs and sediment graphs for each one of the replicated. A final step involved the estimation of the pesticide removal efficacy based on a semi-empirical equation which was coupled with VFMSOD. Preliminary results indicate that the mechanistic approach used by VFSMOD is helpful to understand the water and sediment dynamics within the filter. For the pesticide prediction, the tool is able to properly predict the removal of pesticides within the limits of the accuracy of the semi-empirical equation.