An Optimization Model for Water Management under the Dual Constraints of Water Pollution and Water Scarcity in the Fenhe River Basin, North China

被引:3
|
作者
Meng, Chong [1 ]
Zhou, Siyang [1 ]
Li, Wei [1 ]
机构
[1] Beijing Normal Univ, Sch Environm, Key Lab Water Environm Simulat, 19 Xinjiekouwai St, Beijing 100875, Peoples R China
基金
中国国家自然科学基金;
关键词
water resource allocation; pollutant emission; two-stage stochastic programming; downside risk; coordinated development; STOCHASTIC-PROGRAMMING MODEL; RESOURCES MANAGEMENT; QUALITY MANAGEMENT; CLIMATE-CHANGE; ALLOCATION; UNCERTAINTY; IRRIGATION; STABILITY; STRATEGY; IMPACT;
D O I
10.3390/su131910835
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Sustainable watershed development suffers from severe challenges, such as water pollution and water scarcity. Based on an analysis of water quality and water utilization in the Fenhe River Basin, an inexact two-stage stochastic programming model with downside-risk aversion was built for optimal water resource allocations for the four primary water use sectors (industry, domestic use, agriculture, and the environment) in the Fenhe River Basin. The model aims to maximize the comprehensive watershed benefits, including water benefits, water costs, water treatment costs, and downside risks. The constraints are water quality, available water resources, and sectoral demands in different hydrological scenarios. The results show that pollutant emissions decrease as risk-aversion levels increase and show the opposite trend in the midstream and downstream areas. The increase in water resource allocation for agriculture and reduction in ecological water indicate that agriculture suffered the greatest water shortage and risk. Improving water recycling and coordinating the transferred water resources increases the comprehensive benefits and reduces sectoral risks. The model effectively manages rational water allocations under dual constraints and provides support for coordinating socio-economic development and environmental protection in the river basin.
引用
收藏
页数:18
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