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Metaheuristic optimization of water resources: A case study of the Manas River irrigation district
Journal of Hydrology ( IF 5.9 ) Pub Date : 2024-07-02 , DOI: 10.1016/j.jhydrol.2024.131640 Yue Pan , Hao Tian , Muhammad Arsalan Farid , Xinlin He , Tong Heng , Cecilie Hermansen , Lis Wollesen de Jonge , Fadong Li , Yongli Gao , Lijun Tian , Guang Yang
Journal of Hydrology ( IF 5.9 ) Pub Date : 2024-07-02 , DOI: 10.1016/j.jhydrol.2024.131640 Yue Pan , Hao Tian , Muhammad Arsalan Farid , Xinlin He , Tong Heng , Cecilie Hermansen , Lis Wollesen de Jonge , Fadong Li , Yongli Gao , Lijun Tian , Guang Yang
Irrigated arid oasis areas experience shortages in water resources and imbalances between supply and demand. A rational water resources allocation strategy must be devised to solve such problems; however, this remains a challenging issue to overcome. In this study, a multi-objective water resources optimization model based on a metaheuristic algorithm was established for the Manas River irrigation area in Xinjiang. First, considering future population growth and the development of the ecological environment in arid oasis irrigation areas, a multi-objective water resource optimization allocation model was established. This model was developed to derive the maximum economic benefits from water supply allocation to users, improve the degree to which ecological water demand is met for ecological environmental restoration, and reduce water shortages. The model adheres to the constraints of the total water resources in this area and can be used to effectively solve future water resources supply and demand imbalances in the Manas River irrigation area. Second, a multi-objective beluga whale optimization algorithm was selected to solve multi-objective problems. In contrast to traditional optimization algorithms, the multi-objective beluga whale optimization algorithm does not rely on the knowledge of a specific problem domain, representing a more generalized approach. Instead, this algorithm provides a general framework for searching for solutions, finding an approximate optimal solution, and generating a multi-objective solution set, taking into account the model computation time and domain. Finally, the target solution set obtained after 100 iterations is used as the basis for identifying the optimal solution. The key findings of this study are as follows: (1) The solution sets obtained by applying the multi-objective beluga whale optimization algorithm to solve the multi-objective optimal allocation model for irrigation water resources in each subirrigation district (Shihezi, Mosouwan, and Xiayedi irrigation districts), for four distinct user categories (agriculture, industry, household, and ecological water), consistently adhered to the comprehensive water resources index of the irrigation district. (2) After employing the 2030 projections for the Shihezi irrigation district as an example, the binary comparison methodology helped ascertain the objective weights (0.43, 0.35, and 0.22). The multi-objective fuzzy preference model was then used to shift through the solution set, highlighting the solution with the highest degree of superiority ( = 0.979) as the optimal solution. (3) Under this scenario, the economic objective of the optimal solution for the Shihezi irrigation district for 2030 is 14,912.91 million yuan, with social and ecological objectives of 1186.77 and 1.22 million m, respectively. The results of this scenario can serve as a reference for decision-makers and provide a basis for optimal water resources allocation in arid oasis irrigation districts.
更新日期：2024-07-02
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