• Documentation: https://smash.recover.inrae.fr
• Source code: https://github.com/DassHydro/smash
• Contributing: https://smash.recover.inrae.fr/contributor_guide/index.html
• Scientific references from latest version: https://smash.recover.inrae.fr/bibliography/index.html
• Bug reports: https://github.com/DassHydro/smash/issues

smash is a Python library, that provides a variety of user-friendly routines for hydrological modeling, including data preprocessing, high-dimensional optimization tools, sensitivity and signatures analysis, all interfaced with an efficient Fortran solver.

smash offers a range of advanced optimization techniques, including Variational Data Assimilation (VDA), Bayesian estimation, and Artificial Neural Network (ANN) approaches, using an adjoint model generated with the Tapenade Automatic Differentiation Engine.

• Tapenade website: https://team.inria.fr/ecuador/en/tapenade/
• Tapenade article: https://doi.org/10.1145/2450153.2450158
• Tapenade source code: https://gitlab.inria.fr/tapenade/tapenade.git

Whether you are managing water resources or conducting research on hydrological models, smash can provide an easy-to-use yet powerful solution for your work. See this documentation for the installation instructions.