Groundwater Modelling in Karst Areas

Zanini, A.; Feo, Alessandra; Petrella, Emma; Celico, Fulvio

doi:10.3390/w13060854

Cited by 4 publications

(1 citation statement)

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“…To adequately represent these flow dynamics, it is vital to account for the spatial distribution of the conduits. However, this task is often associated with challenges and uncertainties due to the large scale and complexity of karst aquifer systems (Bakalowicz, 2005).Numerical groundwater models are essential tools for addressing groundwater-related problems, for example, water resources assessment, and have been widely applied to study karst aquifers (Anderson et al, 2015;Parise et al, 2018;Zanini et al, 2021). Global model approaches, that link recharge estimations to spring discharge time series, provide information on the hydraulic behavior of the entire karst system, but do not provide detailed information on the hydraulic parameter field and therefore lack predictive power for climatic and geo-hydraulic interactions (Eisenlohr et al, 1997;Kovács & Sauter, 2007).…”

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confidence: 99%

Stochastic Modeling Approach to Identify Uncertainties of Karst Conduit Networks in Carbonate Aquifers

Banusch

Somogyvári

Sauter

et al. 2022

Water Resources Research

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Karst aquifers exist in all climate zones and constitute crucial water resources. Analyses by Goldscheider et al. (2020) showed that approximately 15% of the global ice-free land surface consists of carbonate rock, and Stevanović (2019) estimated that around 9% of the world population consumes water from karst resources. Karst aquifers are characterized by highly permeable conduits embedded in a less permeable porous rock matrix. Most of the groundwater flow in karst aquifers is therefore controlled by the conduits, which form complex, hierarchically organized networks (Ford & Williams, 2007). Thus, the conduit network dominates the hydraulic properties of karst aquifers. To adequately represent these flow dynamics, it is vital to account for the spatial distribution of the conduits. However, this task is often associated with challenges and uncertainties due to the large scale and complexity of karst aquifer systems (Bakalowicz, 2005).Numerical groundwater models are essential tools for addressing groundwater-related problems, for example, water resources assessment, and have been widely applied to study karst aquifers (Anderson et al., 2015;Parise et al., 2018;Zanini et al., 2021). Global model approaches, that link recharge estimations to spring discharge time series, provide information on the hydraulic behavior of the entire karst system, but do not provide detailed information on the hydraulic parameter field and therefore lack predictive power for climatic and geo-hydraulic interactions (Eisenlohr et al., 1997;Kovács & Sauter, 2007). Advanced model approaches for conduit networks are based on the speleogenetic evolution of karst aquifers (Kaufmann et al., 2019;Liedl et al., 2003). These models solve complex coupled process equations of chemical carbonate dissolution and groundwater flow with major computational effort (Bauer et al., 2003). Incorporating stochastic approaches into the modeling process provides the opportunity to evaluate uncertainties related to the resulting spatial distribution and geometry of a conduit network. A stochastic model approach developed by Jaquet et al. (2004) focuses on integrating conservative and reactive transport processes that control the conduit evolution such as advection, dispersion, and dissolution, but does not account for actual field observations of the karst system investigated. Further approaches by Frantz et al. (2021) and Pardo-Igúzquiza et al. (2012) simulate the conduit's geometry stochastically, based on field data of the dimensions of known conduit segments. However, these data are normally laborious to obtain,

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confidence: 99%