Mangel, Adam R.Moysey, Stephen M. J.Bradford, John H.2018-01-252022-02-022018-01-252022-02-02https://hdl.handle.net/11124/172053http://dx.doi.org/10.25676/11124/172053The .zip file contains raw GPR data, soil moisture probe data, and all numerical simulations. A README file is included that describes the contents of each file. Analysis of the GPR data was carried out using commercial software.Ground-penetrating radar (GPR) reflection tomography algorithms allow non-invasive monitoring of water content changes resulting from flow in the vadose zone.  The approach requires multi-offset GPR data that is traditionally slow to collect.  We automate GPR data collection to reduce the survey time by orders of magnitude, thereby making this approach to hydrologic monitoring feasible.  The method was evaluated using numerical simulations and laboratory experiments that suggest reflection tomography can provide water content estimates to within 5-10% vol./vol. for the synthetic studies, whereas the empirical estimates were typically within 5-15% of in-situ probes.  Both studies show larger observed errors in water content near the periphery of the wetting front, beyond which additional reflectors were not present to provide data coverage.  Automation of GPR data collection enables higher-order data analysis algorithms, like reflection tomography, that show promise in resolving details of the spatial distribution of water content in soils through time.engCopyright of the original work is retained by the author.Dataset