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The SPEC model (Predicted Environmental Concentrations in agricultural Soils) was developed and improved for the simulation of pesticide runoff. The model was applied to the Sakaecho upland bare soil field (Tokyo, Japan) to predict runoff water, sediment concentration in runoff water, pesticide concentrations in runoff water, and runoff sediment (clothianidin and imidacloprid) under artificial rainfall conditions. The results showed that the simulated time to first runoff agreed very well with the observed data. The simulated cumulative runoff, sediment yield, and imidacloprid concentration in sediment agreed well with the observed data (Nash–Sutcliffe Efficiency (NSE)>0.75). The simulated runoff rate agreed reasonably well with the observed data (NSE >0.5). The predicted clothianidin concentrations in sediment and in runoff water had acceptable agreement with the observed data (NSE >0). The results implied the model’s potential to predict runoff water, sediment yield, and pesticide runoff.

A pesticide fate and transport model, SPEC, was developed for assessing Soil-PEC (Predicted Environmental Concentrations in agricultural soils) for pesticide residues in upland field environments. The SPEC model was validated for predicting the water content and concentrations of atrazine and metolachlor in 5-cm deep soil. Uncertainty and sensitivity analyses were used to evaluate the robustness of the model's predictions. The predicted daily soil water contents were accurate regarding the number of observation points (n=269). The coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE ) were equal to 0.38 and 0.22, respectively. The predicted daily concentrations of atrazine and metolachlor were also satisfactory since the R2 and NSE statistics were greater than 0.91 and 0.76, respectively. The field capacity, the saturated water content of the soil and the Q10 parameter were identified as major contributors to variation in predicted soil water content or/and herbicide concentrations.

This paper demonstrates the procedures for probabilistic assessment of a pesticide fate and transport model, PCPF-1, to elucidate the modeling uncertainty using the Monte Carlo technique. Sensitivity analyses are performed to investigate the influence of herbicide characteristics and related soil properties on model outputs using four popular rice herbicides: mefenacet, pretilachlor, bensulfuron-methyl and imazosulfuron. Uncertainty quantification showed that the simulated concentrations in paddy water varied more than those of paddy soil. This tendency decreased as the simulation proceeded to a later period but remained important for herbicides having either high solubility or a high 1st-order dissolution rate. The sensitivity analysis indicated that PCPF-1 parameters requiring careful determination are primarily those involve with herbicide adsorption (the organic carbon content, the bulk density and the volumetric saturated water content), secondary parameters related with herbicide mass distribution between paddy water and soil (1st-order desorption and dissolution rates) and lastly, those involving herbicide degradations.