System Dynamics-Multiple Objective Optimization Model for Water Resource Management: A Case Study in Jiaxing City, China

Predicting and allocating water resources have become important tasks in resource management. System dynamics optimal planning models are widely applied to solve individual problems, but seldom combined studies. In this work, we developed a framework involving system dynamics-multiple objective optimization (SD-MOO) model, which integrated the functions of simulation, policy control, allocation, it case study management Jiaxing, China demonstrate modeling. The predicted results showed that shortage would not occur at high-inflow level during 2018–2035 appear mid- low-inflow levels 2025 2022, respectively. After made dynamic adjustments use efficiency, economic growth, population utilization, rates decreased by approximately 69–70% 2035 compared scenarios without any adjustment strategies. Water allocation schemes obtained from “prediction + regulation optimization” were competitive terms social, environmental benefits flexibly satisfied demands. demonstrated SD-MOO model could be an effective tool achieving sustainable