On the field estimation of moisture content using electrical geophysics‐the impact of petrophysical model uncertainty

Tso, Michael and Kuras, Oliver and Binley, Andrew (2019) On the field estimation of moisture content using electrical geophysics‐the impact of petrophysical model uncertainty. Water Resources Research, 55 (8). pp. 7196-7211. ISSN 1944-7973

Text (Tso_et_al-2019-Water_Resources_Research online first)
Tso_et_al_2019_Water_Resources_Research_online_first.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.
Download (7MB)

Abstract

The spatiotemporal distribution of pore water in the vadose zone can have a critical control on many processes in the near-surface Earth, such as the onset of landslides, crop yield, groundwater recharge, and runoff generation. Electrical geophysics has been widely used to monitor the moisture content (θ) distribution in the vadose zone at field sites, and often resistivity (ρ) or conductivity (σ) is converted to moisture contents through petrophysical relationships (e.g., Archie's law). Though both the petrophysical relationships (i.e., choices of appropriate model and parameterization) and the derived moisture content are known to be subject to uncertainty, they are commonly treated as exact and error-free. This study examines the impact of uncertain petrophysical relationships on the moisture content estimates derived from electrical geophysics. We show from a collection of data from multiple core samples that significant variability in the θ(ρ) relationship can exist. Using rules of error propagation, we demonstrate the combined effect of inversion and uncertain petrophysical parameterization on moisture content estimates and derive their uncertainty bounds. Through investigation of a water injection experiment, we observe that the petrophysical uncertainty yields a large range of estimated total moisture volume within the water plume. The estimates of changes in water volume, however, generally agree within (large) uncertainty bounds. Our results caution against solely relying on electrical geophysics to estimate moisture content in the field. The uncertainty propagation approach is transferrable to other field studies of moisture content estimation.