Allocation of fresh water recourses in China with nested probabilistic-numerical linguistic information in multi-objective optimization

Abstract

Fresh water resources are made of conventional water resources (CWRs) and unconventional water resources (UWRs), and they are one of the important natural resources that cannot be replaced. The purpose of this paper is to predict and allocate China’s fresh water resources in 2025 under complex environment. According to historical data, we first conduct data reprocessing including data collection, data prediction and discussion. In order to achieve an appropriate tradeoff between ecological environment and economic development, a multi-objective optimization model is constructed based on market mechanism. Specifically, we establish two objective functions: one is to minimize the total cost, the other is to minimize the whole amount of CWRs, and then, we optimize the parameters in the model based on nested probabilistic-numerical linguistic information. After that, the solution and the strategy of fresh water resources are obtained, and the sustainable development and risk response by adjusting and adding the parameters are further analyzed. The results show that the model is effective, feasible and applicable. Finally, we make some discussions about the strengths and weakness of the model, and the suggestions for the fresh water resources in China.