Water distribution networks (WDNs), an interconnected collection of hydraulic control elements, are susceptible to a small disturbance that may induce unbalancing flows within a WDN and trigger large-scale losses and secondary failures. Identifying critical regions in a water distribution network (WDN) to formulate a scientific reinforcement strategy is significant for improving the resilience when network disruption occurs. This paper proposes a framework that identifies critical regions within WDNs, based on the three metrics that integrate the characteristics of WDNs with an external service function; the criticality of urban function zones, nodal supply water level and water shortage. Then, the identified critical regions are reinforced to minimize service loss due to disruptions. The framework was applied for a WDN in Dalian, China, as a case study. The results showed the framework efficiently identified critical regions required for effective WDN reinforcements. In addition, this study shows that the attributes of urban function zones play an important role in the distribution of water shortage and service loss of each region.
A Cooperative Co-Evolutionary Approach to Large-Scale Multisource Water Distribution Network Optimization
