Preprints
https://doi.org/10.5194/hess-2022-280
https://doi.org/10.5194/hess-2022-280
30 Aug 2022
 | 30 Aug 2022
Status: a revised version of this preprint was accepted for the journal HESS.

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

Abstract. Reconstructing the geologic history of a karst area can advance understanding of the system’s present-day hydrogeologic functioning, and help predict the location of unexplored conduits. This study tests competing hypotheses describing past conditions controlling cave formation in an alpine karst catchment, by comparing an ensemble of modelled networks to the observed network map. The catchment, the Gottesacker karst system (Germany/Austria), is drained by three major springs and a paleo-spring, and includes the partially explored Hölloch cave, which consists of an active section whose formation is well-understood, and an inactive section whose formation is the subject of debate. Two hypotheses for the formation of the inactive section are: 1) glaciation obscured the three present-day springs, leaving only the paleo-spring, or 2) the lowest of the three major springs (Sägebach) is comparatively young, so its subcatchment previously drained to the paleo-spring. These hypotheses were tested using the pyKasso Python library (built on anisotropic fast marching methods) to generate two ensembles of networks, one representing each scenario. Each ensemble was then compared to the known cave map. The simulated networks generated under Hypothesis 2 match the observed cave map more closely than those generated under Hypothesis 1. This supports the conclusion that the Sägebach spring is young, and suggests that the cave likely continues southwards. Finally, this study extends the applicability of model ensemble methods from situations where the geologic setting is known but the network is unknown, to situations where the network is known but the geologic evolution is not.

Chloé Fandel et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2022-280', Anonymous Referee #1, 04 Oct 2022
    • AC1: 'Reply on RC1', Nico Goldscheider, 22 Nov 2022
  • RC2: 'Comment on hess-2022-280', Anonymous Referee #2, 17 Oct 2022
    • AC2: 'Reply on RC2', Nico Goldscheider, 22 Nov 2022
  • AC3: 'Comment on hess-2022-280 - Comment for the handling editor', Nico Goldscheider, 22 Nov 2022

Chloé Fandel et al.

Video supplement

Popular science film about out research in this test site (in German, no direct relation to this paper) Austrian TV, with Nico Goldscheider https://www.pm-wissen.com/umwelt/v/aa-24mv4em992112/

Chloé Fandel et al.

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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.