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

Anis Younes (1, 2, 3) , Jabran Zaouali (1) , Sabri Kanzari (4) , Francois Lehmann (1) , Marwan Fahs (1)

1 LHyGeS - Laboratoire d'Hydrologie et de Géochimie de Strasbourg
2 UMR LISAH - Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème
3 ENIT - Ecole Nationale d'Ingénieurs de Tunis
4 INRGREF - Institut National de Recherche en Génie Rural Eaux et Forêts

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.

Mots clés: Markov chain Monte Carlo; predictive uncertainty; advection-dispersion equation; infiltration laboratory experiment; Richards equation

Mots clés: mobile-immobile model

Domaines: Milieux fluides et réactifs

Anis Younes, Jabran Zaouali, Sabri Kanzari, Francois Lehmann, Marwan Fahs. Bayesian Simultaneous Estimation of Unsaturated Flow and Solute Transport Parameters from a Laboratory Infiltration Experiment. Water, 2019, 11 (8), pp.1660. ⟨10.3390/w11081660⟩. ⟨hal-02390243⟩