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Abstract: The solution to the 2-D time-dependent unsaturated flow equation is numerically approximated by a second-order accurate cell-centered finite-volume discretization on unstructured grids. The approximation method is based on a vertex-centered Least Squares linear reconstruction of the solution gradients at mesh edges. A Taylor series development in time of the water content dependent variable in a finite-difference framework guarantees that the proposed finite volume method is mass conservative. A Picard iterative scheme solves at each time step the resulting non-linear algebraic problem. The performance of the method is assessed on five different test cases and implementing four distinct soil constitutive relationships. The first test case deals with a column infiltration problem. It shows the capability of providing a mass-conservative behavior. The second test case verifies the numerical approximation by comparison with an analytical mixed saturated–unsaturated solution. In this case, the water drains from a fully saturated portion of a 1-D column. The third and fourth test cases illustrate the performance of the approximation scheme on sharp soil heterogeneities on 1-D and 2-D multi-layered infiltration problems. The 2-D case shows the passage of an abrupt infiltration front across a curved interface between two layers. Finally, the fifth test case compares the numerical results with an analytical solution that is developed for a 2-D heterogeneous soil with a source term representing plant roots. This last test case illustrates the formal second-order accuracy of the method in the numerical approximation of the pressure head. [Copyright &y& Elsevier]

Geophysical surveys can provide useful, albeit indirect, information on vadose zone processes. However, the ability to provide a quantitative description of the subsurface hydrological phenomena requires to fully integrate geophysical data into hydrological modeling. Here, we describe a controlled infiltration experiment that was monitored using both electrical resistivity tomography (ERT) and ground-penetrating radar (GPR). The experimental site has a simple, well-characterized subsoil structure: the vadose zone is composed of aeolic sand with largely homogeneous and isotropic properties. In order to estimate the unknown soil hydraulic conductivity, we apply a data assimilation technique based on a sequential importance resampling (SIR) approach. The SIR approach allows a simple assimilation of either or both geophysical datasets taking into account the associated measurement uncertainties. We demonstrate that, compared to a simpler, uncoupled hydro-geophysical approach, the coupled data assimilation process provides a more reliable parameter estimation and better reproduces the evolution of the infiltrating water plume. The coupled procedure is indeed much superior to the uncoupled approach that suffers from the artifacts of the geophysical inversion step and produces severe mass balance errors. The combined assimilation of GPR and ERT data is then investigated, highlighting strengths and weaknesses of the two datasets. In the case at hand GPR energy propagates in form of a guided wave that, over time, shows different energy distribution between propagation modes as a consequence of the evolving thickness of the wet layer. We found that the GPR inversion procedure may produce estimates on the depth of the infiltrating front that are not as informative as the ERT dataset. [ABSTRACT FROM AUTHOR]