考虑上游梯级水库群调度的小南海水电站坝址设计洪水分析
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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.
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.
引文
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[2]赵元弘.小南海水库地震堰塞坝体防渗处理[J].水利水电科技进展,2008,28(5):39-44.(ZHAO Yuanhong.Seepage control of the earthquake-induced barrier bar of Xiaonanhai Reservoir[J].Advances in Science and Technology of Water Resources,2008,28(5):39-44.(in Chinese))
[3]李霞,张绪进,杜宗伟,等.长江小南海枢纽施工二期导流明渠通航条件研究[J].重庆交通大学学报:自然科学版,2013,32(2):306-309.(LI Xia,ZHANG Xujin,DU Zongwei,et al.Diversion channel navigation condition in construction phaseⅡof Xiaonanhai water control project on Yangtze River[J].Journal of Chongqing Jiaotong University:Natural Science,2013,32(2):306-309.(in Chinese))
[4]金光炎.水文频率分布模型的异同性与参数估计问题[J].水科学进展,2010,21(4):466-470.(JIN Guangyan.Similarities and differences of hydrologic frequency distribution models and their parameter estimation problems[J].Advances of Water Science,2010,21(4):466-470.(in Chinese))
[5]杨涛,陈喜,杨红卫,等.基于线性矩法的珠江三角洲区域洪水频率分析[J].河海大学学报:自然科学版,2009,37(6):615-619.(YANG Tao,CHEN Xi,YANG Hongwei,et al.Regional flood frequency analysis in Pearl River Delta region based on L-moments approach[J].Journal of Hohai University:Natural Sciences,2009,37(6):615-619.(in Chinese))
[6]JIN Guangyan.Problems in statistical treatment of flood series[J].Journal of Hydrology,1987,96(1):173-184.
[7]SL 44—2006水利水电工程设计洪水计算规范[S].
[8]谢蕾.同频率地区组成法在区间洪水计算中的应用[J].新疆农业大学学报:2010,33(5):442-447.(XIE Lei.Application of method of same frequency area composition in calculating interzone flood water[J].Journal of Xinjiang Agricultural University,2010,33(5):442-447.(in Chinese))
[9]LI Tianyuan,GUO Shenglian,LI Yanqing,et al.Review of design flood estimation methods for cascade reservoirs[J].Journal of Water Resources Research,2012(1):14-20.
[10]梁忠民,钟平安,华家鹏.水文水利计算[M].2版.北京:中国水利水电出版社,2008:58-59.
[11]阚光远,李致家,刘志雨,等.改进神经网络模型在水文模拟中的应用[J].河海大学学报:自然科学版,2013,41(4):294-299.(KAN Guangyuan,LI Zhijia,LIU Zhiyu,et al.An improved neural network model and its application to hydrological simulation[J].Journal of Hohai University:Natural Sciences,2013,41(4):294-299.(in Chinese))
[12]黄国如,芮孝芳.河道洪水演算的径向基函数神经网络模型[J].河海大学学报:自然科学版,2003,31(6):621-625.(HUANG Guoru,RUI Xiaofang.Radial basis function neural network model for channel flood routing[J].Journal of Hohai University:Natural Sciences,2003,31(6):621-625.(in Chinese))
[13]王光生,苏佳林,沈必成,等.神经网络理论在河道洪水预报中的应用[J].水文,2009,29(5):55-58.(WANG Guangsheng,SU Jialin,SHEN Bicheng,et al.Application of neural network in channel flow forecasting[J].Journal of China Hydrology,2009,29(5):55-58.(in Chinese))
[14]李晓峰,刘光中.人工神经网络BP算法的改进及其应用[J].四川大学学报:工程科学版,2000,32(2):105-109.(LI Xiaofeng,LIU Guangzhong.The improvement of BP algorithm and its application[J].Journal of Sichuan University:Engineering Science Edition,2000,32(2):105-109.(in Chinese))
[15]郑重,马富裕,李江全,等.基于BP神经网络的农田蒸散量预报模型[J].水利学报,2008,39(2):230-234.(ZHEN Zhong,MA Fuyu,LI Jiangquan,et al.Analysis on failure stress in concrete due to corrosion of rebar under bidirectional loading[J].Journal of Hydraulic Engineering,2008,39(2):230-234.(in Chinese))
[16]徐晨光,李春静,赵麦换.串联水库洪水预报模型影响因素及精度分析[J].人民黄河,2008,30(7):34-35.(XU Chenguang,LI Chunjing,ZHAO Maihuan.Analysis of influencing factors and precision of flood forecasting model of connection reservoir[J].Yellow River,2008,30(7):34-35.(in Chinese))
[17]长江流域综合规划报告[R].武汉:水利部长江水利委员会,2009.
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