Calibration and validation of a dynamic water model in agricultural scenarios.

A dynamic aquatic model (DynA model) was previously developed to predict the fate of a chemical in aquatic scenarios characterized by daily or periodic changes in several input parameters. DynA model is here calibrated with data obtained from the literature in specific unsteady state scenarios, such as those of rice fields. The results obtained for two herbicides (cinosulfuron and pretilachlor) in rice paddy scenarios revealed the capability of the model to accurately predict water and sediment concentrations, as shown by some statistical indicators. Modelling efficiency (EF) values of 0.86-0.99 for the water compartment and of 0.77-0.84 for sediment show the good agreement between predicted and measured concentrations. An "external validation" was performed using measured data for a different herbicide (molinate) applied in a Portuguese paddy rice scenario. A sensitivity analysis for this volatile chemical revealed the influence of some climatic parameters (e.g. temperature) to the model outcomes, such as water and sediment concentrations. This confirmed the capability of DynA model as an efficient tool for the pesticide risk assessment in dynamic scenarios.