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基于CNSGA-Ⅲ算法的乌苏市水资源优化配置
Optimize Allocation of Water Resources in Wusu City Based on CNSGA-Ⅲ Algorithm
【摘要】 以新疆塔城区乌苏市水资源优化问题为例,构建以经济、社会和生态效益为目标的水资源优化配置模型,选用带有Deb约束准则的CNSGA-Ⅲ算法对模型求解,结合熵权-逼近理想解排序法(technique for order preference by similarity to ideal solution, TOPSIS)评价模型,对求解方案进行对比筛选,选出区域水资源最佳配置方案。结果表明:在用水红线约束下,2025年、2035年优化后的水量较原始水量分别节约了50×10~4、9×10~4m~3;在用水结构上,与现状年相比农业用水占比分别下降6%、10%;在水源结构上,地下水供水占比下降28%,效果明显,充分利用了地表水及外调水,使地下水超采得到有效遏制,表明所建立的水资源优化模型对乌苏市水资源研究具有一定适用性,对未来水资源配置研究具有一定的参考价值。
【Abstract】 With the water resources optimization problem in Wusu City, Tacheng District, Xinjiang as an example, an optimal allocation model of water resources aimed at economic, social, and ecological benefits was constructed, the CNSGA-Ⅲ algorithm with Deb constraint criteria was selected to solve the model, and the entropy weight technique for order preference by similarity to ideal solution(TOPSIS) evaluation model was combined to compare and screen the solutions to select the optimal allocation scheme of regional water resources. The results show that constrained by the red line for water consumption, the optimized water consumption in 2025 and 2035 are reduced by 50×10~4, 9×10~4m~3 respectively compared to the original water consumption. In terms of water consumption structure, their proportions of agricultural water consumption decrease by 6% and 10% respectively compared to the planned base year. In terms of water source structure, the proportion of groundwater supply decreases by 28%, with significant effects. It is concluded that the surface water and external water are fully used, and groundwater overexploitation is effectively limited, which indicate that the established water resources optimization model has certain applicability for water resources research in Wusu City, and has certain reference value for future water resources allocation research.
【Key words】 entropy weight-technique for order preference by similarity to ideal solution(TOPSIS) model; CNSGA-III algorithm; optimal allocation of water resources; groundwater;
- 【文献出处】 科学技术与工程 ,Science Technology and Engineering , 编辑部邮箱 ,2023年32期
- 【分类号】TV213.4
- 【下载频次】82