[口头报告]Optimization of Water Resources Allocation Under Multi-objective Constraints in Ecologically Fragile Area
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[口头报告]Optimization of Water Resources Allocation Under Multi-objective Constraints in Ecologically Fragile Area

Optimization of Water Resources Allocation Under Multi-objective Constraints in Ecologically Fragile Area
编号:350 访问权限:仅限参会人 更新:2024-05-16 14:33:51 浏览:301次 口头报告

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摘要
The current water use structure in Xinjiang is characterized by high water consumption and low output.Finding optimal water resources allocation for crops and ecological is necessary to increase the efficiency of water usage. This study takes Abby Lake Basin as an example to quantify the social, economic, and ecological values of surface water generation,the optimal allocation model of water resources with the maximum economic-ecological benefit, the minimum water shortage and Food security as a constraint as the objective function was constructed. The improved third generationnon-dominated sorting genetic algorithm ( NSGA-Ⅲ) was used to solve the model.The results show that the total economic-ecological benefit generated by surface water in the Abbey Lake Basin through optimization could reach 3.09 ×1010yuan in 2021,About 36.5% higher than the original benefit .Also, the volume of the water shortage is 301,800 m3, of which 78.2% of the water shortage in the Bortala River Basin, 21.2% of the water shortage in the Jing River Basin, and 197,447.89 m3 river water allocated to the lake water.When social benefit minimization takes precedence,economic-ecological benefit values are 2.72×1010 yuan, the volume of the water shortage is 326.53m3, of which the Bortala River shortage is 326.40m3, Jing River is 0.1m3, and 1208,869.56 m3 river water is allocated to the lake. In this condition, the economic-ecological benefit is smaller than the first condition, but still 20.3% higher than the actual production of economic value.This research results provide new ideas and approaches to water resources management in arid zones.
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报告人
Gulbostan Tursun
China University of Mining and Technology

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