Adaptation pathways for intermittent water supply systems under limited resources

ABSTRACT Water scarcity and power outages are critical challenges causing intermittency in water supply systems. This is further exacerbated by climate change and uncertain future conditions. This study develops a methodology for implementing adaptation pathways under uncertainty to enhance the performance, equity, and resilience of intermittent water supply (IWS) systems. The methodology, applied to the benchmark D_Town benchmark network, focuses on three-time horizons: short-term actions optimize network operations to improve equity and supply hours; medium-term actions involve sectorizing the network and enhancing tank capacities; and long-term actions include rehabilitating pump capacities and exploring alternative water and power resources. Using an evolutionary multiobjective optimization method (non-dominated sorting genetic algorithm, NSGA-II) based on minimizing operational costs, maximizing equity, and extending supply hours, the results demonstrate that the interventions implemented in each period significantly improved network performance and resilience to water scarcity and power outage conditions. The study recommends adopting adaptive planning in IWS management, focusing on immediate actions to address current challenges while maintaining flexibility for future decisions. By integrating adaptation pathways with multiobjective optimization, this research provides a robust framework for addressing uncertainty and supporting sustainable and equitable water supply for IWS systems under power outages and water scarcity conditions.