EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Can the electrical conductivity of karst spring discharge improve the identification of model structures and reduce simulation uncertainty?

Yong Chang1, Ling Liu2, Guanghui Jiang3,4, Andreas Hartmann5,6, and Jichun Wu7
Yong Chang et al.
  • 1School of Earth Science and Engineering, Hohai University, Nanjing, China (
  • 2Geological Survey of Jiangsu Province, Nanjing, China(
  • 3Karst Dynamics Laboratory, Institute of Karst Geology, Guilin, China(
  • 4International Karst Research Center auspices of UNESCO, Guilin, China
  • 5Chair of Hydrological Modeling and Water Resources, Freiburg University, Freiburg, Germany(
  • 6Department of Civil Engineering, University of Bristol, Bristol, United Kingdom
  • 7School of Earth Sciences and Engineering, Nanjing University, Nanjing, China(

Lumped karst hydrological models often suffer from the over-simplified structures. In recent days, hydrochemical has been used as an auxiliary information to define realistic karst model structures. For karst aquifers, the hydrochemical dynamics of karst springs contain important information about the internal behavior of the karst aquifer that can be conducive to model identification and calibration. In this presentation, electrical conductivity (EC), as a substitution for Ca2+ concentration of the spring discharge, is evaluated for its potential for model structure identification and reduction of simulation uncertainty. A new framework to integrate EC in karst modeling is developed at a small, well-instrumented karst catchment near Guilin City, China. A set of different hydrologic models were enabled to consider the linear dissolution process of Ca2+ and its transport to investigate the models’ abilities to reproduce the behavior of spring discharge and EC. We found that most hydrologic models obtain similar performances concerning spring discharge, however, their performances in simulating spring EC show obvious differences. The combination of observed spring discharge and EC could identify a more realistic model structure that was in accordance with the observed perception of this karst aquifer’s functioning. Using the identified “most realistic” model, we use sensitivity analysis to show that spring EC only improves the identifiability of one hydrologic parameter mostly due to too complex EC dynamics during recharge events and therefore has limited potential to reduce discharge simulation uncertainty. Consequently, our new framework to include EC in karst models opens new doors for more realistic simulation but an explicit treatment of uncertainties remains necessary due to EC’s limited potential to reduce simulation uncertainty. The next step of our work is to integrate appropriate nonlinear dissolution process of carbonate rock in the model to further improve the simulation of spring EC (Ca2+).

How to cite: Chang, Y., Liu, L., Jiang, G., Hartmann, A., and Wu, J.: Can the electrical conductivity of karst spring discharge improve the identification of model structures and reduce simulation uncertainty?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3781,, 2020

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