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基于帕累托解集的水资源优化模型及应用

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[目的]为解决需水预测中信息缺失，忽略目标之间博弈过程等问题，研发了考虑水资源与城市发展之间相互联系与博弈特征的非线性多目标水资源优化模型。[方法]模型以用水总量最低和万元增加值用水量最小为目标，基于"四水四定"原则，对不同年份、不同产业的水资源需求进行联合优化。针对传统的定额预测法忽视了目标间竞争过程的问题，使用遗传算法求解此非线性多目标模型的帕累托解集，生成一系列符合目标要求的水资源优化方案。[结果]模型应用于江苏省苏州市吴江区，得到100组非劣的水资源优化方案。结果显示:帕累托解集上的优化方案在区域用水总量上较定额法低6％～16％，万元增加值用水量较定额法降低19％～31％，优化效果显著。[结论]结果表明:帕累托解集可以全面展现出水与城市发展之间的竞争状态。该模型统筹考虑了水资源与人口、土地、城市、产业之间的关系，将其内在复杂的竞争关系清晰地展现出来，可以为实际应用提供更丰富的决策支持信息。
Water resources optimization model and application based on Pareto solution set
[Objective]A nonlinear multi-objective water resources optimization model has been developed to address issues such as missing information and neglecting the game process between targets in water demand forecasting.The interrelation and game characteristics between water resources and urban development in water demand forecasting are taken into consideration.[Meth-ods]The model aims to minimize total water consumption and minimize water consumption per 10,000 yuan of value-added,based on the principles of the"Basing Four Aspects on Water Resources".Joint optimization of water resource demand is con-ducted for different years and industries.In contrast to the traditional water quota forecasting method,which disregards the com-petition process between objective,the Pareto solution set of this nonlinear multi-objective model is determined using a genetic algorithm,[Results]ing in a series of water resource optimization schemes that fulfill the target requirements.[Results]The model has been applied to Wujiang District,Suzhou City,Jiangsu Province,yielding 100 non-inferior water resource optimization schemes.The findings indicate that the optimized solution on the Pareto solution set is 6％to 16％lower than the water quota method in terms of total regional water use,and the water use per 10,000 yuan of value-added is reduced by 19％～31％com-pared to the water quota method,demonstrating a significant optimization effect.[Conclusion]The result suggest that the com-petitive state between water use and urban development can be comprehensively illustrated by the Pareto solution set.It is revealed by the model that the relationship between water resources and population,land,cities,and industries is inherently complex and competitive.Richer decision-support information for practical applications is provided by taking into account these relationships.

Pareto solution setBasing Four Aspects on Water Resourcesmulti-objective optimizationwater quota methodwater resources optimizationwater resourcesInfluencing factorspopulation

曲永驭、蔡淑兵、赵晶、倪红珍、余蔚卿、陈潇、陈根发

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长江勘测规划设计研究有限责任公司水利规划院,湖北武汉 430014

华北水利水电大学水资源学院,河南郑州 450046

中国水利水电科学研究院,北京 100038

帕累托解集 四水四定 多目标优化 定额法 水资源优化 水资源 影响因素 人口

"十四五"国家重点研发计划项目长江勘测规划设计研究有限责任公司自主创新基金

2022YFC3006402CX2022Z15

2024

10.13928/j.cnki.wrahe.2024.09.004

水利水电技术(中英文)
水利部发展研究中心

水利水电技术(中英文)

CSTPCD北大核心
影响因子：0.456
ISSN：1000-0860
年,卷(期)：2024.55(9)