Evaluation of karst vulnerability methods by tracer experiments and modeling (Mirjam Scheller)


GIS-based approaches assess the resource vulnerability of karst systems by overlapping different climatic, pedological and geological features of karst systems. They provide maps the indicate strong and less vulnerable areas of the contributing areas of karst springs. This property made them a valuable tool for water management in karst regions across the globe (Iván and Mádl-Szőnyi, 2017). However, despite strong differences among the different vulnerability mapping approaches, there has not been a systematic evaluation of the different approaches mostly due to the lack of observations on connections between the surface and subsurface of karst areas.

The aim of this MSc thesis is the development of a model-based approach for the independent evaluation of karst vulnerability approaches.


The MSc thesis will be conducted at a strongly karstified test site (the Unica karst catchment, Slovenia), at which vulnerability mapping has already been performed. Guided by the supervisor, the student will set up a semi-distributed karst model (VarKarst, Hartmann et al., 2013). The model’s semi-distributed structure will be linked with a spatial map of the catchment using a previously developed approach for the spatiotemporal assessment of groundwater recharge (Hartmann et al., 2014). The model will be enabled to simulate transit time distributions by virtual tracer experiments (Hartmann et al., 2016; Weiler and McDonnell, 2004) and it will be benchmarked by previously conducted artificial tracer experiments (Mudarra et al., 2019). After successful evaluation, the model will be able to simulate the transit times of different source areas to the system outlet at different hydrological conditions and a spatiotemporal comparison of the GIS-based vulnerability method can be performed.

Skills and Challenges

The primary challenge of this MSc thesis is the setup of the model using different types of data for calibration and its spatial attribution. To succeed, programming and modelling skills are required (Matlab to apply the model, R can be used for analysis and visualization). Further assets are interest in karst system characterization and tracer hydrology.


JProf. Andreas Hartmann, Dr Yan Liu and Dr Natasha Ravbar (Slovenian Karst Research Institute, Postojna)

Further notes

All necessary data is available and all necessary approaches have been already developed and tested but never in this new proposed combination.

A visit at the test site is strongly encouraged and will be fully funded within an ongoing DAAD project (


Andreas Hartmann Tel. +49 (0)761 / 203-3520




Hartmann, A., Barberá, J. A., Lange, J., Andreo, B. and Weiler, M.: Progress in the hydrologic simulation of time variant recharge areas of karst systems – Exemplified at a karst spring in Southern Spain, Adv. Water Resour., 54, 149–160, doi:10.1016/j.advwatres.2013.01.010, 2013.

Hartmann, A., Mudarra, M., Andreo, B., Marín, A., Wagener, T. and Lange, J.: Modeling spatiotemporal impacts of hydroclimatic extremes on groundwater recharge at a Mediterranean karst aquifer, Water Resour. Res., 50(8), 6507–6521, doi:10.1002/2014WR015685, 2014.

Hartmann, A., Kobler, J., Kralik, M., Dirnböck, T., Humer, F. and Weiler, M.: Model-aided quantification of dissolved carbon and nitrogen release after windthrow disturbance in an Austrian karst system, Biogeosciences, 13(1), 159–174, doi:10.5194/bg-13-159-2016, 2016.

Iván, V. and Mádl-Szőnyi, J.: State of the art of karst vulnerability assessment: overview, evaluation and outlook, Environ. Earth Sci., 76(3), 112, doi:10.1007/s12665-017-6422-2, 2017.

Mudarra, M., Hartmann, A. and Andreo, B.: Combining Experimental Methods and Modeling to Quantify the Complex Recharge Behavior of Karst Aquifers, Water Resour. Res., 0(ja), doi:10.1029/2017WR021819, 2019.

Weiler, M. and McDonnell, J. J.: Virtual experiments: a new approach for improving process conceptualization in hillslope hydrology, J. Hydrol., 285(1–4), 3–8, 2004.

thesis/karst_vulnerability.txt · Zuletzt geändert: 2020/02/18 14:03 von a.hartmann