Coupling 1D Monte-Carlo simulations and geostatistics to assess groundwater vulnerability to pesticide contamination on a regional scale

A method to predict groundwater vulnerability to pesticide contamination on a regional scale has been developed and applied to a part of the upper Rhone river valley in Western Switzerland. Stochastic application of deterministic pesticide leaching models (Monte-Carlo), along with geostatistical interpolation techniques, were used to map both vulnerability levels and uncertainties. The various tested leaching models (numerical and analytical solutions of the convection–dispersion equation, capacitive model) lead to similar outcomes. The resulting maps show very high vulnerabilities. However, uncertainties are large, ranging from 20–30% for vulnerability indices between 0 and 1. Variations in pesticide properties (40–50%), water table depth (30–40%) and organic carbon content (20%) account for almost all the uncertainties on predicted contamination levels.