Articles | Volume 28, issue 14
https://doi.org/10.5194/hess-28-3099-2024
© 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-28-3099-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Jul 2024
Research article |
| 17 Jul 2024
| 17 Jul 2024
Global-scale evaluation of precipitation datasets for hydrological modelling
Solomon H. Gebrechorkos
CORRESPONDING AUTHOR
School of Geography and the Environment, University of Oxford, Oxford, UK
School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
Julian Leyland
School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
Simon J. Dadson
School of Geography and the Environment, University of Oxford, Oxford, UK
Sagy Cohen
Department of Geography and the Environment, University of Alabama, Tuscaloosa, AL, USA
Louise Slater
School of Geography and the Environment, University of Oxford, Oxford, UK
Michel Wortmann
School of Geography and the Environment, University of Oxford, Oxford, UK
Philip J. Ashworth
School of Applied Sciences, University of Brighton, Brighton, Sussex, BN2 4AT, UK
Georgina L. Bennett
Department of Geography, Faculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4RJ, UK
Richard Boothroyd
School of Geographical & Earth Sciences, University of Glasgow, Glasgow, UK
Hannah Cloke
Department of Geography and Environmental Science, University of Reading, Reading, UK
Department of Meteorology, University of Reading, Reading, UK
Pauline Delorme
Energy and Environment Institute, University of Hull, Hull, UK
Helen Griffith
Department of Geography and Environmental Science, University of Reading, Reading, UK
Richard Hardy
Department of Geography, Durham University, Lower Mountjoy, South Road, Durham, DH1 3LE, UK
Laurence Hawker
School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
Stuart McLelland
Energy and Environment Institute, University of Hull, Hull, UK
Jeffrey Neal
School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
Andrew Nicholas
Department of Geography, Faculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4RJ, UK
Andrew J. Tatem
School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
Ellie Vahidi
Department of Geography, Faculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4RJ, UK
Yinxue Liu
School of Geography and the Environment, University of Oxford, Oxford, UK
Justin Sheffield
School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
Daniel R. Parsons
Energy and Environment Institute, University of Hull, Hull, UK
Geography and Environment, Loughborough University, Loughborough, UK
Stephen E. Darby
School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK
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Total article views: 1,443 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 26 Oct 2023)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,071 | 330 | 42 | 1,443 | 116 | 29 | 30 |
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- PDF: 330
- XML: 42
- Total: 1,443
- Supplement: 116
- BibTeX: 29
- EndNote: 30
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Total article views: 1,443 (including HTML, PDF, and XML)
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Total article views: 1,443 (including HTML, PDF, and XML)
Thereof 1,415 with geography defined
and 28 with unknown origin.
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Short summary
This study evaluated six high-resolution global precipitation datasets for hydrological modelling. MSWEP and ERA5 showed better performance, but spatial variability was high. The findings highlight the importance of careful dataset selection for river discharge modelling due to the lack of a universally superior dataset. Further improvements in global precipitation data products are needed.
This study evaluated six high-resolution global precipitation datasets for hydrological...
