TY - JOUR
A1 - Banusch, S.
A1 - Somogyvári, M.
A1 - Sauter, M.
A1 - Renard, P.
A1 - Engelhardt, I.
T1 - Stochastic Modeling Approach to Identify Uncertainties of Karst Conduit Networks in Carbonate Aquifers
Y1 - 2022-08-09
VL - 58
IS - 8
JF - Water Resources Research
DO - 10.1029/2021WR031710
PB -
N2 - The characterization of the karst conduit network is an essential task to understand the complex flow system within karst aquifers. However, this task is challenging and often associated with uncertainty. Equivalent porous media approaches for modeling flow in karst aquifers fall short of capturing the hydraulic effect of individual karst features, while process‐oriented karst evolution models imply major computational efforts. In this study, we apply the Stochastic Karst Simulator (SKS) developed by Borghi et al. (2012) to generate karst conduit networks at a regional scale of a highly karstified carbonate aquifer located in the Eastern Mediterranean region and extensively used for water supply. The SKS generates conduit network geometries reasonably quick, using a mathematical proxy that mimics conduit evolution. The conduit simulation is based on a conceptual model of the genesis of the aquifer, consisting of different karstification phases. The stochastic approach of the algorithm enables us to generate an ensemble of conduit network realizations and to represent the uncertainties of these simulations in a Karst Probability Map. With only soft input information to constrain conduit evolution, multiple equivalent realizations yield similar resulting network geometries, indicating a robust approach. The presented methodology is numerically efficient, and its input can be easily adjusted. Subsequently, the resulting stochastic spatial distribution of conductivities can be employed for the parametrization of regional karst groundwater models.
N2 - Key Points: We statistically generate multiple sets of karst conduit network geometries using input data based on soft information. The resulting Karst Probability Map accounts for uncertainty in the spatial distribution of the karst conduit network. Our approach can assist in the integration of soft information into the parametrization of karst groundwater models.
UR - http://resolver.sub.uni-goettingen.de/purl?gldocs-11858/10336
ER -