Evaluating E-OBS forcing data for large-sample hydrology using model performance diagnostics

Clerc-Schwarzenbach, Franziska; do Nascimento, Thiago V. M.

doi:10.5194/hess-30-119-2026

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.

https://doi.org/10.5194/hess-30-119-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 30, issue 1

Research article

|

13 Jan 2026

Research article |

| 13 Jan 2026

Evaluating E-OBS forcing data for large-sample hydrology using model performance diagnostics

Franziska Clerc-Schwarzenbach and Thiago V. M. do Nascimento

Supplement

https://doi.org/10.5194/hess-30-119-2026-supplement

Data sets

CAMELS-DK: Hydrometeorological Time Series and Landscape Attributes for 3330 Catchments in Denmark J. Koch et al. https://doi.org/10.22008/FK2/AZXSYP

CAMELS-FR dataset O. Delaigue et al. https://doi.org/10.57745/WH7FJR

CAMELS-DE: hydrometeorological time series and attributes for 1582 catchments in Germany A. Dolich et al. https://doi.org/10.5281/zenodo.13837553

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

BULL Database – Spanish Basin attributes for Unraveling Learning in Large-sample hydrology [Dataset] (1) J. Senent-Aparicio et al. https://doi.org/10.5281/zenodo.10844207

Hydroklimatiska förhållanden i Sverige 1961-2020 - Nederbörd, temperatur och avrinningsobservationer i 50 avrinningsområden (CAMELS-SE) [Dataset] C. Teutschbein https://doi.org/10.57804/t3rm-v029

Catchment attributes and hydro- meteorological time series for large-sample studies across hydrologic Switzerland (CAMELS-CH) [Dataset] (0.9) M. Höge et al. https://doi.org/10.5281/zenodo.15025258

EStreams: An Integrated Dataset and Catalogue of Streamflow, Hydro-Climatic Variables and Landscape Descriptors for Eu- rope (1.4) T. V. M. do Nascimento et al. https://doi.org/10.5281/zenodo.17598150

Model code and software

Code from: "Evaluating E-OBS forcing data for large-sample hydrology using model performance diagnostics" T. V. M. do Nascimento and F. Clerc-Schwarzenbach https://doi.org/10.5281/zenodo.17943610

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.