Multiobjective Spatial Optimization Framework for Determining the Optimal Degree of Decentralization for Nonpotable Water Reuse in Existing Cities: A Case Study of Hong Kong

Investing in nonpotable water reuse (NPWR) is essential for circular urban water management. Existing research lacks methods to determine the number and capacities of NPWR plants (i.e., degree of decentralization) for large-scale applications in existing cities. We developed a spatial optimization framework in which the degree of decentralization emerges from the collective decisions of urban districts regarding where to send wastewater for reclamation and where to source water for nonpotable uses. We modified the genetic algorithm to optimize collective decisions with objectives including minimizing freshwater withdrawal, electricity consumption, and the cost of NPWR plants. Optimization results suggest an optimal number from one to eight among Pareto optimal solutions, with two to three being most common in Hong Kong. The cost-effective solutions suggest locations of NPWR plants in Kowloon and Hong Kong Island where NPWR demand is significant, while the electricity use for freshwater and seawater is high. The city could save about 6% freshwater and 29.4% seawater while consuming 20.7% more electricity. Overall, our spatial optimization framework provides a holistic evaluation of the optimal degree of decentralization for NPWR at the water-energy-cost nexus on an urban scale. Our findings serve as a benchmark to explore more energy-conscious planning strategies in Hong Kong.