Data-driven estimation of the hydrologic response using generalized additive models

Duchemin, Quentin; Zanoni, Maria Grazia; Floriancic, Marius G.; Seybold, Hansjörg; Obozinski, Guillaume; Kirchner, James W.; Benettin, Paolo

doi:10.5194/gmd-18-8663-2025

Articles | Volume 18, issue 22

https://doi.org/10.5194/gmd-18-8663-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-18-8663-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 22

Model description paper

|

17 Nov 2025

Model description paper |

| 17 Nov 2025

Data-driven estimation of the hydrologic response using generalized additive models

Quentin Duchemin, Maria Grazia Zanoni, Marius G. Floriancic, Hansjörg Seybold, Guillaume Obozinski, James W. Kirchner, and Paolo Benettin

Supplement

https://doi.org/10.5194/gmd-18-8663-2025-supplement

Data sets

GAMCR paper: Data Quentin Duchemin et al. https://doi.org/10.5281/zenodo.15180911

Model code and software

GAMCR Quentin Duchemin https://github.com/quentin-duchemin/GAMCR/

quentin-duchemin/GAMCR: GAMCR package Quentin Duchemin https://doi.org/10.5281/zenodo.15180816

Short summary

We introduce GAMCR (Generalized Additive Models for Catchment Responses), a data-driven model that estimates how catchments respond to individual precipitation events. We validate GAMCR on synthetic data and demonstrate its ability to investigate the characteristic runoff responses from real-world hydrologic series. GAMCR provides new data-driven opportunities to understand and compare hydrological behavior across different catchments.