摘要
新一代全球卫星降水产品GPM(Global Precipitation Measurement)为降雨观测提供了新的途径。以淮河上游王家坝流域为研究区,以地面实测降雨数据为基准,空间上从点、面尺度,时间上从日、月尺度综合评价了GPM卫星降水数据的精度,并结合分布式的SWAT(Soil and Water Assessment Tool)模型评估了GPM用于水文模拟的适用性,以探究GPM卫星降水数据对地面实测降水数据的可替代性。结果显示:(1)从日尺度聚合到月尺度、从点尺度平均到面尺度,GPM的降雨精度逐渐提高,在面尺度上统计月尺度GPM降雨具有最高的精度(相关系数CC=0.95,均方根误差RMSE=1.10 mm,平均绝对误差MAE=0.79 mm);(2) GPM整体上表现出对实测降雨的高估(相对误差BIAS为17.50%~24.14%),高估主要发生在低降雨强度事件和降雨相对不充足的非汛期,对高强度降雨和汛期的降雨估算精度较高,河源山区和淮河干流以南的湿润地区因降雨量大GPM精度高;(3)当采用静态参数法(沿用地面实测降雨率定的SWAT模型参数)时,GPM驱动的日尺度SWAT模型模拟精度出现了严重的退化,但是月尺度的SWAT模型仍然能保持可靠的精度;(4)当采用动态参数法(基于GPM降雨重新率定SWAT模型参数)时,GPM驱动的SWAT模型在日尺度和月尺度上的模拟精度均能得到保证。研究结果表明,GPM虽然对日降雨过程的刻画不准确,但在月降雨总量的估算上精度较高,因此GPM在月尺度的水文模拟上能够基本替代地面实测降雨数据。此外,对于无降雨资料的地区,基于GPM历史数据率定水文模型参数用于水文模拟具有更好的适用性。
The new generation of global satellite precipitation product,GPM(Global Precipitation Measurement),offers an innovative approach to rainfall estimation.Taking the gauge′s observations as the reference,the accuracy of GPM satellite precipitation data is comprehensively evaluated from point to subbasin scale spatially and from daily to monthly scale temporally in the Wangjiaba Basin,located in the upper Huaihe River Basin.Furthermore,by integrating the distributed SWAT(Soil And Water Assessment Tool)model,the applicability of GPM for hydrological simulation is also evaluated.The results show that:①From the aggregation of daily scale to the monthly scale,from the average of point scale to the subbasin scale,the rainfall accuracy of GPM is gradually improved.On an area-based scale,the statistical monthly GPM rainfall achieves the highest accuracy(correlation coefficient CC=0.95,root mean square error RMSE=1.10 mm,average absolute error MAE=0.79 mm).②GPM overestimates generally against the measured rainfall(relative error BIAS=17.50%~24.14%),particularly during non-flood seasons with low rainfall intensity and frequency.However,GPM demonstrates high accuracy in estimating high-intensity rainfall and rainfall during flood seasons,and the accuracy of GPM is particularly high in mountain regions and humid areas located in the south part of the Huaihe River′s mainstream due to abundant rainfall.③When the static parameter method(i.e.the SWAT model parameters determined by the gauge observation)is adopted,the daily simulation accuracy which is driven by GPM is significantly degraded,but the monthly SWAT model can still maintain reliable accuracy.④By adopting the dynamic parameter method(re-calibration of SWAT model parameters based on GPM rainfall),the daily and monthly simulation accuracies based on GPM rainfall can be guaranteed.This study indicates that although GPM may not accurately capture the daily rainfall processes,it exhibits high accuracy in estimating the total monthly rainfall.Therefore,GPM can basically substitute for gauge-based rainfall data in monthly flow simulation.In addition,for areas lacking rainfall data,the calibration of hydrological model parameters based on GPM historical data demonstrates good applicability for hydrological simulation.
作者
赵乔
王海政
刘兴举
丁光旭
黄莉
甘恒玉
ZHAO Qiao;WANG Haizheng;LIU Xingju;DING Guangxu;HUANG Li;GAN Hengyu(powerchina Guiyang Engineering Corporation Limited.,Guiyang 550081,China;China Renewable Energy Engineering Institute,Beijing 100120,China;Guizhou Wujiang Hydropower Development Co.,Ltd.,Guiyang 550002,China)
出处
《人民长江》
北大核心
2025年第11期110-118,共9页
Yangtze River
基金
2023年贵阳院重点科研课题(YJ2023-11)
贵州省水利厅科技项目(KT202302)
贵州省科技计划项目(黔科合成果(2025)一般001)。
关键词
GPM卫星降水
SWAT模型
水文模拟
淮河流域
GPM satellite precipitation
SWAT model
hydrological simulation
Huaihe River Basin
