EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model-based assessment of dynamic volume estimates for karst aquifers

Steffen Birk1 and Mahmoud Abirifard2
Steffen Birk and Mahmoud Abirifard
  • 1Institute of Earth Sciences, NAWI Graz Geocenter, University of Graz, Graz, Austria (
  • 2Department of Earth Sciences, Shiraz University, Shiraz, Iran (

Karst springs frequently drain large catchment areas and thus represent important water resources. Adequate management of karst water resources requires quantitative information about the drainable water volume, i.e., the dynamic volume of the karst aquifer supplying the spring. The mathematical integration of a functional relationship fitted to the observed discharge recession curve is one approach commonly employed for this purpose. Yet, this approach implicitly assumes that the observed recession behavior can be extrapolated to longer times and lower discharge values. Here, we explore the adequacy of this approach using the numerical karst groundwater flow model MODFLOW-CFP to simulate the discharge recession of hypothetical karst aquifers. While the model scenarios represent simplified hydrogeological settings, each of them includes complexities that may be encountered in real karst aquifers. By comparing the actual dynamic volume of the modelled aquifer to the volume estimate obtained from recession analysis, we identify factors potentially affecting the accuracy of the dynamic volume estimate (Abirifard et al., J. Hydrol., 2022, ). It is found, for example, that a decrease of hydraulic conductivity with depth causes underestimation of the dynamic volume, whereas groundwater abstraction within the spring catchment results in an overestimation. Real-world examples where these factors likely affect the recession behavior and thus the dynamic volume estimate are identified and described.

How to cite: Birk, S. and Abirifard, M.: Model-based assessment of dynamic volume estimates for karst aquifers, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13275,, 2023.

Supplementary materials

Supplementary material file