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Open AccessArticle

Bayesian Simultaneous Estimation of Unsaturated Flow and Solute Transport Parameters from a Laboratory Infiltration Experiment

1
LHyGES, University de Strasbourg/EOST/ENGEES, CNRS, 67084 Strasbourg, France
2
LISAH, University Montpellier, INRA, IRD, Montpellier SupAgro, 34060 Montpellier, France
3
LMHE, Ecole Nationale d’Ingénieurs de Tunis, Tunis 1002, Tunisia
4
INRGREF, Laboratory of Rural Engineering, University of Carthage, Carthage 1054, Tunisia
*
Author to whom correspondence should be addressed.
Water 2019, 11(8), 1660; https://doi.org/10.3390/w11081660
Received: 28 July 2019 / Revised: 30 July 2019 / Accepted: 7 August 2019 / Published: 11 August 2019
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Abstract

Numerical modeling has become an irreplaceable tool for the investigation of water flow and solute transport in the unsaturated zone. The use of this tool for real situations is often faced with lack of knowledge of hydraulic and soil transport parameters. In this study, advanced experimental and numerical techniques are developed for an accurate estimation of the soil parameters. A laboratory unsaturated flow and solute transport experiment is conducted on a large undisturbed soil column of around 40 cm length. Bromide, used as a nonreactive contaminant, is injected at the surface of the undisturbed soil, followed by a leaching phase. The pressure measurements at different locations along the soil column as well as the outflow bromide concentration are collected during the experiment and used for the statistical calibration of flow and solute transport. The Richards equation, combined with constitutive relations for water content and permeability, is used to describe unsaturated flow. Both linear and non-equilibrium mobile–immobile transport models are investigated for the solute transport. All hydraulic and mass transport parameters are inferred using a one-step Bayesian estimation with the Markov chain Monte Carlo sampler. The results prove that the pressure and concentration measurements are able to identify almost all hydraulic and mass transport parameters. The mobile–immobile transport model better reproduces the infiltration experiment. It produces narrower uncertainty intervals for soil parameters and predictive output concentrations. View Full-Text
Keywords: infiltration laboratory experiment; Richards equation; advection-dispersion equation; mobile–immobile model; predictive uncertainty; Markov chain Monte Carlo infiltration laboratory experiment; Richards equation; advection-dispersion equation; mobile–immobile model; predictive uncertainty; Markov chain Monte Carlo
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Younes, A.; Zaouali, J.; Kanzari, S.; Lehmann, F.; Fahs, M. Bayesian Simultaneous Estimation of Unsaturated Flow and Solute Transport Parameters from a Laboratory Infiltration Experiment. Water 2019, 11, 1660.

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