A Pipe Ranking Method for Water Distribution Network Resilience Assessment Based on Graph-Theory Metrics Aggregated Through Bayesian Belief Networks

Abstract The resilience assessment is crucial for many infrastructures, including water supply and distribution networks. In particular, the identification of ‘critical’ components (nodes or pipes) whose failure may negatively affect network performances system a key issue, with direct relevance decision-makers involved in planning, management improvement activities. Among multiple methods tools available, use graph-theory metrics cutting-edge research topic, as analysis topological properties provide simple yet reliable information on performance complex present work, we aim to overcome limit associated individual metrics, identifying subset relevant that are directly connected properties, using them perform ‘network degradation analysis’ case single pipe finally proposing an aggregation results Bayesian Belief Network. Ultimately, proposed methodology provides ranking most critical pipes, i.e. those contribute resilience. A real Italy used model development validation.