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Sciences in Cold and Arid Regions ›› 2015, Vol. 7 ›› Issue (2): 157-169.doi: 10.3724/SP.J.1226.2015.00157

• ARTICLES • Previous Articles    

Accuracy evaluation of two precipitation datasets over upper reach of Heihe River Basin, northwestern China

SiWei He1,2, ZhuoTong Nan1, YuTing Hou3   

  1. 1. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China;
    2. Civil and Architectural Engineering Department, University of Wyoming, Laramie, WY 82071, USA;
    3. Shiyan Environmental Protection Monitoring Station, Shiyan, Hubei 442000, China
  • Received:2014-07-12 Revised:2014-11-21 Published:2018-11-23
  • Contact: Dr. ZhuoTong Nan, Professor of Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. No. 320, West Donggang Road, Lanzhou, Gansu 730000, China. Tel: +86-931-4967236; E-mail: nztong@lzb.ac.cn E-mail:nztong@lzb.ac.cn
  • Supported by:
    This study was supported by NSFC (91125006) and partially by state key laboratory grant (SKLFSE201009).

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Abstract: As an important forcing data for hydrologic models, precipitation has significant effects on model simulation. The China Meteorological Forcing Dataset (ITP) and Global Land Data Assimilation System (GLDAS) precipitation data are the two commonly used data sources in the Heihe River Basin (HRB). This paper focused on evaluating the accuracy of these two precipitation datasets. A set of metrics were developed to characterize the trend, magnitude, annual allocation, event matching, frequency, and spatial distribution of the two datasets. Meanwhile, such accuracy evaluation was performed at various scales, i.e., daily, monthly, and yearly. By comparing with observations, this study concluded that: first, both ITP and GLDAS precipitation data well represented the trends at corresponding sites, and GLDAS underestimated precipitation in most regions except the east tributary headwater region; second, unusual annual precipitation distribution was observed in both datasets with overestimation of precipitation in May through September and GLDAS appeared to be much severe; third, the ITP data seriously over-predicted the precipitation events; fourth, the ITP data have better spatial distribution than GLDAS in the upper reach area of HRB. Overall, we recommended ITP precipitation data for the land surface study in the upper reach of HRB.

Key words: precipitation, Heihe River Basin (HRB), accuracy evaluation

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