Articles | Volume 13, issue 12
https://doi.org/10.5194/essd-13-5483-2021
© Author(s) 2021. 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-13-5483-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
30 Nov 2021
Data description paper |
| 30 Nov 2021
| 30 Nov 2021
GRQA: Global River Water Quality Archive
Department of Geography, Institute of Ecology and Earth Sciences, University of Tartu, Vanemuise 46, Tartu, 51003, Estonia
Giuseppe Amatulli
School of the Environment, Yale University, New Haven, CT, 06511, USA
Center for Research Computing, Yale University, New Haven, CT, 06511, USA
Alexander Kmoch
Department of Geography, Institute of Ecology and Earth Sciences, University of Tartu, Vanemuise 46, Tartu, 51003, Estonia
Longzhu Shen
HyperAmp, Barnwell Road, Cambridge CB5 8RQ, UK
Spatial-Ecology, Meaderville House, Wheal Buller, Redruth TR16 6ST, UK
Evelyn Uuemaa
Department of Geography, Institute of Ecology and Earth Sciences, University of Tartu, Vanemuise 46, Tartu, 51003, Estonia
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- Deep learning for water quality W. Zhi et al. 10.1038/s44221-024-00202-z
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- Data limitations in developing countries make river restoration planning challenging. Study case of the Cesar River, Colombia S. Vega et al. 10.1016/j.ecohyd.2024.01.012
- Sharing FAIR monitoring program data improves discoverability and reuse J. Bayer et al. 10.1007/s10661-023-11788-4
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Latest update: 20 Nov 2024
Short summary
Water quality modeling is essential for understanding and mitigating water quality deterioration in river networks due to agricultural and industrial pollution. Improving the availability and usability of open data is vital to support global water quality modeling efforts. The GRQA extends the spatial and temporal coverage of previously available water quality data and provides a reproducible workflow for combining multi-source water quality datasets.
Water quality modeling is essential for understanding and mitigating water quality deterioration...
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