Articles | Volume 13, issue 8
https://doi.org/10.5194/essd-13-3847-2021
© 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-13-3847-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
06 Aug 2021
Data description article |
| 06 Aug 2021
| 06 Aug 2021
CAMELS-AUS: hydrometeorological time series and landscape attributes for 222 catchments in Australia
Keirnan J. A. Fowler
CORRESPONDING AUTHOR
Department of Infrastructure Engineering, University of Melbourne,
Parkville, Victoria, Australia
Suwash Chandra Acharya
Department of Infrastructure Engineering, University of Melbourne,
Parkville, Victoria, Australia
Nans Addor
Department of Geography, University of Exeter, Exeter, UK
Chihchung Chou
Department of Infrastructure Engineering, University of Melbourne,
Parkville, Victoria, Australia
now at: Department of Earth Sciences, Barcelona Supercomputing
Centre, Barcelona, Spain
Murray C. Peel
Department of Infrastructure Engineering, University of Melbourne,
Parkville, Victoria, Australia
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Keirnan Fowler, Murray Peel, Margarita Saft, Tim J. Peterson, Andrew Western, Lawrence Band, Cuan Petheram, Sandra Dharmadi, Kim Seong Tan, Lu Zhang, Patrick Lane, Anthony Kiem, Lucy Marshall, Anne Griebel, Belinda E. Medlyn, Dongryeol Ryu, Giancarlo Bonotto, Conrad Wasko, Anna Ukkola, Clare Stephens, Andrew Frost, Hansini Gardiya Weligamage, Patricia Saco, Hongxing Zheng, Francis Chiew, Edoardo Daly, Glen Walker, R. Willem Vervoort, Justin Hughes, Luca Trotter, Brad Neal, Ian Cartwright, and Rory Nathan
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We present a cascade of models to compute high-resolution river flooding. This takes meteorological inputs, e.g., rainfall and temperature from observations or climate models, and takes them through a series of modeling steps. This is relevant to evaluating current day and future flood risk and impacts. The model framework uses global data sets, allowing it to be applied anywhere in the world.
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Short summary
This paper presents the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS comprises data for 222 unregulated catchments with long-term monitoring, combining hydrometeorological time series (streamflow and 18 climatic variables) with 134 attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. It is freely downloadable from https://doi.pangaea.de/10.1594/PANGAEA.921850.
This paper presents the Australian edition of the Catchment Attributes and Meteorology for...
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