Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 28, issue 9
Articles | Volume 28, issue 9
https://doi.org/10.5194/hess-28-2167-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-2167-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 28, issue 9
Research article
 | 
17 May 2024
Research article |  | 17 May 2024

Towards understanding the influence of seasons on low-groundwater periods based on explainable machine learning

Andreas Wunsch, Tanja Liesch, and Nico Goldscheider

Data sets

Weekly groundwater level time series dataset for 118 wells in Germany Andreas Wunsch et al. https://doi.org/10.5281/zenodo.4683879

Supplement material to the study: Towards understanding the influence of seasons on low groundwater periods based on explainable machine learning Andreas Wunsch https://doi.org/10.5281/zenodo.10157406

Model code and software

Influence-of-seasons-on-low-GW-periods Andreas Wunsch https://github.com/AndreasWunsch/influence-of-seasons-on-low-GW-periods

AndreasWunsch/influence-of-seasons-on-low-GW-periods: First release for Zenodo (v1.0) Andreas Wunsch https://doi.org/10.5281/zenodo.10156638

Influence-of-seasons-on-low-GW-periods - trained models and modeling results Andreas Wunsch https://doi.org/10.5281/zenodo.10156582

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Short summary
Seasons have a strong influence on groundwater levels, but relationships are complex and partly unknown. Using data from wells in Germany and an explainable machine learning approach, we showed that summer precipitation is the key factor that controls the severeness of a low-water period in fall; high summer temperatures do not per se cause stronger decreases. Preceding winters have only a minor influence on such low-water periods in general.
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