Analyzing multi-scale hydrodynamic processes in karst with a coupled conceptual modeling and signal decomposition approach

More than 25% of the world's population either lives on or obtains its water from karst aquifers, which makes the understanding of these systems essential for water resources management. However it is often difficult to observe and assess their internal dynamics precisely. In this study we investigated (1) the ability of both conceptual model approach and signal decomposition methods to extract meaningful components from karst spring hydrographs and (2) how a modelled spring discharge acquires its spectral signature through a conceptual reservoirs model. We used the conceptual modeling software KARSTMOD to model the discharge of a small karst spring in Normandy (France). We compared the model internal discharges with natural tracers of the system (conductivity, turbidity) and piezometry. The results suggested that the conceptual model was able to reproduce part of the internal hydrological behavior of the karst system, especially the exchange dynamics between conduits and the surrounding aquifer. We compared the internal flows of the model with wavelet details obtained from multiresolution analysis of the spring discharge. These internal flows appeared strongly correlated to specific consecutive sums of wavelet details. Finally we studied how the modeled discharge at the spring was acquiring its spectral characteristics across the model, using Fourier spectra analysis. Cut-off frequencies visible on the Fourier spectrum of the spring were matching the frequencies obtained with the multiresolution analysis. These results combined illustrate the ability of decomposition methods to reproduce the spectral variations of the different discharges within the model, and likely within the observed karst system.