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基于卫星降水数据的金沙江流域可能最大降水量计算方法 被引量:5

Calculation Method of Probable Maximum Precipitation in Jinshajiang River Basin Based on Satellite Precipitation Data
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摘要 为探索缺资料地区可能最大降水计算方法,以金沙江巴塘水文站以上流域为研究区,依据该流域测站降水资料,对MSWEP卫星降水数据进行精度评定。选取MSWEP自1979年以来的数据,采用统计估算法计算得到该流域1、3、7、15d可能最大降水量分别为25.2、49.1、86.1、150.9mm;同时,基于该流域及邻近地区的测站资料,采用水文气象法计算得到对应历时的可能最大降水量。对比两套结果发现,相同历时下前者计算结果与后者的相对偏差均在16%以内,表明在该流域基于MSWEP数据,采用统计估算法计算可能最大降水是有效可行的。研究结果不仅为该流域的可能最大洪水计算奠定了基础,更为缺资料地区的可能最大降水计算提供了新途径。 In order to explore the method for the probable maximum precipitation(PMP)calculation in ungauged region,the upstream of the Batang hydrological station in the Jinshajiang River was selected as research area.According to the observed precipitation data in the basin,the accuracy of satellite precipitation data MSWEP were evaluated.PMP was estimated through the statistical method,based on MSWEP data since 1979.The 1-day,3-day,7-day,and 15-day PMP were 25.2 mm,49.1 mm,86.1 mm and 150.9 mm,respectively.In addition,PMP was also calculated by hydrometeorological estimation method based on observation data in and around the basin correspondingly.The relative deviation between two estimated PMP for each given duration is less than 16%,which indicates that it is feasible and effective to calculate PMP based on MSWEP data using statistical estimation method in this basin.The research provides a basis for calculating the probable maximum flood in the basin and a new approach for PMP calculation in ungauged regions.
作者 吴成兴 李国芳 杨百银 夏传清 高洁 康有 WU Cheng-xing;LI Guo-fang;YANG Bai-yin;XIA Chuan-qing;GAO Jie;KANG You(College of Hydrology and Water Resources Hohai University,Nanjing 210098,China;China Renewable Energy Engineering Institute,Beijing 100120 China;PowerChina Chengdu Engineering Corporation Limited.Chengdu 610072,China)
出处 《水电能源科学》 北大核心 2020年第2期5-8,共4页 Water Resources and Power
基金 中国电力建设股份有限公司重大科技专项(DJ-ZDZX-2016-02-02) 国家重点研发计划(2018YFC1508001) 国家自然科学基金项目(51479061)。
关键词 可能最大降水 卫星降水数据 缺资料地区 统计估算法 水文气象法 probable maximum precipitation satellite precipitation data ungauged region statistical estimation method hydrometeorological estimation method
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