Abstract

This research evaluated the predictive ability of a pesticide fate and transport model to simulate the potential for pesticide leaching from slow-release insecticide-treated corn seeds. No studies in the literature report model evaluation for pesticide-treated seeds. The column studies consisted of ten 60 cm soil columns of silt loam soil, each planted with one corn seed treated with the active ingredient of an experimental pesticide. The columns were modeled using the Root Zone Water Quality Model (RZWQM), which is capable of simulating slow-release, instantaneous equilibrium (IE) and equilibrium kinetic (EK) sorption, and irreversible binding. The model was calibrated for hydrology (i.e., leachate from the bottom of the soil columns), crop growth, and total pesticide in the soil profile. Measured concentrations were compared to model predictions for IE and EK sorption scenarios across a range of sorption parameters derived from batch and time-dependent sorption studies. Modeling scenarios failed to predict the observed pesticide confinement (70% of applied pesticide) to primarily the upper 15 cm of the soil profile, with 1% to 20% of applied in the upper 15 cm for IE sorption and 3% to 18% of applied for EK sorption at the end of the simulation period. Both IE and EK sorption scenarios failed to predict pesticide in leachate (observed cumulative of 0.12% of applied) unless using minimum IE and EK sorption parameters. Model deviations from observations were hypothesized to be due to the model representing a theoretical two-dimensional process in one-dimension and the potential for preferential flow paths formed by root formation. Long-term (i.e., 20-year) simulations suggested that significant differences (i.e., average of 8% compared to less than 1% cumulative leaching) arise between IE and EK sorption after several plantings of the pesticide-treated seed. The error in assuming IE sorption for an EK sorption process is negligible over the short term but increases with subsequent chemical applications over the long term.

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