Articles | Volume 28, issue 17
https://doi.org/10.5194/hess-28-4219-2024
https://doi.org/10.5194/hess-28-4219-2024
Research article
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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

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Cited articles

Adam, J. C., Clark, E. A., Lettenmaier, D. P., and Wood, E. F.: Correction of global precipitation products for orographic effects, J. Climate, 19, 15–38, https://doi.org/10.1175/JCLI3604.1, 2006. 
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: Catchment attributes for large-sample studies, UCAR/NCAR, Boulder, CO [data set], https://doi.org/10.5065/D6G73C3Q, 2017a. 
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017b. 
Addor, N., Nearing, G., Prieto, C., Newman, A. J., Le Vine, N., and Clark, M. P.: A ranking of hydrological signatures based on their predictability in space, Water Resour. Res., 54, 8792–8812, https://doi.org/10.1029/2018WR022606, 2018. 
Addor, N., Do, H. X., Alvarez-Garreton, C., Coxon, G., Fowler, K., and Mendoza, P. A.: Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges, Hydrolog. Sci. J., 65, 712–725, https://doi.org/10.1080/02626667.2019.1683182, 2020. 
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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.
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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