白龟山水库入库洪水预报分布式模型研究
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  • 英文篇名:Research on the Physically Based Distributed Hydrological Model for Baiguishan Reservoir Flood Forecasting
  • 作者:魏恒志 ; 陈洋波 ; 刘永强 ; 董礼明 ; 徐章耀 ; 王幻宇
  • 英文作者:WEI Heng-zhi;CHEN Yang-bo;LIU Yong-xing;DONG Li-ming;XU Zhang-yao;WANG Huan-yu;Baiguishan Reservoir Administration,Henan Province;School of Geography and Planning,Sun Yat-sen University;
  • 关键词:洪水预报 ; 分布式物理水文模型 ; 流溪河模型
  • 英文关键词:flood forecasting;;physically based distributed hydrological model;;Liuxihe model
  • 中文刊名:ZNSD
  • 英文刊名:China Rural Water and Hydropower
  • 机构:河南省白龟山水库管理局;中山大学地理科学与规划学院;
  • 出版日期:2017-09-15
  • 出版单位:中国农村水利水电
  • 年:2017
  • 期:No.419
  • 基金:河南省水利厅科技项目(GG201402);; 国家自然科学基金项目(50479033)
  • 语种:中文;
  • 页:ZNSD201709014
  • 页数:7
  • CN:09
  • ISSN:42-1419/TV
  • 分类号:62-67+71
摘要
白龟山水库流域下垫面条件复杂,人类活动剧烈,洪水受上游昭平台水库影响,洪水预报难度大,采用常规的洪水预报模型无法满足水库防洪调度对洪水预报的精度要求。为了充分发挥水库在淮河流域防洪中的作用,实现水库洪水资源的最大化利用,需要高精度的水库入库洪水预报作支撑。采用国内外新一代流域洪水预报模型——流溪河模型开展了白龟山水库入库洪水预报研究。以高分辨率的DEM为依据,构建了白龟山水库入库洪水预报流溪河模型结构,并确定了初始模型参数,采用PSO优化算法,对模型参数进行了自动优选。对白龟山水库实测入库洪水过程进行了模拟,效果明显优于集总式NAM模型,可应用于白龟山水库入库洪水预报。
        Due to the complex terrain property,extreme human activity and the impact of Zhaopintai Reservoir in the upstream,the flood forecasting of Baiguishan Reservoir is difficult,and the traditional flood forecasting model can provide no accurate flood forecasting for reservoir flood regulation. To play its potential capability in Huaihe flood mitigation,fulfill the maximum benefit of flood resource utilization,high accuracy flood forecasting is the key support for fulfilling the reservoir ' s flood mitigation capability. This paper studies the flood forecasting model by employing the new generation flood forecasting model-the Liuxihe Model. Based on the high resolution DEM,the model structure is set up first with the initial model parameter derived,then the model parameters are optimized by using the PSO algorithm.Observed flood events are simulated by the model,the results are better than those of NAM model,a lumped hydrological model,and can be used to forecast the flood of Baiguishan Reservoir.
引文
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