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作 者:冯涛 杨睿峰 左其亭[2,3] 朱大炯 于磊 FENG Tao;YANG Ruifeng;ZUO Qiting;ZHU Dajiong;YU Lei(Henan Water&Power Engineering Consulting Co.,Ltd.,Zhengzhou 450016,China;School of Water Conservancy and Transportation,Zhengzhou University,Zhengzhou 450001,China;Yellow River Institute for Ecological Protection&Regional Coordination Development,Zhengzhou University,Zhengzhou 450001,China)
机构地区:[1]河南省水利勘测设计研究有限公司,河南郑州450016 [2]郑州大学水利与交通学院,河南郑州450001 [3]郑州大学黄河生态保护与区域协调发展研究院,河南郑州450001
出 处:《华北水利水电大学学报(自然科学版)》2024年第4期47-55,共9页Journal of North China University of Water Resources and Electric Power:Natural Science Edition
基 金:河南省水利厅水利科技攻关项目(GG202125,GG202022);国家重点研发计划项目(2021YFC3200201);河南省重大公益性科技专项(201300311500);河南省高层次人才特殊支持计划项目(ZYQR201912184)。
摘 要:开展灌区水资源承载力多目标决策研究,探究灌区水资源、社会经济以及生态环境三者之间的互动关系,对可持续性灌区建设具有重要意义。以赵口引黄灌区二期工程为研究对象,以灌区经济效益最大、缺水率最小、承载人口总量最多、污染物排放量最小以及粮食产量最大为目标,综合考虑灌区供需水能力、灌溉面积、污染物排放等多维临界约束,构建了赵口引黄灌区二期工程水资源承载力多目标决策模型,运用第3代非支配排序遗传算法(NSGA-Ⅲ)进行求解,获得Pareto最优解集,并依据不同的目标偏好和熵权法从中选取多套决策方案。研究结果表明:文中经济效益最大、社会效益最大、生态效益最大、人口总量最大以及粮食产量最大5个目标相互制约,Pareto非劣解侧重于追求其中一方效益最优的同时,必然会引起其他目标值(至少一个)变劣。因此,文中得到的多种决策方案可为灌区未来水资源承载力的提升提供科学理论指导。It is of great significance for sustainable construction of irrigated areas to carry out multi-objective decision-making research on water resources carrying capacity and explore the interactive relationship among water resources,social economy and ecological environment in irrigated areas.This paper took the Phase II Project of Zhaokou Yellow River Irrigation District as the research object, the maximum economic benefit, the minimum water shortage, the largest carrying popu-lation, the minimum pollutant discharge and the maximum grain yield of the irrigated area were identified as objectives, comprehensively considering the multidimensional critical constraints (e. g. water supply and demand capacity, irrigation area and pollutant discharge), a multi-objective decision-making model of water resources carrying capacity of the Phase II Project of Zhaokou Yellow River Irrigation District was constructed. The model was solved by the third-generation non-dom-inated sorting genetic algorithm ( NSGA - Ⅲ), and the Pareto optimal solution sets were obtained. Multiple decision schemes were selected based on the obtained results according to different objective preferences and entropy weight method. The results show that the five goals of maximum economic benefit, maximum social benefit, maximum ecological benefit, maximum population and maximum grain output in this paper are mutually restricted. The non-inferior Pareto solution focu-ses on the pursuit of the optimal benefit of one of the five goals, and will inevitably cause the other goals (at least one) to become inferior. Therefore, the decision schemes obtained in this paper can provide scientific theoretical guidance for the future improvements of water resources carrying capacity in irrigated areas.
关 键 词:水资源承载力 多目标决策 第3代非支配排序遗传算法 供需关系 赵口引黄灌区二期工程
分 类 号:TV213.4[水利工程—水文学及水资源]
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