Coupled hydrogeophysical inversion for soil hydraulic property estimation from time-lapse geophysical data

Good knowledge of the hydraulic properties of the vadose zone is important for understanding water flow and solute transport processes therein. This can help to promote sustainable use and mitigate anthropogenic threats to soil and water resources. The use of time-lapse geophysical data to constrain our understanding of the flow and transport properties of the vadose zone is now well recognised. Conventional use of geophysical data to estimate the hydraulic properties of the vadose zone is based on an uncoupled inversion approach including an ill-posed tomograhic inversion step which can lead to error propagation to the estimated hydraulic properties. One way of improving the accuracy of estimating soil hydraulic properties is to use a so-called coupled hydrogeophysical inversion approach. In this inversion approach, the tomograhic inversion step is avoided as geophysical measurements are directly used in the hydrological inverse problem by coupling a forward model of the geophysical measurements with a hydrological model describing the hydrologic processes under investigation. Although the potential benefits of the coupled inversion approach have been illustrated with synthetic data, there are very few applications of the approach to actual field or laboratory data. Moreover, most studies using this approach focused on electrical resistivity tomography (ERT) and ground penetration radar (GPR), and the usefulness of this inversion approach remains to be explored for a range of other geophysical methods. Although coupled hydrogeophysical inversion frameworks are flexible enough for the integration of multiple hydrologic and geophysical data types, this data fusion aspect has also received less attention. Therefore, the aim of this thesis was to develop inversion frameworks for the estimation of effective subsurface hydraulic parameters from: i) the fusion of ERT and inflow data obtained under constant head infiltration in a field sandy loam, ii) SP data acquired during primary drainage of a sandy soil column, and ...