The accuracy of electrical resistivity tomography (ERT) as a method for locating frozen-to-unfrozen interfaces in permafrost environments was investigated systematically for simplified scenarios using forward modeling. The impacts of varying the resistivity, thickness, and lateral continuity of the frozen region, altering the thickness
Core Ideas
We collected resistivity data at a range of temperatures and initial saturations.
Archie's equation was modified to include temperature dependence below 0°C.
Bulk resistivity was used to estimate unfrozen water content and fluid resistivity.
At subzero temperatures, unfrozen water content is independent of initial saturation.
Ion exclusion from ice explains the dependence of resistivity on initial saturation.
Electrical resistivity tomography has been used in many frozen ground applications to delineate frozen and unfrozen areas of the subsurface and monitor changes with time. In these studies, the amount of unfrozen water remaining in the pore space at subzero temperatures is often a parameter of interest. To interpret resistivity data quantitatively in terms of unfrozen water content, it is necessary to establish a relationship between bulk resistivity, subzero temperature, and liquid water saturation. In the literature, a consensus has not been reached on the form of this relationship, and a better understanding of the mechanisms controlling the resistivity of frozen ground is needed. This study used a unique laboratory apparatus to collect electrical resistivity tomography data for a uniform porous medium at temperatures from −20 to 25°C for a range of initial water saturations. Archie's equation was modified to include the effects of temperature above and below 0°C. Resistivity data collected below 0°C were used to estimate temperature‐dependent liquid water saturation and fluid resistivity. The amount of unfrozen water remaining at a given temperature was not related to initial water saturation and was nearly identical for all initial saturations at temperatures below about −5°C. The dependence of resistivity–temperature curves on initial water saturation at subzero temperatures was caused by differences in fluid resistivity as a result of ion exclusion during freezing. The relationships established in this study provide insight into the physical mechanisms that govern the resistivity of porous media at subzero temperatures and a starting point for quantitative analysis of resistivity data collected in frozen ground.
Time-lapse electrical resistivity tomography (ERT) can be used to image a wide variety of subsurface processes. It is often necessary to remove the effects of seasonal near-surface temperature variability in order to interpret the signal of interest. Here, we use a synthetic modeling approach to explore the challenges related to removing temperature effects from ERT data in seasonally frozen ground. Electrical resistivity tomography data collection and processing methods that are often used to improve resolution in frozen ground do not appreciably improve the accuracy of temperature corrected data. A sensitivity analysis showed that errors in the temperature corrected data are primarily caused by error in the inverted resistivity models, and that this sensitivity to model error is much higher in partially frozen ground than in unfrozen ground.
INTRODUCTIONElectrical resistivity tomography (ERT) is a geophysical method that uses electrical resistance measurements to estimate subsurface resistivity. Resistivity is sensitive to several factors, including rock type, porosity, water saturation, pore water chemistry, and temperature, making ERT a valuable tool for a wide range of environmental problems (Samouëlian et al., 2005). Additionally, multiple ERT datasets can be collected over time to image dynamic processes-for example, to monitor snowmelt infiltration (
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