Disentangling the water quality dimension of the Water-Energy-Food nexus: a Bayesian Network Approach applied to the Upper Agide river basin

Understanding and effectively managing water quality within the context of global changes requires a nexus approach that embraces the interconnected facets of the Water-Energy-Food system. This perspective acknowledges the intricate interplay between diverse processes and human activities that together can impact water quality. In this context, the aim of the thesis is to understand and model the complex intersectoral relations occurring across the WEF nexus, with a special focus on the water quality dimension. In the first part, a literature review on cross-sectoral interactions serves as a base for creating a DPSIR framework that depicts the most important implications for water quality. Later, the framework has been used to frame the most prominent nexus interactions occurring in the Upper Adige river basin. In this area many factors concur in the water quality, including both the food sector (i.e. intensive fruit and wine production) and the energy sector, as the area is an important producer of hydroelectric energy. Finally, a spatially explicit Bayesian Network (BN) has been developed to predict the influence of different configurations of sub-catchment characteristics (i.e. land use, socioeconomic and climatic variables) on multiple water quality parameters and to perform scenario analysis. The final goal is to identify which of the considered variables are the primary drivers of water quality alterations under global changes.