Quantifying shallow subsurface water and heat dynamics using coupled hydrological-thermal-geophysical inversion

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Abstract

Improving our ability to estimate the parameters that control water and heat fluxes in the shallow subsurface is particularly important due to their strong control on recharge, evaporation and biogeochemical processes. The objectives of this study are to develop and test a new inversion scheme to simultaneously estimate subsurface hydrological, thermal and petrophysical parameters using hydrological, thermal and electrical resistivity tomography (ERT) data. The inversion scheme-which is based on a nonisothermal, multiphase hydrological model-provides the desired subsurface property estimates in high spatiotemporal resolution. A particularly novel aspect of the inversion scheme is the explicit incorporation of the dependence of the subsurface electrical resistivity on both moisture and temperature. The scheme was applied to synthetic case studies, as well as to real datasets that were autonomously collected at a biogeochemical field study site in Rifle, Colorado. At the Rifle site, the coupled hydrological-thermal-geophysical inversion approach well predicted the matric potential, temperature and apparent resistivity with the Nash-Sutcliffe efficiency criterion greater than 0.92. Synthetic studies found that neglecting the subsurface temperature variability, and its effect on the electrical resistivity in the hydrogeophysical inversion, may lead to an incorrect estimation of the hydrological parameters. The approach is expected to be especially useful for the increasing number of studies that are taking advantage of autonomously collected ERT and soil measurements to explore complex terrestrial system dynamics.

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APA

Phuong Tran, A., Dafflon, B., Hubbard, S. S., Kowalsky, M. B., Long, P., Tokunaga, T. K., & Williams, K. H. (2016). Quantifying shallow subsurface water and heat dynamics using coupled hydrological-thermal-geophysical inversion. Hydrology and Earth System Sciences, 20(9), 3477–3491. https://doi.org/10.5194/hess-20-3477-2016

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