Citations and Related Papers#
How to cite smash#
For smash software use, please cite:
Colleoni, F., Huynh, N. N. T., Garambois, P.-A., Jay-Allemand, M., Organde, D., Renard, B., De Fournas, T., El Baz, A., Demargne, J., and Javelle, P. (2025). SMASH v1.0: A Differentiable and Regionalizable High-Resolution Hydrological Modeling and Data Assimilation Framework. Geosci. Model Dev., 18, 2025, 7003–7034. https://doi.org/10.5194/gmd-18-7003-2025.
BibTeX entry:
@article{Colleoni2025smash,
author = {Colleoni, François and Huynh, Ngo Nghi Truyen and Garambois, Pierre-André and Jay-Allemand, Maxime and Organde, Didier and Renard, Benjamin and De Fournas, Thomas and El Baz, Apolline and Demargne, Julie and Javelle, Pierre},
title = {SMASH v1.0: a differentiable and regionalizable high-resolution hydrological modeling and data assimilation framework},
journal = {Geoscientific Model Development},
volume = {18},
year = {2025},
number = {19},
pages = {7003--7034},
doi = {10.5194/gmd-18-7003-2025}
}
Please also cite the relevant references corresponding to the algorithms and methods used:
Hybrid physics-AI framework for learning regionalization and refining internal water fluxes of algebraic or ordinary differential equations (ODEs)-based solvers:
Huynh, N. N. T., Garambois, P.-A., Renard, B., Colleoni, F., Monnier, J., and Roux, H. (2025). A distributed hybrid physics–AI framework for learning corrections of internal hydrological fluxes and enhancing high-resolution regionalized flood modeling. Hydrol. Earth Syst. Sci., 29, 3589–3613. https://doi.org/10.5194/hess-29-3589-2025.
Huynh, N. N. T., Garambois, P.-A., Colleoni, F., and Monnier, J. (2025). Hybrid Physics-AI and Neural ODE Approaches for Spatially Distributed Hydrological Modeling. EGUsphere, 2025, 1–24. https://doi.org/10.5194/egusphere-2025-2797.
Hybrid Data Assimilation and Parameter Regionalization (HDA-PR) approach:
Huynh, N. N. T., Garambois, P.-A., Colleoni, F., Renard, B., Roux, H., Demargne, J., Jay-Allemand, M., and Javelle, P. (2024). Learning Regionalization Using Accurate Spatial Cost Gradients Within a Differentiable High-Resolution Hydrological Model: Application to the French Mediterranean Region. Water Resour. Res., 60, e2024WR037544. https://doi.org/10.1029/2024WR037544.
Signatures, multi-criteria calibration, hydrograph segmentation algorithm:
Huynh, N. N. T., Garambois, P.-A., Colleoni, F., and Javelle, P. (2023). Signatures-and-sensitivity-based multi-criteria variational calibration for distributed hydrological modeling applied to Mediterranean floods. J. Hydrol., 625, 129992. https://doi.org/10.1016/j.jhydrol.2023.129992.
Fully distributed variational calibration:
Jay-Allemand, M., Javelle, P., Gejadze, I., Arnaud, P., Malaterre, P.-O., Fine, J.-A., and Organde, D. (2020). On the potential of variational calibration for a fully distributed hydrological model: application on a Mediterranean catchment. Hydrol. Earth Syst. Sci., 24, 5519–5538. https://doi.org/10.5194/hess-24-5519-2020.
Related papers#
Additional smash-related publications:
Garambois, P.A., Colleoni, F., Huynh, N. N. T., Akhtari, A., Nguyen, N. B., El Baz, A., Jay-Allemand, M., and Javelle, P. (2025). Spatially distributed gradient-based calibration and parametric sensitivity of a spatialized hydrological model over 235 French catchments. J. Hydrol. : Reg. Stud., 60, 102485. https://doi.org/10.1016/j.ejrh.2025.102485.
Ettalbi, M., Garambois, P.A., Huynh, N. N. T., Arnaud, P., Ferreira, E., and Baghdadi, N. (2025). Improving parameter regionalization learning for spatialized differentiable hydrological models by assimilation of satellite-based soil moisture data. J. Hydrol., 660, 133300. https://doi.org/10.1016/j.jhydrol.2025.133300.
Jay‐Allemand, M., Demargne, J., Garambois, P.‐A., Javelle, P., Gejadze, I., Colleoni, F., Organde, D., Arnaud, P., and Fouchier, C. (2024). Spatially distributed calibration of ahydrological model with variational optimization constrained by physiographic maps for flash flood forecasting in France. Proceedings of IAHS, 385, 281–290. https://doi.org/10.5194/piahs-385-281-2024.
Evin, G., Le Lay, M., Fouchier, C., Penot, D., Colleoni, F., Mas, A., Garambois, P.-A., Laurantin, O. (2024). Evaluation of hydrological models on small mountainous catchments: impact of the meteorological forcings. Hydrol. Earth Syst. Sci., 28, 261–281. https://doi.org/10.5194/hess-28-261-2024.
Huynh, N. N. T., Garambois, P.‐A., Colleoni, F., Renard, B., and Roux, H. (2023). Multi‐gauge hydrological variational data assimilation:Regionalization learning with spatial gradients using multilayer perceptron and Bayesian‐guided multivariate regression. Colloque SHF 2023 - Prévision des crues et des inondations. https://doi.org/10.48550/arXiv.2307.02497.