基于多源降水数据估算澜湄流域可能最大降水  

Estimating probable maximum precipitation based on multisource data of precipitation in the Lancang-Mekong River basin

作　　者：熊景华 郭靖 郭生练[2] 李娜[2] 王俊 尹家波[2] 唐俊龙 XIONG Jinghua;GUO Jing;GUO Shenglian;LI Na;WANG Jun;YIN Jiabo;TANG Junlong(Power China Hua Dong Engineering Corporation Limited,Hangzhou 311122,China;State Key Laboratory of Water Resources and Hydropower Engineering Science,Wuhan University,Wuhan 430072,China)

机构地区：[1]中国电建集团华东勘测设计研究院有限公司,杭州311122 [2]武汉大学水资源与水电工程科学国家重点实验室,武汉430072

出　　处：《水力发电学报》2022年第9期77-86,共10页Journal of Hydroelectric Engineering

基　　金：国家“十四五”重点研发计划项目(2021YFC3200301;KY2020-GH-05-01-2022)。

摘　　要：基于多源降水数据估算流域可能最大降水(PMP),对推求稀缺资料地区的设计和校核洪水具有重要意义。选取澜沧江-湄公河流域为研究区域,以APHRODITE降水数据集和实测降水为基准,评价CHIRPS、MSWEP和PERSIANN三套全球降水产品的精度,基于改进的统计法估算1天和3天的PMP。结果表明:(1)MSWEP产品具有较高的精度和降水探测能力;(2)栅格尺度下MSWEP与APHRODITE降水数据的PMP估算结果显著相关;(3)基于MSWEP卫星降水数据估算的湄公河流域1天和3天的PMP分别为122 mm和192 mm,与其他的PMP估算结果相近。卫星降水数据可为缺乏资料地区的PMP估算提供重要参考依据。Multi-source precipitation products play important roles in estimation of possible maximum precipitation(PMP),especially for data-sparse regions.This study evaluates the accuracy of three global precipitation products-i.e.Climate Hazards Group Infrared Precipitation with Station(CHIRPS),Multi-Source Weighted-Ensemble Precipitation(MSWEP),and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks(PERSIANN)-based on the Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation(APHRODITE)dataset and in-situ measurements in the Lancang-Mekong River basin.An improved statistical method is used to estimate the 1d and 3d PMPs.Results show that(1)the MSWEP dataset presents the satisfactory accuracy and precipitation detection ability;(2)the MSWEP-based PMP is significantly correlated with the APHRODITE results at the grid-cell scale;(3)the MSWEP-based 1 d and 3 d PMP estimates are 122 and 192 mm,respectively,comparable to the previous estimation results.This study indicates that the global precipitation products are useful to PMP estimation for data-sparse regions.

关 键 词：多源数据 可能最大降水 统计法 设计洪水 澜沧江-湄公河流域 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置] P333[自动化与计算机技术—控制科学与工程]