As conventional methods, spring hydro- and physico-chemographs are widely applied. With the help of these graphs, the local dynamics and heterogeneity of the aquifer can be investigated on catchment and aquifer scale. In turn, springs are the natural discharge points of flow systems, they can reflect the subsurface flow and temperature conditions, and therefore they can provide information about the groundwater flow pattern. Namely, the character of springs and their spatial distribution can be indicative for nested groundwater flow systems via the physicochemical parameters of their outflowing water, as well as for geothermal potential via their outflowing water volume and temperature. Similarly, to the groundwater flow pattern evolved in siliciclastic sedimentary basins, carbonate regions can also be characterized by regional subsurface flow field due to gravitational driving force on basin-scale.
This study intends to display the methodology of groundwater flow characterization based on springs via the case study of Hungarian hills and highlands, with special emphasis on the Transdanubian Range. It is located in the central part of Hungary and it consists of ~2-3 km thick carbonate formations and there are ~700 naturally discharging springs. Multidimensional data analysis of the springs as natural discharge points could help to understand the natural groundwater flow pattern and hydraulic role of structures. Elevation of spring orifice, water temperature, volume discharge of springs and major ion content as potential indicative parameters for groundwater flow were applied during basin-scale classification. Based on combined cluster and discriminant analysis (CCDA), groups were derived which were ranked into local, intermediate and regional flow systems.
Systematic analysis of springs can lead to a comprehensive conceptualization of groundwater flow systems and the consequent characterization regarding the geothermal potential of a carbonate area.
This study 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.