Date of Award

8-2016

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Legacy Department

Environmental Engineering

Committee Member

Stephen M.J. Moysey

Committee Member

Lawrence C. Murdoch

Committee Member

Ronald W. Falta

Committee Member

Christophe Darnault

Abstract

This body of research focuses on resolving physical and hydrological heterogeneities in the subsurface with ground-penetrating radar (GPR). Essentially, there are two facets of this research centered on the goal of improving the collective understanding of unsaturated flow processes: i) modifications to commercially available equipment to optimize hydrologic value of the data and ii) the development of novel methods for data interpretation and analysis in a hydrologic context given the increased hydrologic value of the data. Regarding modifications to equipment, automation of GPR data collection substantially enhances our ability to measure changes in the hydrologic state of the subsurface at high spatial and temporal resolution (Chapter 1). Additionally, automated collection shows promise for quick high-resolution mapping of dangerous subsurface targets, like unexploded ordinance, that may have alternate signals depending on the hydrologic environment (Chapter 5). Regarding novel methods for data inversion, dispersive GPR data collected during infiltration can constrain important information about the local 1D distribution of water in waveguide layers (Chapters 2 and 3), however, more data is required for reliably analyzing complicated patterns produced by the wetting of the soil. In this regard, data collected in 2D and 3D geometries can further illustrate evidence of heterogeneous flow, while maintaining the content for resolving wave velocities and therefore, water content. This enables the use of algorithms like reflection tomography, which show the ability of the GPR data to independently resolve water content distribution in homogeneous soils (Chapter 5). In conclusion, automation enables the non-invasive study of highly dynamic hydrologic processes by providing the high resolution data required to interpret and resolve spatial and temporal wetting patterns associated with heterogeneous flow. By automating the data collection, it also allows for the novel application of established GPR data algorithms to new hydrogeophysical problems. This allows us to collect and invert GPR data in a way that has the potential to separate the geophysical data inversion from our ideas about the subsurface; a way to remove ancillary information, e.g. prior information or parameter constraints, from the geophysical inversion process.

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