Evaluation of multi‐source precipitation data in a watershed with complex topography based on distributed hydrological modeling

降水 插值(计算机图形学) 环境科学 地表径流 分水岭 遥感 气候学 气象学 卫星 计算机科学 地质学 地理 机器学习 人工智能 运动(物理) 工程类 生物 航空航天工程 生态学
作者
Wei-Chen Wang,Lian Sun,Yanpeng Cai,Yujun Yi,Wei Yang,Zhifeng Yang
出处
期刊:River Research and Applications [Wiley]
卷期号:37 (8): 1115-1133 被引量:21
标识
DOI:10.1002/rra.3681
摘要

Abstract Hydrological simulation in areas with complex topography and pronounced climatic heterogeneity has a certain degree of uncertainty, and how precipitation data from multiple types of sources influence hydrological simulation remains unclear. Performances of precipitation datasets based on multiple interpolation methods (i.e., inverse distance weighted [IDW], cokriging, and ANUSPLIN) and satellite remote sensing datasets (i.e., tropical rainfall measuring mission multi‐satellite precipitation analysis 3B42 version7 [TRMM 3B42V7], precipitation estimation from remote sensing information using artificial neural networks–climate data record [PERSIANN‐CDR], climate predication centre morphing technique, and sian precipitation–highly resolved observational data integration towards evaluation of water resources [APHRODITE]) were obtained for comparison. Hydrological responses from these precipitation datasets were evaluated through distributed hydrological model variable infiltration capacity. The Yalong river basin (YRB), located in the Hengduan Mountains region and characterized by the significant heterogeneity of precipitation in China, was focused. Four sub‐regions (i.e., sub‐region I to IV) were divided. The results indicated that: (a) TRMM 3B42V7 and APHRODITE data were superior in detection capability from daily to annual measurement than other satellite precipitation data sets generally; (b) under the scale of gauges, TRMM 3B42V7, APHRODITE, and cokriging performed well in sub‐regions I, II, and IV, respectively. In sub‐region III, performance of the interpolation methods was better than that of TRMM 3B42V7; (c) the interpolation datasets exhibited a poor capability to simulate peak runoff. The combination dataset COM could improve the overall runoff simulation in flood periods; and (d) the interpolation method has the problem of excessive smoothness. Whatever the interpolation dataset is, hydrological simulation tends to result in smaller runoff, which was related to that the measurements from meteorological stations in mountainous valleys are not necessarily representative of the entire region. In this paper, the applicability of multi‐source precipitation data in the hydrological simulation process of YRB was comprehensively analysed, which could provide effective references for improving the accuracy of precipitation data and the applicability of hydrological simulation.
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