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The leaching processes of the insecticide imidacloprid [1‐(6‐chloro‐3‐pyridinylmethyl)‐N‐nitro‐2‐imidazolidinylideamine] and the fungicide procymidone [N‐(3,5‐dichlorophenyl)‐1,2‐dimethyl‐1,2‐cyclopropanedicarboximide] in a greenhouse soil from the southeastern of Spain were investigated. Four separate pesticide applications were made at dose rates considerably higher than the recommended in normal agronomic practice, representing a worst case scenario. Soils samples were taken to a depth of 40 cm at time intervals after each application and analyzed by high performance liquid chromatography (HPLC). The partition coefficients (Kd) of the samples for imidacloprid and procymidone were calculated by carrying out batch experiments and fitting the experimental data point to the linear isotherm equation. Soil tension, water content, and temperature measurements were also determined during all the experiments. Although the results show a high degree of variability, rapid transport of pesticides through the soil occurred which increases the possibility of groundwater pollution. The leaching of these pesticides, particularly procymidone, generally thought of as immobile, might be possible through formation of stable soluble organic fraction–pesticide interactions in solution, allowing an increased groundwater contamination potential.

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Effective prediction of pesticide fate using mathematical models requires good process descriptions in the models and good choice of parameter values by the user. This paper examines the ability of seven pesticide leaching models (LEACHP, MACRO, PELMO, PESTLA, PLM, PRZM and VARLEACH) to describe an arable field environment where sunflowers are grown in the Po Valley, northern Italy. Two pesticides were considered, aclonifen and ethoprophos. The models were evaluated in terms of their ability to reproduce field data of soil water content and pesticide residues in the soil and ground water. The evaluation was based on a combination of calibrated and uncalibrated runs. The results from the models were compared with each other to explore the differences between the models. The models varied in their ability to predict soil water content in the summer: the capacity models PRZM, PELMO and VARLEACH predicted less drying than MACRO, PESTLA, PLM and LEACHP. The models varied in their ability to simulate the persistence of the pesticides in the soil. Differences in the simulated pesticide degradation rate were observed between the models, due to variations in the simulated soil water content and soil temperature, and also differences in the equation linking degradation rate to soil water content. There were large differences among the predictions of the models for the mean leaching depth of ethoprophos. PRZM, PELMO, PESTLA and LEACHP all showed similar mean leaching depth to each other, whereas VARLEACH predicted lower ethoprophos mobility and PLM and MACRO predicted greater mobility. All the models overpredicted dispersion of ethoprophos through the soil profile, as compared to the field data. None of the models was able to simulate the field data of rapid leaching of pesticide to ground water except PLM after calibration of the percentage of macropores in the mobile pore space. More work is required in the parameterisation of macropore flow for those models that include this process.

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