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基于分布式水文模型的“尼伯特”台风暴雨洪水反演
作者姓名:徐帅帅  王雅莉  陈淑芬  刘荣华  曲丽英  田济扬
作者单位:山东建筑大学市政与环境工程学院;中国水利水电科学研究院;河海大学水文水资源学院;水利部防洪抗旱减灾工程技术研究中心;福建省水利水电科学研究院
基金项目:国家重点研发计划(2017YFB0203104);国家自然科学基金(51579131);中国博士后科学基金(2017M620839);中国水科院科研专项(JZ0145B042016);山东建筑大学博士基金(0000601489)
摘    要:台风暴雨具有强度大、降雨集中的特点,容易在沿海地区中小流域形成局地破坏性洪水灾害,基于高精度地形地貌数据构建分布式水文模型,是实现中小流域洪水模拟和预报的重要手段。以福建闽清县梅溪流域为研究区,基于高精度DEM、土壤和土地利用数据,采用中国山洪水文模型(CNFF-HM),构建了梅溪流域分布式水文模型,以56场实测水文气象资料对模型进行率定和验证,并对2016年7月9日发生的"尼伯特"台风带来的暴雨洪水进行反演。结果显示,构建的分布式水文模型验证和率定效果良好,对"尼伯特"台风暴雨洪水模拟的洪峰流量误差小于20%,确定性系数达到0.96,因此模型能够很好地反映流域短历时强降雨引发的洪水特征,为流域防洪减灾提供可靠的技术支撑。

关 键 词:分布式水文模型  降雨分析  洪水反演  尼伯特台风

Characterization and simulation of 'Niebert' typhoon rain and flood in Meixi River basin
Authors:XU Shuaishuai  WANG Yali  CHEN Shufen  LIU Ronghu  QU Liying  TIAN Jiyang
Affiliation:(1.School of Municipal and Environmental Engineering,Shandong Jianzhu University,Jinan 250101,China;2.China Institute of Water Resources and Hydropower Research,Beijing 100038,China;3.Research Center on Flood and Drought Disaster Reduction of the Ministry of Water Resources,Beijing 100038,China;4.Fujian Institute of Water Resource & Hydropower Research,Fuzhou 350004,China;5.College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China)
Abstract:The typhoon storm has the characteristics of high intensity and concentrated rainfall.It is easy to form local destructive flood disasters in the middle and small sized watersheds of coastal areas.The distributed hydrological model based on high resolution topographic and geomorphic data is an effective way to forecast flood in small and medium sized basins.The Meixi River Basin in Minqing County of Fujian Province was selected as out study region.The China Flash Flood Model (CNFF-HM),based on the high resolution DEM,soil data,and land use data,was used to build the distributed hydrological model of the Meixi Basin.Fifty six hydrological events were used to calibrate and validate the model.The flood caused by the ''Niebert'' typhoon,which occurred on 9 July 2016,was simulated. The result showed the model performance was good with a less than 20% error for flood peak flow,and a Nash Sutcliffe efficiency coefficient (NSE) of 0-96.Thus the model can reflect the flood characteristics caused by short-term heavy rainfall in the basin,and provide reliable technical support for disaster prevention and reduction in the basin.
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