Détermination des propriétés hydrogéologiques de l'aquifère de lachenaie par géoradar et polarisation spontanée

La polarisation spontanée -- Étude des mécanismes de polarisation spontanée (PS) -- Le potentiel d'électro-filtration -- Le couplage de flux -- Description des applications de PS -- Technique de modélisation -- Essais en laboratoire -- Mesures effectuées sur le site de Lachenaie -- Préparation du levé -- Le radar géologique -- Équations fondamentales -- Estimation of hydraulic conductivity of an unconfined aquifer using cokriging of GPR and hydrogeological data

Ensemble Kalman Filter Assimilation of ERT Data for Numerical Modeling of Seawater Intrusion in a Laboratory Experiment

Seawater intrusion in coastal aquifers is a worldwide problem exacerbated by aquifer overexploitation and climate changes. To limit the deterioration of water quality caused by saline intrusion, research studies are needed to identify and assess the performance of possible countermeasures, e.g., underground barriers. Within this context, numerical models are fundamental to fully understand the process and for evaluating the effectiveness of the proposed solutions to contain the saltwater wedge; on the other hand, they are typically affected by uncertainty on hydrogeological parameters, as well as initial and boundary conditions. Data assimilation methods such as the ensemble Kalman filter (EnKF) represent promising tools that can reduce such uncertainties. Here, we present an application of the EnKF to the numerical modeling of a laboratory experiment where seawater intrusion was reproduced in a specifically designed sandbox and continuously monitored with electrical resistivity tomography (ERT). Combining EnKF and the SUTRA model for the simulation of density-dependent flow and transport in porous media, we assimilated the collected ERT data by means of joint and sequential assimilation approaches. In the joint approach, raw ERT data (electrical resistances) are assimilated to update both salt concentration and soil parameters, without the need for an electrical inversion. In the sequential approach, we assimilated electrical conductivities computed from a previously performed electrical inversion. Within both approaches, we suggest dual-step update strategies to minimize the effects of spurious correlations in parameter estimation. The results show that, in both cases, ERT data assimilation can reduce the uncertainty not only on the system state in terms of salt concentration, but also on the most relevant soil parameters, i.e., saturated hydraulic conductivity and longitudinal dispersivity. However, the sequential approach is more prone to filter inbreeding due to the large number of observations assimilated compared to the ensemble size

Regional-scale integration of multiresolution hydrological and geophysical data using a two-step Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale for the purpose of improving predictions of groundwater flow and solute transport. However, extending corresponding approaches to the regional scale still represents one of the major challenges in the domain of hydrogeophysics. To address this problem, we have developed a regional-scale data integration methodology based on a two-step Bayesian sequential simulation approach. Our objective is to generate high-resolution stochastic realizations of the regional-scale hydraulic conductivity field in the common case where there exist spatially exhaustive but poorly resolved measurements of a related geophysical parameter, as well as highly resolved but spatially sparse collocated measurements of this geophysical parameter and the hydraulic conductivity. To integrate this multi-scale, multi-parameter database, we first link the low- and high-resolution geophysical data via a stochastic downscaling procedure. This is followed by relating the downscaled geophysical data to the high-resolution hydraulic conductivity distribution. After outlining the general methodology of the approach, we demonstrate its application to a realistic synthetic example where we consider as data high-resolution measurements of the hydraulic and electrical conductivities at a small number of borehole locations, as well as spatially exhaustive, low-resolution estimates of the electrical conductivity obtained from surface-based electrical resistivity tomography. The different stochastic realizations of the hydraulic conductivity field obtained using our procedure are validated by comparing their solute transport behaviour with that of the underlying "true” hydraulic conductivity field. We find that, even in the presence of strong subsurface heterogeneity, our proposed procedure allows for the generation of faithful representations of the regional-scale hydraulic conductivity structure and reliable predictions of solute transport over long, regional-scale distance

New methods to spatially extend thermal response test assessments

Thermal response tests (TRTs), used to evaluate the subsurface thermal conductivity when designing ground source heat pump systems, are spatially limited to the vicinity of the borehole where a test is carried out. The subsurface is heterogeneous and the thermal conductivity assessment provided by a TRT is likely to vary beyond the tested borehole. New methods have, therefore, been developed to extend subsurface assessments at the building site and the urban district scales. The first method relies on temperature profiles measured at equilibrium in ground heat exchangers that are reproduced with inverse numerical simulations to infer the terrestrial heat flow and the subsurface thermal conductivity beyond a first TRT. Inversion of temperature profiles was verified at a pilot site in the Appalachians where TRTs had been performed and showed a thermal conductivity estimate within less than 10 % for both approaches. The second method is based on geostatistical simulations to map the distribution of the subsurface thermal conductivity in areas where several ground source heat pump installations are anticipated. A first mapping exercise was achieved to the north of Montreal in the St. Lawrence Lowlands with fours TRTs and ten laboratory measurements interpolated with sequential Gaussian simulations

Development of a thermal conductivity map of Stockholm

New methods have been suggested to spatially extend in situ thermal response test (TRT) assessments based on geostatistical analysis. These methods can be used to determine a stochastic distribution of the subsurface thermal conductivity beyond the test borehole on larger scales by interpolating the data with geostatistics, including sequential Gaussian simulations (SGS) used in the present study. This paper presents a simulated thermal conductivity map for Greater Stockholm in Sweden, based on the SGS method with input data from in situ measurements (TRT and DTRT). The geology of Stockholm is used as a background raster in the simulations, based on bedrock maps from the Geological Survey of Sweden (SGU). The resulting maps are compared with a point map of punctual ground thermal conductivity of Greater Stockholm earlier derived by SGU, compiled from laboratory data that were obtained by thermal conductivity scanning and modal analysis of surface rock specimens of the area

A framework for parameter estimation using sharp-interface seawater intrusion models

Funding : This work was supported by Quebec’s Ministère de l'Environnement et de la Lutte contre les changements climatiques (MELCC) [project « Acquisition de connaissances sur les eaux souterraines dans la région des Îles-de-la-Madeleine » (Groundwater characterization project in the Magdalen Islands region)]; and the Fonds québécois de la recherche sur la nature et les technologies (FRQNT) [International internship program accessed through CentrEau, the Quebec Water Research Center]. The authors would like to thank the Municipality of Les Îles-de-la-Madeleine for providing pumping datasets and information on current and historical groundwater management. They would also like to thank the team at Université Laval working on the Magdalen Islands project, for their help acquiring datasets and for field logistics, John Molson, for proofreading, and finally the two anonymous reviewers for their valuable comments. The authors would also like to thank Vincent Post for discussions on deep open boreholes, and Francesca Lotti and John Doherty for discussions on seawater intrusion modeling and data assimilation. J-C Comte and O Banton acknowledge the financial support from the Fonds d'Action Québécois pour le Développement Durable for the ERT data collection, undertaken as part of the Madelin'Eau consortium (Ageos-Enviro'Puits-Hydriad), and further thank the Municipality of Les Îles-de-la-Madeleine for fieldwork logistical and technical support.Peer reviewedproo