A Bayesian Network Approach to Probabilistic Risk Assessment of Pesticides Under Current and Future Agricultural and Climate Scenarios

Summary

Future weather patterns are expected to result in increased precipitation and temperature, in Northern Europe. These changes can potentially cause an increase in plant disease and insect pests which will alter agricultural practice amongst other things the used crop types and application patterns of pesticides. We use a Bayesian network to explore a probabilistic risk assessment approach to better account for variabilities and magnitudes of pesticide exposure to the aquatic ecosystem. As Bayesian networks link selected input and output variables from various models and other information sources, they can serve as meta-models. In this study, we are using a pesticide fate and transport models (e.g. WISPE) with specific environmental factors such as soil and site parameters together with chemical properties and climate scenarios that are linked to a representative Norwegian study area. The derived exposure of pesticide of the study area is integrated in the Bayesian network model to estimate the risk to the aquatic ecosystem also integrating an effect distribution derived from toxicity test. This Bayesian network model will allow to incorporate climate predictions into ecological risk assessment.