Parametric sensitivity analysis of a model simulating pesticide movement in the soil
The ever increasing number of cases of groundwater contamination by pesticides has recently given rise to numerous experimental studies on the tale of these compounds within the soil-water system. In parallel with these experimental studies, the quick and intensive development of numerous simulation models bas emphasized the importance of the various factors and processes controlling the transport of pesticides in the unsaturated zone. The calibration and the validation of such deterministic models, which are especially used in groundwater management, requires the evaluation of several parameters related to the nature of the pesticide as well as to the pedologic and hydrogeological conditions of a given site. The reliability of results predicted by those models is mainly a function of the precision and the representativeness in the evaluation of those parameters at a specific site. The aim of this study was to evaluate the sensitivity of a simulation modes of pesticide movement in the unsaturated zone with regards to the variation in soil physical properties. More particularly, a sensitivity analysis was performed in order to determine the importance of the variation in these parameters with respect to simulation results obtained from the Pesticide Root Zone Model (PRZM). The spatial variability of the composition and structure of the soil, which comes from the site pedogenesis, is the main cause of the variability of the soil water distribution and of the soil transient properties. The sensitivity analysis of a model with respect to the variation in these parameters allows the evaluation of the impact of their representativeness on the model output results. Such an analysis thus allows the determination of an acceptable level of precision (or error) for which an increase of precision in the evaluation of a parameter does not anymore correspond to a significant gain in the representativeness of the model results. It also permits the estimation of the impact of a potential variation of a parameter on the prediction of pesticide transport in the unsaturated zone. The deterministic PRZM modal used in this study has been developed by the US-EPA and devoted to pesticide application on agricultural sites. This modal evaluates the pesticide leaching towards groundwater with respect to the type of culture and pesticide used, the climatic conditions, the soil characteristics and some agricultural practices. Output results from the model can he expressed in concentrations or masses of pesticide, in fluxes or cumulated quantities. Simulations were performed using characteristics and data of the Portneuf region (Quebec). This area of potato farming was until recently one of the Quebec most important sites for aldicarb application before the recommendation of its non use. Cultivated surfaces, which are rather homogeneous, consist of medium-size sand. Simulations were performed river a ten year period (1974 to 1984), implying one application of pesticide a1 the seed-time, and a trop for each year. The parameters of water and pesticide inputs (rain and application rates) are those that induce the higher impact on the simulation results. The simulation results were also influenced by the variation of the field capacity and of the soil bulk density. Temperature, wilting point, maximum evaporation depth and dispersion are the input parameters for which the PRZM model is the less sensitive. The simulation results of pesticide transport, which ultimately consist in predicting the groundwater contamination, are very sensitive to the variations of some physical parameters for which the precision and the representativeness in the measured values are thus very important for the reliability of the results. Considering the spatial variability of a site characteristics, the representativeness of these results is very uncertain if a limited number of data is used in order to determine the mean value. A particular attention has to be focused on the parameters that induce the higher sensitivity of the model. Finally, such a sensitivity analysis shows that a stochastic approach in modelling the solute transport through soil can be a good alternative to take into account the variability of parameters encountered in field situations.