黄河下游非汛期来水来沙对平滩流量的影响  

Influences of non-flood-season flow and sediment load on bankfull discharge in lower Yellow River

作　　者：李文文[1] 傅旭东[1] 吴保生[1] 吴文强[2] 

机构地区：[1]水沙科学与水利水电工程国家重点实验室清华大学,北京100084 [2]中国水利水电科学研究院,北京100038

出　　处：《水力发电学报》2013年第1期132-138,共7页Journal of Hydroelectric Engineering

基　　金：国家自然科学基金项目(51109116);国家水专项(2009ZX07212-005-3;水利部公益项目(200901016-03);中荷战略科学联盟计划项目(2008DFB90240)

摘　　要：本文采用人工神经网络方法分析了黄河下游汛期和非汛期水沙条件对平滩流量的影响,建立了黄河下游4个测站的人工神经网络模型,并重点分析了非汛期水沙因子对平滩流量的作用。结果表明,人工神经网络模型能够同时考虑汛期和非汛期水沙条件对平滩流量的综合作用。当平滩流量计算中加入非汛期影响因子后,各站计算精度均有较大幅度提高。因此,对于黄河下游平滩流量的计算,不仅要考虑汛期水沙条件的影响,非汛期水沙条件的影响也是不可忽视的。Estimation of bankfull discharge is crucial to determination of water regulating volume and sediment load in the lower Yellow. This paper studies the effects of flow and sediment load in non-flood season on the bankfull discharge at four hydrological stations on this river. BP neural network was used to develop bankfull discharge models that take the control factors of flow and sediment discharge as input conditions. To estimate these effects, two inputs were compared： given volumes of water and sediment load transported only in flood season, the same volumes transported in one hydrological year. The results show that the effects of non-flood season transports on the bankfull discharge are not negligible. Consideration of the non-flood season roles of water flow and suspended load can significantly improve the modeling accuracy of the flows at all the four stations.

关 键 词：河流泥沙工程学 河床演变 平滩流量 神经网络 黄河下游 非汛期 

分 类 号：TV147[水利工程—水力学及河流动力学]