Identifying More Realistic Model Structures by Electrical Conductivity Observations of the Karst Spring

Electrical conductivity (EC) of karst spring discharge has always been a fundamental variable to characterize karst systems. However, to incorporate EC into the lumped hydrologic modeling is challenging but has a huge potential since EC observations are widely collected. In this study, we present a new framework to integrate EC into lumped karst hydrological models for model structure identification and parameter uncertainty reduction. Our framework is tested in a small, well-instrumented karst catchment near Guilin city (China) where EC dynamics are mostly controlled by the dissolution of carbonate rock and dilution by event water. Four karst models with different structures were equipped to consider the linear growth of EC with the carbonate rock dissolution and its mixing within the karst system. Applying a parameter estimation framework that accounts for uncertainty in discharge and EC simulations, we find that all hydrologic models obtain similar performances concerning spring discharge. However, their performances in simulating spring EC strongly differ permitting us to identify the most realistic model out of the four model structures. Our analysis further shows that including EC into parameter estimation reduces parameter uncertainty concerning concentrated flow in the conduits and helps to estimate immobile water storage in the system. Consequently, our new framework to include EC in karst models provides new directions for the more realistic simulation that can easily be transferred to other karst systems where EC dynamics are controlled by rock dissolution and dilution by event water.