星地数据融合的日降水产品及其径流模拟研究  

Daily Precipitation Estimates Merging Ground-Based Observations with Satellite-Derived Data and Its Runoff Simulated Performance

作　　者：闫鑫 陈华[2] 尚志宏[3] 王金星[4] YAN Xin;CHEN Hua;SHANG Zhi-hong;WANG Jin-xing(Anhui Survey and Design Institute of Water Resources and Hydropower Co.Ltd,Hefei 230088,Anhui Province,China;State Key Laboratory of Water Resources and Hydropower Engineering Science,Wuhan University,Wuhan 430072,Hubei Province,China;Bureau of Hydrology,Songliao Water Conservancy Commission,Changchun 130021,Jilin Province,China;Hydrology Bureau,Ministry of Water Resources,Beijing 100142,China)

机构地区：[1]安徽省水利水电勘测设计研究总院有限公司,安徽合肥230088 [2]武汉大学水资源与水电工程科学国家重点实验室,湖北武汉430072 [3]松辽水利委员会水文局,吉林长春130021 [4]水利部信息中心,北京100053

出　　处：《中国农村水利水电》2023年第6期36-46,共11页China Rural Water and Hydropower

基　　金：国家重点研发计划项目(2019YFC1510703)。

摘　　要：降水作为连接着大气过程与地表过程的一个水分通量,在水文、气象、生态等方面具有重要意义。由于降水较强的时空变异性,使其成为目前最不易准确测量的水文变量之一。准确、高效地获取高时空分辨率、高精度的降水数据对于水文以及气象分析研究是十分有意义的。以汉江流域为研究区,提出了两步降尺度融合方案,利用雨量站观测降水和卫星反演降水数据在可用性和准确性方面具有互补的特点,通过融合雨量站观测值和全球降水观测任务(Global Precipitation Measurement,GPM)卫星降水产品,生成0.01°的空间分辨率高精度的日降水产品。将获得的融合降水产品驱动分布式水文模型WASMOD-D来模拟降雨—径流过程,验证其径流模拟效果。结果表明:①基于随机森林模型的降尺度算法不仅显著提高了GPM降水的空间分辨率,而且也保持了较好的精度。②基于协同克里金法的降水数据线性融合模型,融合方法大大提高了GPM降水的估算精度,平均绝对误差和均方根误差分别降低了32.38%和21.38%,偏差下降到了1%以下;③综合两种不同情景下的日径流模拟效果来看,由于结合了卫星降水数据和站点降水数据的优势,融合降水数据的整体模拟效果最好,整体改善效果较为显著。研究为基于卫星—地面雨量站(Satellite-Gauge,S-G)降水数据融合的方法提供了新思路,研究结果可作为获取高分辨率、高精度的降水数据方法的参考。Precipitation is the basic component of the earth water cycle.As a water flux,it connects the atmospheric process with the surface process,and has important significance in meteorology,climatology and hydrology.Due to the strong temporal and spatial variability of precipitation,it is one of the most difficult hydrological variables to measure accurately at present.Accurate precipitation data with high temporal and spatial resolution is very important for many applications such as hydrological and meteorological analysis.This paper takes Hanjiang River Basin as the research area and puts forward a two-step downscaling-merging method.By using the complementary characteristics of data availability and accuracy of precipitation observed by rainfall gauges and retrieved by satellites,a high-quality daily precipitation product with a spatial resolution of 0.01 can be generated by fusing gauge observations and GPM satellite precipitation products.The obtained fused precipitation product is driven by semi-distributed hydrological model WASMOD-D to simulate the rainfall-runoff process,and its runoff simulation effect is verified.The results show that:①The downscaling algorithm based on random forest model not only significantly improves the spatial resolution of GPM precipitation,but also maintains good accuracy.②The linear fusion model of precipitation data based on the co-Kriging method,the fusion scheme greatly improves the estimation accuracy of GPM precipitation,with the average absolute error and root mean square error reduced by 32.38%and 21.38%respectively,and the bias dropped below 1%;③Considering the simulation results of daily runoff under two different scenarios,the overall simulation effect of integrating precipitation data is the best because of combining the advantages of satellite precipitation data and gauge observations,and the overall improvement effect is obvious.This paper provides a new idea for the data fusion method based on Satellite-Gauge(S-G),and the research results can be used as a refer

关 键 词：空间降尺度 数据融合 日降水 随机森林 协同克里金 

分 类 号：TV621[水利工程—水利水电工程]