A model ensemble generator to explore structural uncertainty in karst systems with unmapped conduits
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PAPER
A model ensemble generator to explore structural uncertainty in karst systems with unmapped conduits Chloé Fandel 1
&
Ty Ferré 1
&
Zhao Chen 2 & Philippe Renard 3
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Nico Goldscheider 4
Received: 28 April 2020 / Accepted: 10 August 2020 # The Author(s) 2020
Abstract Karst aquifers are characterized by high-conductivity conduits embedded in a low-conductivity fractured matrix, resulting in extreme heterogeneity and variable groundwater flow behavior. The conduit network controls groundwater flow, but is often unmapped, making it difficult to apply numerical models to predict system behavior. This paper presents a multi-model ensemble method to represent structural and conceptual uncertainty inherent in simulation of systems with limited spatial information, and to guide data collection. The study tests the new method by applying it to a well-mapped, geologically complex long-term study site: the Gottesacker alpine karst system (Austria/Germany). The ensemble generation process, linking existing tools, consists of three steps: creating 3D geologic models using GemPy (a Python package), generating multiple conduit networks constrained by the geology using the Stochastic Karst Simulator (a MATLAB script), and, finally, running multiple flow simulations through each network using the Storm Water Management Model (C-based software) to reject nonbehavioral models based on the fit of the simulated spring discharge to the observed discharge. This approach captures a diversity of plausible system configurations and behaviors using minimal initial data. The ensemble can then be used to explore the importance of hydraulic flow parameters, and to guide additional data collection. For the ensemble generated in this study, the network structure was more determinant of flow behavior than the hydraulic parameters, but multiple different structures yielded similar fits to the observed flow behavior. This suggests that while modeling multiple network structures is important, additional types of data are needed to discriminate between networks. Keywords Multi-model ensemble . Structural uncertainty . Alpine hydrogeology . Karst . Groundwater flow
Introduction Approximately 16.5% of the global population lives on karst (Goldscheider et al. 2020). Karst systems form in carbonate
rock when water containing CO2 gradually dissolves a network of conduits through a fractured rock matrix. Conduits are major pathways for groundwater flow in karst aquifers (Worthington et al. 2012), and conduit flow is often rapid
Published in the special issue “Five decades of advances in karst hydrogeology”. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10040-020-02227-6) contains supplementary material, which is available to authorized users. * Nico Goldscheider [email protected]
1
Department of Hydrology & Atmospheric Sciences, University of Arizona, 1133 E. James E. Rogers Way, Rm. 122, Tucson, AZ 85721, USA
2
Environmental Resources Management, Siemensstr. 9, 63263 Neu-Isenburg,
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