Multi-objective Optimization of Urban Water Allocation Considering Recycled Water

Recycled water is a vital solution to urban water scarcity and a key element in sustainable water management. This study develops a multi-objective optimal allocation model that integrates conventional and recycled water. By incorporating carbon emissions into the water allocation process, the model provides a comprehensive approach to balancing social, economic and environmental goals. Advanced methodologies, including direct policy search, nonlinear approximation networks, and multi-objective evolutionary algorithms, are employed to design Pareto-optimal operating policies for joint water allocation. Additionally, the AHP-Entropy method is applied as a multi-attribute decision-making (MADM) framework to systematically evaluate and rank allocation strategies based on ecological, economic, and social objectives. The model is demonstrated in Yiwu City, China, a region characterized by severe water shortages due to rapid industrial development. Results show that incorporating recycled water reduces water shortages by 31.67%, increases economic benefits by 8.45%, and minimally raises carbon emissions by 1.78%. These findings highlight the dual role of recycled water in alleviating urban water scarcity and mitigating carbon emissions, underscoring its value as a sustainable alternative in water resource management. By integrating advanced optimization techniques with robust decision-making tools, this study provides a scientific basis for developing low-carbon water allocation strategies and offers critical insights for policymakers seeking to enhance water security and sustainability in rapidly urbanizing regions.