Recession analysis has been a valuable tool for characterizing the storage capacities and base flow dynamics of hydrological systems in many regions in the world (Beck et al., 2013; Berghuijs et al., 2016). Despite the value of analysing the recession properties of large numbers of catchments, karst research has yet omitted a broader analysis of recession properties of karst areas. This is on one hand due to the lack of large data sets that provide the necessary discharge observations. On the other hand, previous research showed that recession properties of do not reflect hydrological characteristics alone but mix together the climatic signal and the signal of the hydrological system (Jeannin and Sauter, 1998).

The aim of this MSc thesis is the exploration of climatic and hydrological influences on recession parameters obtained by recession analysis. Using a virtual modelling lab, a wide range of climatic settings will be applied to an ensemble of synthetically created karst systems with varying degree of karstification.


A wide range of realistic climatic conditions will be created either using observations from openly available climate data archives (E-OBS, Cornes et al., 2018) or a weather generator. A simple two-bucket model will be used to obtain discharge time series of virtual karst systems by varying the fractions of recharge to the fast and slow flow components and the parameters that control the hydraulic differences among fast and slow karstic groundwater discharge. To test the impact of climate, karst recession parameters will be obtained by traditional recession analysis approaches (Arciniega-Esparza et al., 2017) using discharge only in a first step. In a second step, hydrochemical data will be incorporated using discharge-concentration relationships (Li et al., 2017). Finally, the virtual results will be benchmarked against discharge and hydrochemical observations from a set of real karst systems across France (Jourde et al., 2018).

Skills and Challenges

The primary challenge of this MSc thesis is creation and the handling of very large data set. To succeed, programming and modelling skills are required (R or Matlab). Further assets are interest in recession analysis and multi-variate modelling approaches.


JProf. Andreas Hartmann, Dr. Michael Stölzle

Further notes

The data to create virtual experiments and to run the recession analysis is readily available at the Chair of Hydrological Modeling and Water resources or I is open for free download. The observations to benchmark the approach are also freely available through the recently developed global karst database (WOKAS).


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




Arciniega-Esparza, S. S. S. S., Breña-Naranjo, J. A., Pedrozo-Acuña, A., Appendini, C. M., Bre??a-Naranjo, J. A., Pedrozo-Acu??a, A., Appendini, C. M., Breña-Naranjo, J. A., Pedrozo-Acuña, A. and Appendini, C. M.: HYDRORECESSION: A Matlab toolbox for streamflow recession analysis, Comput. Geosci., 98(October), 87–92, doi:10.1016/j.cageo.2016.10.005, 2017.

Beck, H. E., van Dijk, A. I. J. M., Miralles, D. G., de Jeu, R. A. M., Sampurno Bruijnzeel, L. A., McVicar, T. R. and Schellekens, J.: Global patterns in base flow index and recession based on streamflow observations from 3394 catchments, Water Resour. Res., 49(12), 7843–7863, doi:10.1002/2013wr013918, 2013.

Berghuijs, W. R., Hartmann, A., Woods, R. A., Rupp, D. E. and Woods, R. A.: Streamflow sensitivity to water storage changes across Europe, Geophys. Res. Lett., 43(5), 1980–1987, doi:10.1002/2016GL067927, 2016.

Cornes, R. C., Schrier, G. Van Der, Jones, P. D. and Besselaar, E. J. M. Van Den: An Ensemble Version of the E-OBS Temperature and Precipitation Data Sets, , 9391–9409, 2018.

Jeannin, P.-Y. and Sauter, M.: Analysis of karst hydrodynamic behaviour using global approach: a review, edited by C. d’Hydrogeologie, Bull. d’Hydrogéologie, 16, 1998.

Jourde, H., Massei, N., Mazzilli, N., Binet, S., Batiot-Guilhe, C., Labat, D., Steinmann, M., Bailly-Comte, V., Seidel, J. L., Arfib, B., Charlier, J. B., Guinot, V., Jardani, A., Fournier, M., Aliouache, M., Babic, M., Bertrand, C., Brunet, P., Boyer, J. F., Bricquet, J. P., Camboulive, T., Carrière, S. D., Celle-Jeanton, H., Chalikakis, K., Chen, N., Cholet, C., Clauzon, V., Soglio, L. D., Danquigny, C., Défargue, C., Denimal, S., Emblanch, C., Hernandez, F., Gillon, M., Gutierrez, A., Sanchez, L. H., Hery, M., Houillon, N., Johannet, A., Jouves, J., Jozja, N., Ladouche, B., Leonardi, V., Lorette, G., Loup, C., Marchand, P., de Montety, V., Muller, R., Ollivier, C., Sivelle, V., Lastennet, R., Lecoq, N., Maréchal, J. C., Perotin, L., Perrin, J., Petre, M. A., Peyraube, N., Pistre, S., Plagnes, V., Probst, A., Probst, J. L., Simler, R., Stefani, V., Valdes-Lao, D., Viseur, S. and Wang, X.: SNO KARST: A French Network of Observatories for the Multidisciplinary Study of Critical Zone Processes in Karst Watersheds and Aquifers, Vadose Zo. J., 17, doi:10.2136/vzj2018.04.0094, 2018.

Li, L., Bao, C., Sullivan, P. L. and Brantley, S. L.: Understanding watershed hydrogeochemistry: 2. Synchronized hydrological and geochemical processes drive stream chemostatic behavior, , (November 2018), doi:10.1002/2016WR018935, 2017.

  • thesis/karst_recession.txt
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