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. Mathematic al models often are use d to predict the fate of these chemicals and to develop regulations. In thi s 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. Esti mated pesticide mass leaching beyond a depth of Im was two or more orders o f magnitude greater when the temperature effect was incorporated into the m odel. Predicted soil temperatures at four different depths using measured s urface soil temperatures followed the seasonal temperature variation of obs erved data with an average deviation <0.3 degrees C. Among the input parame ters analyzed, the amount of pesticide leached was most sensitive to uncert ainties 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 pesticid e leached. Uncertainties in damping depth and time lag of annual minimum te mperature had little effect. Uncertainties in model parameters can result i n differences on the order of one- to fourfold in simulation output. Althou gh 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. W e conclude that models used for pesticide risk assessment should incorporat e temperature effects on degradation. The algorithm presented here can be i ncorporated readily into many leaching models.