Fate and Transport Modeling of Pesticides Applied to Turf

Abstract

This research centers on modeling fate and transport processes affecting pesticides applied to turfgrass systems. Interest in predicting pesticide fate and transport from these systems stems from observations of pesticide residues in urban surface and groundwaters, and the need for information with which to assess human health and ecological risks of using these pesticides, total maximum daily load and other water quality management studies. The main processes that affect pesticide fate and transport in turf systems are reviewed, and general magnitudes of each process are reported. Dissipation rates for turf systems are compared to half-life values for aerobic decay in soil, photolysis and field dissipation. From this analysis, microbial decay appears to be a major factor in pesticide dissipation. Decay rates specific for turf are developed based on dissipation rates from these systems. The hypothesis that the use of soil-based decay rates leads to overestimation of pesticide runoff, volatilization and leaching losses from turfgrass systems is tested by means of long term simulations involving diverse turf, climatic and management conditions. Results indicate significant differences in estimations based on soil and turf decay rates as a result of differences in estimating the pesticide?s persistence in the turf foliage and thatch. However, care should be taken when modeling pesticides that are weakly sorbed to organic matter. The research also includes the development of a volatilization model that is based on splitting pesticides into surface and retained deposits and allowing volatilization to occur from the surface deposits only. This model replicated daily volatilization fluxes better than models previously developed for turf, and was incorporated into the Turf Pesticide Model (TPM), which was designed to predict pesticide runoff, leaching, volatilization and decay on a daily basis using relatively few input parameters. Uncalibrated tests of TPM against data from diverse field studies indicated that the model explained 75% of the observed variation in drainage, 63% for pesticide leaching, 65% for runoff volumes, 64% for pesticide loss in runoff, and 62% for pesticide volatilization. TPM can provide information for risk, TMDL, environmental and water quality studies centered on evaluating the impacts of pesticides applied to turf.