Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 28, issue 17
Articles | Volume 28, issue 17
https://doi.org/10.5194/hess-28-4219-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-4219-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 28, issue 17
Research article
 | Highlight paper
 | 
12 Sep 2024
Research article | Highlight paper |  | 12 Sep 2024

Large-sample hydrology – a few camels or a whole caravan?

Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert

Data sets

Caravan - A global community dataset for large-sample hydrology F. Kratzert et al. https://doi.org/10.5281/zenodo.7944025

Catchment attributes for large-sample studies N. Addor et al. https://doi.org/10.5065/D6G73C3Q

A large-sample watershed-scale hydrometeorological dataset for the contiguous USA A. Newman et al. https://doi.org/10.5065/D6MW2F4D

CAMELS-BR: Hydrometeorological time series and landscape attributes for 897 catchments in Brazil - link to files V. B. P. Chagas et al. https://doi.org/10.5281/zenodo.3964745

Catchment attributes and hydro-meteorological timeseries for 671 catchments across Great Britain (CAMELS-GB) G. Coxon et al. https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9

Model code and software

A few camels or a whole caravan? F. Clerc-Schwarzenbach https://doi.org/10.5281/zenodo.10784701

HBV-light download University of Zurich, Department of Geography https://www.geo.uzh.ch/en/units/h2k/Services/HBV-Model/HBV-Download.html

Scientific colour maps F. Crameri https://doi.org/10.5281/zenodo.8409685

scico: colour palettes based on the scientific colour-maps T. L. Pedersen and F. Crameri https://CRAN.R-project.org/package=scico

hydroGOF: goodness-of-fit functions for comparison of simulated and observed hydrological time series M. Zambrano-Bigiarini https://doi.org/10.5281/zenodo.839854

vioplot: violin plot D. Adler et al. https://github.com/TomKellyGenetics/vioplot

rworldxtra: country boundaries at high resolution A. South https://CRAN.R-project.org/package=rworldxtra

maps: draw geographical maps R. A. Becker et al. https://CRAN.R-project.org/package=maps

Video abstract

Large-sample hydrology – A few camels or a whole caravan? F. Clerc-Schwarzenbach https://doi.org/10.5446/68349

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Executive editor
Large sample hydrology datasets such as Caravan provides the community with hydrometeorological information and catchment attributes for many catchments in the world and offers the opportunity for hydrological research. However, there are considerable differences between the forcing data of Caravan compared to the CAMELS datasets, especially with potential evaporation. This can lead to wrong conclusions on catchment hydrological drivers and affect regionalization. This papers shows the important of robustness of large sample datasets and the need to keep assessing that.
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Short summary
We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
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