Incorporating Temperature Effects on Pesticide Degradation into a Management Model

The impact of agrochemicals on groundwater quality has been the subject of considerable research and public debate. Mathematical models often are used to predict the fate of these chemicals and to develop regulations. In this research, we modified the pesticide degradation component of a management model to estimate soil temperature with depth and time and to incorporate the effect of temperature variation on the pesticide degradation rate. Estimated pesticide mass leaching beyond a depth of 1 m was two or more orders of magnitude greater when the temperature effect was incorporated into the model. Predicted soil temperatures at four different depths using measured surface soil temperatures followed the seasonal temperature variation of observed data with an average deviation <0.3°C. Among the input parameters analyzed, the amount of pesticide leached was most sensitive to uncertainties in activation energy of a degradation reaction, reference half‐life, and annual mean soil temperature. Uncertainty in annual change in surface soil temperature had a moderate impact on the simulated amount of pesticide leached. Uncertainties in damping depth and time lag of annual minimum temperature had little effect. Uncertainties in model parameters can result in differences on the order of one‐ to fourfold in simulation output. Although these are large, they are clearly much less than the differences of 2 to 8 orders of magnitude, which can occur if temperature effect is ignored. We conclude that models used for pesticide risk assessment should incorporate temperature effects on degradation. The algorithm presented here can be incorporated readily into many leaching models.