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作 者:陈甜[1] 董增川[1] 贾本有[1] 黄兴春[1] 钟敦宇
机构地区:[1]河海大学水文水资源学院,江苏南京210098
出 处:《河海大学学报(自然科学版)》2014年第6期476-480,共5页Journal of Hohai University(Natural Sciences)
基 金:教育部科学技术研究重点项目(104197)
摘 要:采用同频率地区组成法分析小南海水电站坝址处设计洪水的地区组成,运用BP人工神经网络对坝址河段洪水演进建模,分析不同典型年上游梯级水库群防洪调度对小南海水电站设计洪水的影响。分析结果表明:上游梯级水库群调度对小南海水电站设计洪水的影响明显,尤其对稀遇洪水的削减程度显著;以金沙江来水为主的洪水受梯级水库群防洪调度的影响较大,以岷江来水为主的洪水受梯级水库群防洪调度的影响较小。The same-frequency area composition method was used to analyze the area composition of a design flood of the dam site of the Xiaonanhai Hydropower Station. The flood routing in the river reach of the dam site was simulated with the artificial neural network model, and the influence of the flood control operation of the upstream cascade reservoir group on the design flood of the Xiaonanhai Hydropower Station in different typical years was analyzed. The results show that the flood control operation of the upstream cascade reservoir group has a significant influence on the design flood of the Xiaonanhai Hydropower Station, especially on the reduction of rare floods. The floods that mainly come from the Jinshajiang River are greatly influenced by the flood control operation, while the floods that mainly come from the Minjiang River are not significantly influenced by the flood control operation.
关 键 词:小南海水电站 防洪标准 设计洪水 同频率地区组成法 人工神经网络
分 类 号:TV122.3[水利工程—水文学及水资源]
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