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Artificial tracer tests constitute one of the most powerful tools to investigate solute transport in conduit-dominated karstic aquifers. One can retrieve information about the internal structure of the aquifer directly by a careful analysis of the residence time distribution (RTD). Moreover, recent studies have shown the strong dependence of solute transport in karstic aquifers on boundary conditions. Information from artificial tracer tests leads us to propose a hypothesis about the internal structure of the aquifers and the effect of the boundary conditions (mainly high or low water level). So, a multi-tracer test calibration of a model appeared to be more consistent in identifying the effects of changes to the boundary conditions and to take into consideration their effects on solute transport. In this study, we proposed to run the inverse problem based on artificial tracer tests with a numerical procedure composed of the following three main steps: (1) conduit network geometries were simulated using a pseudo-genetic algorithm; (2) the hypothesis about boundary conditions was imposed in the simulated conduit networks; and (3) flow and solute transport were simulated. Then, using a trial-and-error procedure, the simulated RTDs were compared to the observed RTD on a large range of simulations, allowing identification of the conduit geometries and boundary conditions that better honor the field data. This constitutes a new approach to better constrain inverse problems using a multi-tracer test calibration including transient flow.

Coupling SKS and SWMM to Solve the Inverse Problem Based on Artificial Tracer Tests in Karstic Aquifers