Articles | Volume 30, issue 1
https://doi.org/10.5194/hess-30-119-2026
© Author(s) 2026. 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-30-119-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Jan 2026
Research article |
| 13 Jan 2026
| 13 Jan 2026
Evaluating E-OBS forcing data for large-sample hydrology using model performance diagnostics
Franziska Clerc-Schwarzenbach
Department of Geography, University of Zurich, Zurich, 8057, Switzerland
Thiago V. M. do Nascimento
CORRESPONDING AUTHOR
Department of Geography, University of Zurich, Zurich, 8057, Switzerland
Eawag: Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, 8600, Switzerland
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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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Short summary
This study provides the first assessment of an European meteorological dataset (E-OBS) for hydrological applications. We compared the dataset to meteorological datasets developed at a country level, and tested how the different data influenced the simulation of streamflow with hydrological model. Our findings show that, despite some limitations, the European dataset offers a reasonable basis for hydrological modelling in most river catchments across Europe.
This study provides the first assessment of an European meteorological dataset (E-OBS) for...
