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Comparing Discrete Fracture and Continuum Models to Predict Contaminant Transport in Fractured Porous Media

Authors

  • Daniela Blessent,

    1. Département de Géologie et de Génie Géologique, Université Laval, 1065 Avenue de la Médecine, Québec, QC G1V 0A6, Canada.
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    • Currently at Department of Civil, Geological and Mining Engineering, École Polytechnique, Montreal, C.P. 6079 succ. Centre-ville, Montréal, Québec, QC Canada H3C 3A7.

  • Peter R. Jørgensen,

    1. PJ-Bluetech ApS, Klintebakken 9, DK-3520, Denmark.
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  • René Therrien

    Corresponding author
    1. Département de Géologie et de Génie Géologique, Université Laval, 1065 Avenue de la Médecine, Québec, QC G1V 0A6, Canada.
    • Corresponding author: Département de Géologie et de Génie Géologique, Université Laval, 1065 Avenue de la Médecine, Québec, QC G1V 0A6, Canada; rene.therrien@ggl.ulaval.ca

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Abstract

We used the FRAC3Dvs numerical model (Therrien and Sudicky 1996) to compare the dual-porosity (DP), equivalent porous medium (EPM), and discrete fracture matrix diffusion (DFMD) conceptual models to predict field-scale contaminant transport in a fractured clayey till aquitard. The simulations show that the DP, EPM, and DFMD models could be equally well calibrated to reproduce contaminant breakthrough in the till aquitard for a base case. In contrast, when groundwater velocity and degradation rates are modified with respect to the base case, the DP method simulated contaminant concentrations up to three orders of magnitude different from those calculated by the DFMD model. In previous simulations of well-characterized column experiments, the DFMD method reproduced observed changes in solute transport for a range of flow and transport conditions comparable to those of the field-scale simulations, while the DP and EPM models required extensive recalibration to avoid high magnitude errors in predicted mass transport. The lack of robustness with respect to variable flow and transport conditions suggests that DP models and effective porosity EPM models have limitations for predicting cause-effect relationships in environmental planning. The study underlines the importance of obtaining well-characterized experimental data for further studies and evaluation of model key process descriptions and model suitability.

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