Construction of a Bayesian Network for the Assessment of Agri-Environmental Measures – The Case Study of the Venice Lagoon Watershed

Abstract

A methodological framework was designed to assess the effectiveness of agri-environmental policy measures adopted by the Veneto Region to reduce diffuse water pollution of agricultural origin. Two already existing methodologies were combined in a new flexible approach for policy assessment: Conceptual Modelling and Bayesian Networks (BNs). The former supported the development of a shared conceptual model (a cognitive map) of the agro-ecosystem of the study area; while the latter allowed the development of a probabilistic model coherent with the cognitive map. BNs were selected because they allow analyses with scarce data; they can be updated when further information becomes available, and are easily understandable by layperson. The paper reports the results obtained in the Venice Lagoon Watershed (VLW) case study, where the current agri-environmental measures were assessed in order to identify their effectiveness in terms of reduction of nitrogen releases in water bodies connected to the lagoon ecosystem. Preliminary results obtained by implementing expert opinions in the BN pointed out the likely limited effects of the measures on the declared objective of