Multi-objective optimization of urban water allocation considering recycled water

Abstract The use of recycled water is an essential means of resolving urban water scarcity. To realize the coordinated allocation of conventional and recycled water, a multi-objective water resources optimal allocation model with recycled water is established. The model takes into account the impact of the carbon footprint on the regional ecology during the total water allocation process, which has not been given enough attention before. Simultaneously, this study combined direct policy search, nonlinear approximation networks and multi-objective evolutionary algorithms to design Pareto approximation operating policies for joint conventional and recycled water allocation. The AHP-Entropy method based on combinatorial assignment of weights is then used to perform multi-attribute decision making on the optimized operating policies for scientific selection of solutions. The proposed model is demonstrated in Yiwu City, China, which suffers from the water shortage due to the rapid development of industry. Results show that radial basis functions can effectively design Pareto approximation operating policies for the water supply system of Yiwu City. The inclusion of recycled water can result in a 31.67% reduction in water shortage and an 8.45% increase in economic benefit, while carbon emissions only increase by 1.78%. This result illustrates the use of recycled water can alleviate urban water scarcity, increase economic benefits, and mitigate carbon emissions to some extent. Multi-attribute decision making based on the AHP-Entropy method provides a scientific basis for optimalurban multi-water allocation.