Improved characterization of river-aquifer interactions through data assimilation with the Ensemble Kalman Filter

Exchange processes between rivers and groundwater are an important driver for the hydrological,chemical and ecological environment around streams and the cycling of waterat the catchment scale. Management decisions for such systems are very often derivedon the basis of model predictions and it is therefore essential to properly estimate therelevant model parameters that govern the interaction between river and aquifer. Variouseld studies indicate that hydraulic parameters in and around streams are associatedwith a considerable uncertainty regarding their temporal and spatial distribution. Theseuncertainties have to be regarded in the estimation of hydraulic parameters and dierentstochastic inversion methods are available for that task. Among these methods, theEnsemble Kalman Filter (EnKF) has been proven to work well for the characterizationof subsurface parameters where its advantage over other stochastic inversion techniquesis the calculation of a full posterior probability density function without linearizationaround an optimum, its computational eciency and its ability to be used for real-timepredictions.In this work, EnKF was applied to a 3D groundwater model of a well eld within theLimmat aquifer in Zurich (Switzerland) which is strongly inuenced by river-aquifer interactions.The specic aim was to investigate dierent aspects of the spatio-temporalcharacterization of river bed properties with EnKF and to explore the worth of dierentconditioning data for this site. In a rst study, the model was used in syntheticexperiments where reference runs with temporally varying river bed hydraulic conductivitieswere generated. Then it was tested, to what extend state-parameter updateswith EnKF are able to detect these changes in river bed properties based on a limitedset of piezometric head measurements from the reference simulations. In a second study,it was investigated how the spatial representation of heterogeneity inuences the updatingbehavior of EnKF. In this case, synthetic references with spatially heterogeneouselds of river bed permeabilities were generated and piezometric head data from thesereferences were used to update four dierent parameter ensembles that varied in thespatial representation of heterogeneity (i.e., fully heterogeneous versus zonated leakageparameters). ..