A Framework of Identifying Critical Water Distribution Pipelines from Recovery Resilience

Identifying critical facilities in a water distribution system (WDS) from the standpoint of recovery resilience is significant for emergency inspection and restoration when a large-scale system disruption occurs. Taking a damaged pipeline into account, this paper proposes a framework for realizing criticality identification. The priority with which a damaged pipeline needs to be restored to minimize WDS service loss and the impact of delaying such priority on the loss of service are taken as criticality metrics. To acquire two metric values for each pipeline, a WDS recovery optimization problem, which integrates mechanical repair measures with hydraulic simulation, aimed at minimizing system service loss, is proposed and then solved by a genetic algorithm. Given the stochasticity of disruptions on a WDS, critical pipelines are identified by a stochastic scoring method, based on the statistical distribution of the two metrics obtained by stochastic sampling. An application of the framework to a case study of a WDS with simulated disruption scenarios distinguished pipelines critical to effective infrastructure restoration. Compared with models using network centrality and vulnerability-based metrics, the framework proposes a more reasonable way to measure facility criticality in terms of recovery resilience.