Articles | Volume 18, issue 19
https://doi.org/10.5194/gmd-18-7003-2025
https://doi.org/10.5194/gmd-18-7003-2025
Model description paper
 | 
10 Oct 2025
Model description paper |  | 10 Oct 2025

smash v1.0: a differentiable and regionalizable high-resolution hydrological modeling and data assimilation framework

François Colleoni, Ngo Nghi Truyen Huynh, Pierre-André Garambois, Maxime Jay-Allemand, Didier Organde, Benjamin Renard, Thomas De Fournas, Apolline El Baz, Julie Demargne, and Pierre Javelle

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Latest update: 10 Oct 2025
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Short summary
We present smash, an open-source framework for high-resolution hydrological modeling and data assimilation. It combines process-based models with neural networks for regionalization, enabling accurate simulations from the catchment scale to the country scale. With an efficient, differentiable solver, smash supports large-scale calibration and parallel computing. Tested on open datasets, it shows strong performance in river flow prediction, making it a valuable tool for research and operational use.
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