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针对资料稀缺地区水文模拟计算难题,开展多源再分析降水数据在拉萨河流域应用对比研究,本文基于HIMS系统构建了拉萨河流域分布式水文模型,以气象站实测数据为参照,对比分析了中国区域地面降水格点日值数据集和中国区域高时空分辨率地面气象要素驱动数据集两套遥感再分析数据集的气象数据在拉萨河流域的径流模拟效果。结果表明:在日和月时间尺度上,气象站实测降水数据的径流模拟精度最好,驱动集降水数据径流模拟结果要好于网格点降水数据。总体上,基于气象站实测降水数据的径流模拟纳西效率系数为0.86(日过程)和0.93(月过程),相关系数均在0.9以上。基于两类再分析数据的降水径流模拟纳西效率系数均在0.7(日过程)和0.8(月过程)以上,相关系数均在0.9左右。对于资料稀缺地区,多源再分析降水数据是重要的可用数据来源。借助于降水—径流模型,探讨多源再分析降水数据对径流模拟精度的影响,是完善多源再分析降水数据产品质量的一个重要环节。
Aiming at the difficult problem of hydrological simulation in the area with scarce data, a multi-source reanalysis precipitation data comparison study was conducted in the Lhasa River Basin. Based on the HIMS system, a distributed hydrological model was constructed for the Lhasa River Basin. Based on the measured data from the weather station, Runoff simulation results of meteorological data of two sets of remote sensing reanalysis datasets in the Lhasa River Basin based on the daily precipitation dataset of regional grids and the ground meteorological element driving datasets of high temporal and spatial resolution in China. The results show that on the time scale of day and month, the runoff simulation accuracy of the observed precipitation data of the weather station is the best, and the runoff precipitation data of the driving set rainfall simulation result is better than the grid point precipitation data. In general, the runoff simulation Naxi efficiency coefficient based on the observed precipitation data of the weather station is 0.86 (day process) and 0.93 (month process), respectively, and the correlation coefficients are all above 0.9. The precipitation runoff simulation Naxi efficiency coefficients based on two types of reanalysis data are all above 0.7 (day process) and 0.8 (month process), and the correlation coefficients are all around 0.9. For areas with scarce data, multiple source reanalysis precipitation data is an important source of available data. With the aid of precipitation-runoff model, it is an important step to improve the quality of multi-source reanalysis precipitation data to explore the impact of multi-source reanalysis precipitation data on runoff simulation accuracy.