|Ph.D Student||Bamberger Elazar|
|Subject||Combined Use of ERT and Vadose Zone Flow Modeling for|
Improved Estimation of Soil Water Content
|Department||Department of Civil and Environmental Engineering||Supervisors||Professor Raphael Linker|
|Professor Alex Furman|
|Full Thesis text|
Electrical resistivity tomography (ERT) is a geophysical technique for active mapping of subsurface electrical resistivity using surface measurements. Hydrologists adapted this technique to the problem of measuring the spatial distribution of the subsurface water content, using the interdependence between the electrical resistivity and the water content. The subsurface tomography is obtained from the surface measurements mathematically as an underdetermined inverse problem. In order to reduce the ill-posed nature of this problem, a priori information is required, which is introduced in the form of constraints. Commonly-used a priori information is derived from a reference moisture profile and constraints the solution to be close to the reference. As a result, the obtained solution depends strongly on this reference profile and local inaccuracies in the reference profile may lead to large inaccuracies in the solution, especially in zones of sharp spatial changes in the electrical properties, such as at wetting fronts.
This research suggests a novel methodology that incorporates a priori information, obtained from a hydrological water flow simulation through constraints and a modified objective function. This allows decoupling the solution from the reference profile in regions of uncertainty such as exists around wetting fronts. The new approach is demonstrated through a synthetic one-directional water flow example. The results indicate that partial relaxation of the commonly-used regularizations, and embedding physically-based a priori information, both based on the water flow simulations, improve the accuracy of the inversion.
The suggested procedure makes the inversion results dependent on the values of the soil hydraulic parameters used for the simulation. In order to reduce uncertainty in these parameters, a “geophysical-hydrological recursion” method was developed based on a sequence of ERT-measured water content profiles. These profiles are analyzed by hydrologic inversion so that new estimates of the soil hydraulic parameters are obtained. These post-inversion values are compared with the previously assumed values, and the parameters are updated until the procedure has converged. This recursive scheme was tested using five initial soil types, and the values of the dominant parameters converged towards the true values.
The main conclusion of this study is that the proposed geophysical-hydrological recursion scheme improves the accuracy of both the water content profiles estimated from ERT, and the values of the soil hydraulic parameters.