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Four pesticide leaching model codes (PELMO, PESTLA, MACRO, and MIKE SHE) were evaluated and compared through a rigorous validation procedure combined with the application of statistical evaluation criteria. The validation procedure followed a strict Stepwise approach based on suggestions put forward by a European work group on regulatory use of pesticide models (FOCUS). The experimental background comprised two different types of data sets. A laboratory and field lysimeter experiment were conducted on a Danish macroporous sandy loam soil. The aim of the study was to evaluate whether a priori model calibration on controlled laboratory data could improve the physical description of the flow and solute transport in the soil and hence the performance of uncalibrated models for predictions of field lysimeter data. The validation procedure proved to be valuable in terms of ensuring process‐based evaluation of model performances and consistent model comparisons. Controlled laboratory experiments and lysimeter experiments consistently showed very significant influence of preferential flow on water and solute transport. Model codes including a description of preferential flow processes (MACRO and MIKE SHE) required less calibration efforts to meet the selected performance criteria on the investigated soil type than those without such description (PELMO and PESTLA).

Deterministic leaching models are used to estimate regional losses of nitrate from agricultural land to the environment. The estimated leaching losses are associated with uncertainty arising from uncertainty in the input data used. In the present case study we have assessed this uncertainty by use of Monte Carlo analysis, using the Latin hypercube sampling technique. Input data have preferably been adopted from publicly available data. Data which could not be retrieved from the databases was assessed by guided estimates or based on local data.The estimated annual leaching loss from the study region was around 106 kg N ha 71 , which is in agreement with previous findings. The uncertainty in the leaching expressed in terms of coefficients of variation (CV) depended on the agricultural practices. CV's for arable farm rotations, cattle farm rotations, and pig farm rotations were around 20, 30 and 40%, respectively. Breakdown of the total uncertainty into contributions of different error sources did not isolate one single all important source.

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