Removing the effects of temperature on electrical resistivity tomography data collected in partially frozen ground: Limitations and considerations for field applications

Abstract

Abstract 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.