Identification of indicator parameters for the quantitative assessment of vulnerability in karst aquifers

Abstract

Prediction of contaminant transport in karst aquifers is therefore challenging and requires the knowledge of flow characteristics and transport processes in these systems. Based in this information, quantitative vulnerability concepts can be established, which are a prerequisite for management of karst water resources and conservation of their quality. The present thesis investigates indicator parameters of intrinsic and specific vulnerability in karst aquifers through the characterization of karst systems based on spring responses and integrated numerical Modelling at a catchment scale. Spring responses include discharge and chemographs and reflect the integrated response of all the flow and transport processes occurring in a system. For this purpose flow in a well investigated karst system was first numerically simulated using the Mike She software (DHI). The spatially distributed model accounts for all the physical processes taking place in the hydrological cycle, and therefore considers all the compartments of a karst system (atmosphere, unsaturated zone, and saturated zone). The physical or empirical parameters involved in the model, which play a role in the shape of the flow response and its transmission, were delineated through an extensive sensitivity analysis. This work shows that all the compartments within a karst system strongly influence the discharge; consequently they have to be accounted for in intrinsic vulnerability assessment. The significance of the physical processes and parameters in the numerical flow model were quantified using two objective functions: the Root Mean Square Error (RMSE) and the percentage error in the annual volume over the modeled period. In the second part of this work, an extensive campaign of about 30 artificial tracer experiments were evaluated for different compartments of a mature karst system. The tracer breakthrough curves (TBCs) were modeled using the Two Region Non Equilibrium Model (2RNEM) to account for irregularities and tailing in the observed TBCs. The conservative transport parameters including tracer transit times, longitudinal dispersivity as well as the portion of the mobile region (