4.7 Article

Assessment of four latest long-term satellite-based precipitation products in capturing the extreme precipitation and streamflow across a humid region of southern China

期刊

ATMOSPHERIC RESEARCH
卷 257, 期 -, 页码 -

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.atmosres.2021.105554

关键词

Satellite-based precipitation product; Extreme precipitation; Extreme streamflow; Distributed hydrological model

资金

  1. National Key Research and Development Program of China [2016YFC0402709]
  2. National Natural Science Foundation of China [41890823]
  3. Strategic Priority Research Program of the Chinese Academy of Sciences [XDA23040304]

向作者/读者索取更多资源

This study evaluates the accuracy of four widely used long time series Satellite-based precipitation products in capturing extreme precipitation and streamflow events in a humid region of southern China. Different products show varying performances in extreme precipitation detection and streamflow simulation, with TMPA demonstrating superior results in both extreme precipitation detection and hydrological model simulation.
The lack of ground-based observation data usually limits the analysis of extreme precipitation and streamflow, especially for the ungauged or data-limited regions. Satellite-based precipitation products (SPPs) with high temporal and spatial resolutions can provide potential data sources in the regions without adequate precipitation data, and it has received much attention of regional or global hydro-climatic analysis. This study aims to evaluate the accuracy of four widely used long time series SPPs (CHIRPS, TMPA, CMORPH and PERSIANN) in capturing extreme precipitation and streamflow events in a humid region of southern China. It is found that, for extreme precipitation detection, both CMORPH and TMPA can capture most heavy and extreme precipitation, CMORPH works better on the rainfall distribution characteristics, while TMPA shows the best performance in capturing the extreme precipitation events with relatively low RMSE, ME and BIAS, and high R values of extreme precipitation indices. For the streamflow simulation, the combinations of different inputs and different models present different model performances. TMPA provides the most accurate hydrological model simulation results, while simulated streamflow forced by CMORPH exhibits considerable underestimation of streamflow. However, the combination of CMORPH and VIC model obtains the best efficiency for detecting extreme streamflow, followed by the combination of TMPA and SWAT model, which indicates the selection of a suitable model and input data is essential to obtain reliable and accurate results for the detection of extreme streamflow. This study is expected to provide a valuable reference for the application and comparison of multiple SPPs and models at watershed scales.

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