ABSTRACT
Karst aquifers are important sources of fresh water on a global scale. The hydrological modelling of karst spring discharge, however, still poses a challenge. In this study we apply a transfer function noise (TFN) model in combination with a bucket-type recharge model to simulate karst spring discharge. The application of the noise model for the residual series has the advantage that it is more consistent with assumptions for optimization such as homoscedasticity and independence. In an earlier hydrological modeling study, named Karst Modeling Challenge (KMC; Jeannin et al., J Hydrol 600:126-508, 2021), several modelling approaches were compared for the Milandre Karst System in Switzerland. This serves as a benchmark and we apply the TFN model to KMC data, subsequently comparing the results to other models. Using different data-model-combinations, the most promising data-model-combination is identified in a three-step least-squares calibration. To quantify uncertainty, the Bayesian approach of Markov-chain Monte Carlo (MCMC) sampling is subsequently used with uniform priors for the previously identified best data-model combination. The MCMC maximum likelihood solution is used to simulate spring discharge for a previously unseen testing period, indicating a superior performance compared to all other models in the KMC. It is found that the model gives a physically feasible representation of the system, which is supported by field measurements. While the TFN model simulated rising limbs and flood recession especially well, medium and baseflow conditions were not represented as accurately. The TFN approach poses a well-performing data-driven alternative to other approaches that should be considered in future studies.
ABSTRACT
Inner boundary conditions describe the interaction of groundwater wells with the surrounding aquifer during pumping and are associated with well-skin damage that limits water production and water derived from wellbore storage. Pumping test evaluations of wells during immediate and early time flow require assignment of inner boundary conditions. Originally, these concepts were developed for vertical well screens, and later transferred to wellbores intersecting highly conductive structures, such as preferential flow zones in fractured and karstic systems. Conceptual models for pumping test analysis in complex bedrock geology are often simplified. Classic analytical solutions generally lump or ignore conditions that limit or enhance well productivity along the well screen at the onset of pumping. Numerical solutions can represent well drawdowns in complex geological settings, such as karst systems, more precisely than many analytical solutions by accounting for additional physical processes and avoiding assumptions and simplifications. Suitable numerical tools for flow simulations in karst are discrete pipe-continuum models that account for various physical processes such as the transient hydraulics of wellbores intersecting highly conductive structures during pumping.
