The Gömör-Torna Karst (known also as Aggtelek Karst and Slovak Karst) is an unconfined transboundary aquifer located on the border of Hungary and Slovakia. Thanks to its complex natural heritage, which includes surface karst forms, caves and sinkholes, the region is under the protection of the Aggtelek National Park and the Slovak Karst National Park. The aquifer consists of karstified Triassic carbonates, partially covered with Quaternary clayey sediments. The karst springs provide the drinking water for the inhabitants of the area. The high sensitivity of these resources thus requires an effective and accurate protection strategy.
In the past decades, the Gömör-Torna Karst was in the focus of numerous studies, including hydrogeological investigations and local-scale groundwater vulnerability assessments. For the significant springs of the area records of long term daily observations (1964-1993) are available. This detailed hydrometeorological database provides an appropriate base for data-driven analysis of the factors influencing groundwater vulnerability.
The Weights of Evidence (WofE) technique is a well-known spatial statistical method successfully applied for mineral exploration, landslide hazard zonation, groundwater productivity potential or vulnerability assessment. WofE is a method based on the Bayesian conditional probability, which enables observations of the individual role and the combined effect of different geological, geophysical or geochemical features to assess the spatial distribution of a natural phenomenon.
Here, we attempt to apply the WofE technique for: i) the evaluation of factors influencing the spring distribution in the karst area and ii) the assessment of a reliable groundwater vulnerability map. The spatial statistical analysis can provide a reliable support in the evaluation of geological and hydrogeological factors influencing groundwater vulnerability in the karst system.
. This result is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 810980”.