Articles | Volume 28, issue 15
https://doi.org/10.5194/hess-28-3597-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-3597-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Aug 2024
Research article |
| 08 Aug 2024
| 08 Aug 2024
A decomposition approach to evaluating the local performance of global streamflow reanalysis
Tongtiegang Zhao
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Key Laboratory for Water Security in the Guangdong-Hongkong-Macao Greater Bay Area, School of Civil Engineering, Sun Yat-Sen University, Guangzhou, China
Zexin Chen
CORRESPONDING AUTHOR
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Key Laboratory for Water Security in the Guangdong-Hongkong-Macao Greater Bay Area, School of Civil Engineering, Sun Yat-Sen University, Guangzhou, China
Yu Tian
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resource and Hydropower Research, Beijing, China
Bingyao Zhang
School of Hydraulic Engineering, Dalian University of Technology, Dalian 116024, Liaoning, China
School of Hydraulic Engineering, Dalian University of Technology, Dalian 116024, Liaoning, China
Xiaohong Chen
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) and Key Laboratory for Water Security in the Guangdong-Hongkong-Macao Greater Bay Area, School of Civil Engineering, Sun Yat-Sen University, Guangzhou, China
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Short summary
The local performance plays a critical part in practical applications of global streamflow reanalysis. This paper develops a decomposition approach to evaluating streamflow analysis at different timescales. The reanalysis is observed to be more effective in characterizing seasonal, annual and multi-annual features than daily, weekly and monthly features. Also, the local performance is shown to be primarily influenced by precipitation seasonality, longitude, mean precipitation and mean slope.
The local performance plays a critical part in practical applications of global streamflow...
