The temperature effect and correction models for using electrical resistivity to estimate wood moisture variations

Abstract Electrical resistivity (ER) tomography is a useful nondestructive tool to visualize and estimate moisture content distribution in soil and wood. Wood ER is a function of both moisture and temperature, however, it is not known yet how the temperature effect should be corrected in order to use ER tomography to monitor wood moisture variations. This study aims to break this technical barrier. The ER of three trunk sections of different Australian native tree species was measured at varying temperature (control experiments), and for different moisture contents. The results show that wood ER decreases with an increase of temperature in a nonlinear manner, and that the exponential model performs the best to represent the temperature effect on ER in comparison to two other models (the linear model and power function model). The key parameter in the exponential model for sapwood, reflecting temperature sensitivity, fluctuates in a narrow range between 0.032 and 0.036 (°C-1). It appears to be independent of tree species, but significantly different from the value recommended in the literature for temperature correction in soil electrical resistivity. The temporal variations of temperature-corrected ER capture wood moisture variations in time. We suggest that it is better to have wood temperature monitoring while ER tomography is taken for living trees so that the temperature effect can be removed from ER tomograms using the exponential model for wood moisture estimation.