Constraining complex aquifer geometry with geophysics (2-D ERT and MRS measurements) for stochastic modelling of groundwater flow |
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| Institution: | 1. Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai 600036, India;2. Department of Civil Engineering, Indian Institute of Science, Bangalore 560012, India;3. Indo-French Cell for Water Science, Indian Institute of Science, Bangalore 560012, India;4. Laboratoire d’étude des Transferts en Hydrologie et Environnement (LTHE), UMR 012 IRD, UJF, CNRS, INPG, Université de Grenoble, BP 53, 38041, Grenoble, France;5. IRD, GET-OMP, UMR 5563 CNRS/Univ. P. Sabatier/IRD, 14 avenue E. Belin, F-31400 Toulouse, France;6. INRA, Agrocampus Ouest, UMR 1069 SAS, 35000 Rennes, France;1. Sonny Astani Dept. of Civil and Environmental Engineering, University of Southern California, Los Angeles, USA;2. Dip. di Ingegneria, Universita di Roma Tre, Rome, Italy;3. Dept. of Mechanical and Aerospace Engineering, University of California, La Jolla, San Diego, USA;4. Dept. of Civil, Environmental and Mechanical Engineering, University of Trento, Trento, Italy;1. Center for Archaeological Sciences, University of Georgia, Athens, GA, USA;2. Department of Anthropology, University of Georgia, Athens, GA, USA;3. South Carolina Institute of Archaeology and Anthropology, University of South Carolina, Columbia, SC, USA;4. Laboratory of Archaeology, University of Georgia, Athens, GA, USA |
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| Abstract: | Stochastic modelling is a useful way of simulating complex hard-rock aquifers as hydrological properties (permeability, porosity etc.) can be described using random variables with known statistics. However, very few studies have assessed the influence of topological uncertainty (i.e. the variability of thickness of conductive zones in the aquifer), probably because it is not easy to retrieve accurate statistics of the aquifer geometry, especially in hard rock context. In this paper, we assessed the potential of using geophysical surveys to describe the geometry of a hard rock-aquifer in a stochastic modelling framework.The study site was a small experimental watershed in South India, where the aquifer consisted of a clayey to loamy–sandy zone (regolith) underlain by a conductive fissured rock layer (protolith) and the unweathered gneiss (bedrock) at the bottom. The spatial variability of the thickness of the regolith and fissured layers was estimated by electrical resistivity tomography (ERT) profiles, which were performed along a few cross sections in the watershed. For stochastic analysis using Monte Carlo simulation, the generated random layer thickness was made conditional to the available data from the geophysics. In order to simulate steady state flow in the irregular domain with variable geometry, we used an isoparametric finite element method to discretize the flow equation over an unstructured grid with irregular hexahedral elements.The results indicated that the spatial variability of the layer thickness had a significant effect on reducing the simulated effective steady seepage flux and that using the conditional simulations reduced the uncertainty of the simulated seepage flux.As a conclusion, combining information on the aquifer geometry obtained from geophysical surveys with stochastic modelling is a promising methodology to improve the simulation of groundwater flow in complex hard-rock aquifers. |
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