Articles | Volume 29, issue 3
https://doi.org/10.5194/hess-29-683-2025
https://doi.org/10.5194/hess-29-683-2025
Research article
 | 
05 Feb 2025
Research article |  | 05 Feb 2025

Lack of robustness of hydrological models: a large-sample diagnosis and an attempt to identify hydrological and climatic drivers

Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel

Related authors

On the use of streamflow transformations for hydrological model calibration
Guillaume Thirel, Léonard Santos, Olivier Delaigue, and Charles Perrin
Hydrol. Earth Syst. Sci., 28, 4837–4860, https://doi.org/10.5194/hess-28-4837-2024,https://doi.org/10.5194/hess-28-4837-2024, 2024
Short summary
Technical note: RAT – a robustness assessment test for calibrated and uncalibrated hydrological models
Pierre Nicolle, Vazken Andréassian, Paul Royer-Gaspard, Charles Perrin, Guillaume Thirel, Laurent Coron, and Léonard Santos
Hydrol. Earth Syst. Sci., 25, 5013–5027, https://doi.org/10.5194/hess-25-5013-2021,https://doi.org/10.5194/hess-25-5013-2021, 2021
Short summary
Technical note: Pitfalls in using log-transformed flows within the KGE criterion
Léonard Santos, Guillaume Thirel, and Charles Perrin
Hydrol. Earth Syst. Sci., 22, 4583–4591, https://doi.org/10.5194/hess-22-4583-2018,https://doi.org/10.5194/hess-22-4583-2018, 2018
Short summary
Continuous state-space representation of a bucket-type rainfall-runoff model: a case study with the GR4 model using state-space GR4 (version 1.0)
Léonard Santos, Guillaume Thirel, and Charles Perrin
Geosci. Model Dev., 11, 1591–1605, https://doi.org/10.5194/gmd-11-1591-2018,https://doi.org/10.5194/gmd-11-1591-2018, 2018
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Catchments do not strictly follow Budyko curves over multiple decades, but deviations are minor and predictable
Muhammad Ibrahim, Miriam Coenders-Gerrits, Ruud van der Ent, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1703–1723, https://doi.org/10.5194/hess-29-1703-2025,https://doi.org/10.5194/hess-29-1703-2025, 2025
Short summary
Scale dependency in modeling nivo-glacial hydrological systems: the case of the Arolla basin, Switzerland
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart N. Lane, and Francesco Comiti
Hydrol. Earth Syst. Sci., 29, 1725–1748, https://doi.org/10.5194/hess-29-1725-2025,https://doi.org/10.5194/hess-29-1725-2025, 2025
Short summary
Extended-range forecasting of stream water temperature with deep-learning models
Ryan S. Padrón, Massimiliano Zappa, Luzi Bernhard, and Konrad Bogner
Hydrol. Earth Syst. Sci., 29, 1685–1702, https://doi.org/10.5194/hess-29-1685-2025,https://doi.org/10.5194/hess-29-1685-2025, 2025
Short summary
Technical note: An approach for handling multiple temporal frequencies with different input dimensions using a single LSTM cell
Eduardo Acuña Espinoza, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Ralf Loritz, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1749–1758, https://doi.org/10.5194/hess-29-1749-2025,https://doi.org/10.5194/hess-29-1749-2025, 2025
Short summary
Projections of streamflow intermittence under climate change in European drying river networks
Louise Mimeau, Annika Künne, Alexandre Devers, Flora Branger, Sven Kralisch, Claire Lauvernet, Jean-Philippe Vidal, Núria Bonada, Zoltán Csabai, Heikki Mykrä, Petr Pařil, Luka Polović, and Thibault Datry
Hydrol. Earth Syst. Sci., 29, 1615–1636, https://doi.org/10.5194/hess-29-1615-2025,https://doi.org/10.5194/hess-29-1615-2025, 2025
Short summary

Cited articles

Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A., and Wood, E. F.: Present and future Köppen-Geiger climate classification maps at 1-km resolution, Sci. Data, 5, 180214, https://doi.org/10.1038/sdata.2018.214, 2018. 
Birhanu, D., Kim, H., Jang, C., and Park, S.: Does the Complexity of Evapotranspiration and Hydrological Models Enhance Robustness?, Sustainability, 10, 2837, https://doi.org/10.3390/su10082837, 2018. 
Blöschl, G., Bierkens, M. F. P., Chambel, A. et al.: Twenty-three unsolved problems in hydrology (UPH) – a community perspective, Hydrol. Sci. J., 64, 1141–1158, https://doi.org/10.1080/02626667.2019.1620507, 2019. 
Brigode, P., Oudin, L., and Perrin, C.: Hydrological model parameter instability: A source of additional uncertainty in estimating the hydrological impacts of climate change?, J. Hydrol., 476, 410–425, https://doi.org/10.1016/j.jhydrol.2012.11.012, 2013. 
Broderick, C., Matthews, T., Wilby, R. L., Bastola, S., and Murphy, C.: Transferability of hydrological models and ensemble averaging methods between contrasting climatic periods, Water Resour. Res., 52, 8343–8373, https://doi.org/10.1002/2016WR018850, 2016. 
Download
Short summary
This work investigates how hydrological models are transferred to a period in which climate conditions are different to the ones of the period in which they were set up. The robustness assessment test built to detect dependencies between model error and climatic drivers was applied to three hydrological models in 352 catchments in Denmark, France and Sweden. Potential issues are seen in a significant number of catchments for the models, even though the catchments differ for each model.
Share