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Publication Date
2-1-2021
Publication Title
Hydrogeology Journal
Volume Number
29
Abstract
Several different approaches have been developed to model the specific characteristics of karst aquifers, taking account of their inherent complex spatial and temporal heterogeneities. This paper sets out the development of a semidistributed modelling approach for applications in an Irish karst context using urban drainage software. The models have proven to be very useful for different studies, with examples given for the ecohydrology of ephemeral karst lakes, extreme groundwater-flood alleviation, karst network investigation, submarine groundwater discharge, and quantification of different recharge and flow components. The limitations of the approach are also highlighted, in particular not being able to simulate diffuse infiltration and flow paths explicitly across the groundwater catchment. Hence, a more distributed, finite-difference modelling approach using MODFLOW Unstructured Grid (USG) with the newly developed Connected Linear Network (CLN) process is then compared against the semidistributed approach on the same karst catchment. Whilst it has proven difficult to achieve the same levels of model performance in simulating the spring flows in the distributed model compared to the semidistributed model, the ability to interrogate the flow paths at any point on the three-dimensional aquifer is demonstrated, which can give new insights into flows (and potential contaminant transport) through such complex systems. The influence of the proximity of highly transmissive conduits on the flow dynamics through the much-lower transmissive matrix cells in which the network is embedded has been particularly investigated.
Document Type
Article
Digital Object Identifier (DOI)
https://doi.org/10.1007/s10040-020-02241-8
Language
English
Recommended Citation
Gill, L. W.; Schuler, P.; Duran, L.; Morrissey, P.; and Johnston, P. M., "An evaluation of semidistributed-pipe-network and distributed-finite-difference models to simulate karst systems" (2021). KIP Articles. 9847.
https://digitalcommons.usf.edu/kip_articles/9847
