Stochastic modelling of pesticide transport to drinking water sources via runoff and resulting human health risk assessment

Abstract

A modelling framework was developed to facilitate a probabilistic assessment of health risks posed by pesticide exposure via drinking water due to runoff, with the inclusion of influential site conditions and in-stream processes. A Monte-Carlo based approach was utilised to account for the inherent variability in pesticide and population properties, as well as site and climatic conditions. The framework presented in this study was developed with an ability to integrate different data sources and adapt the model for various scenarios and locations to meet the users' needs. The results from this model can be used by farm advisors and catchment managers to identify lower risk pesticides for use for given soil and site conditions and implement risk mitigation measures to protect water resources. Pesticide concentrations in surface water, and their risk of regulatory threshold exceedances, were simulated for fifteen pesticides in an Irish case study. The predicted concentrations in surface water were then used to quantify the level of health risk posed to Irish adults and children. The analysis indicated that herbicides triclopyr and MCPA occur in the greatest concentrations in surface water, while mecoprop was associated with the highest potential for health risks. The study found that the modelled pesticides posed little risk to human health under current application patterns and climatic conditions in Ireland using international acceptable intake values. A sensitivity study conducted examined the impact seasonal conditions, timing of application, and instream processes, have on the transport of pesticides to drinking water.