A dynamic allocation framework for urban multi-source water under compound risk: integrating water deficit and quality indices

Abstract

This study addresses the compound risks of drought and water quality deterioration faced by urban water supply systems under climate change. A dynamic allocation model integrating water quantity and quality indicators was developed to enhance adaptive management. The model incorporates an expanded water deficit index (WDI) and a Water Quality Index (WQI) within a fuzzy logic-based decision framework. Through a quality-weighting adjustment mechanism, the model dynamically reallocates surface water, groundwater, reclaimed water (RW), and interregional support water according to real-time hydrological and quality conditions. Using Taichung City, Taiwan, as a case study, results show that the proposed model improves overall supply resilience by 9.6% while maintaining system stability and safeguarding health under variable drought and water quality conditions. The findings demonstrate that integrating dual indicators within a fuzzy inference system provides a practical and scalable approach for adaptive, health-conscious, and climate-resilient urban water governance.