Improving understanding of groundwater flow in an  alpine karst system by reconstructing its geologic  history using conduit network model ensembles

Fandel, Chloé; Ferré, Ty; Miville, François; Renard, Philippe; Goldscheider, Nico

doi:https://doi.org/10.5194/hess-27-4205-2023

Articles | Volume 27, issue 22

https://doi.org/10.5194/hess-27-4205-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-27-4205-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 27, issue 22

Research article

|

28 Nov 2023

Research article |

| 28 Nov 2023

Improving understanding of groundwater flow in an alpine karst system by reconstructing its geologic history using conduit network model ensembles

Chloé Fandel, Ty Ferré, François Miville, Philippe Renard, and Nico Goldscheider

Data sets

Fandel_et_al_2023_HESS.ipynb C. Fandel https://github.com/randlab/pyKasso/blob/c295727053c51d9f4ba735a171a5e94df4e1f48a/notebooks/Fandel_et_al_2023_HESS.ipynb

Improving understanding of groundwater flow in an alpine karst system by reconstructing its geologic history using conduit network model ensembles. In HESS C. Fandel, T. P. A. Ferré, F. Miville, P. Renard, and N. Goldscheider https://doi.org/10.5281/zenodo.10182888

Model code and software

pyKasso - stochastic karst network simulation C. Fandel https://github.com/randlab/pyKasso

Short summary

From the surface, it is hard to tell where underground cave systems are located. We developed a computer model to create maps of the probable cave network in an area, based on the geologic setting. We then applied our approach in reverse: in a region where an old cave network was mapped, we used modeling to test what the geologic setting might have been like when the caves formed. This is useful because understanding past cave formation can help us predict where unmapped caves are located today.