Articles | Volume 14, issue 2
https://doi.org/10.5194/essd-14-665-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-665-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
17 Feb 2022
Data description paper |
| 17 Feb 2022
| 17 Feb 2022
Rainfall erosivity mapping over mainland China based on high-density hourly rainfall records
Tianyu Yue
State Key Laboratory of Earth Surface Processes and Resource Ecology,
Faculty of Geographical Science, Beijing Normal University, Beijing, 100875,
China
Shuiqing Yin
CORRESPONDING AUTHOR
State Key Laboratory of Earth Surface Processes and Resource Ecology,
Faculty of Geographical Science, Beijing Normal University, Beijing, 100875,
China
Yun Xie
State Key Laboratory of Earth Surface Processes and Resource Ecology,
Faculty of Geographical Science, Beijing Normal University, Beijing, 100875,
China
Bofu Yu
Australian Rivers Institute, School of Engineering and Built
Environment, Griffith University, Nathan, Queensland, QLD 4111, Australia
Baoyuan Liu
State Key Laboratory of Earth Surface Processes and Resource Ecology,
Faculty of Geographical Science, Beijing Normal University, Beijing, 100875,
China
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Short summary
This paper provides new rainfall erosivity maps over mainland China based on hourly data from 2381 stations (available at https://doi.org/10.12275/bnu.clicia.rainfallerosivity.CN.001). The improvement from the previous work was also assessed. The improvement in the R-factor map occurred mainly in the western region, because of an increase in the number of stations and an increased temporal resolution from daily to hourly data.
This paper provides new rainfall erosivity maps over mainland China based on hourly data from...
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