There is a need for introducing interdisciplinary tools and approaches in water management for participatory integrated assessment of water protection costs and environmental benefits for different management scenarios. This is required for the Water Framework Directive. Bayesian belief networks (BN) are one example of a possible tool for participatory integrated assessment. BNs allow knowledge and data from economic, social and hydrological domains to be integrated in a transparent, coherent and equitable way. The paper reports on the construction of a BN to assess impacts of pesticide management actions on agricultural economics and groundwater and drinking water quality, with the overall aim of exploring complexity and uncertainties.

With the participatory BN learning process data, expert knowledge and modelling results were combined into a cost-efficiency and cost-benefit analysis, BN being based on a focused dialogue between participating domain experts and end-users of the research. The instruments analysed by the constructed BN were taxes on pesticides and herbicides, and pesticide-free buffer zones around field edges and water abstraction wells.