Inversion of low-induction number conductivity meter data to predict seasonal saturation variation

Our research introduced a method to monitor saturation in the near surface. In agricultural settings, methods measuring electrical conductivity can provide useful information about soil type, moisture content, and salinity extent. Electrical conductivity meters have been used in a number of studies to determine soil properties in a qualitative sense. We examined the range of structures in which the use of low-induction number instruments can be used successfully to determine layered-earth electrical conductivity. We used an inversion routine which employs a Bayesian modification to the ridge-regression technique with a priori conductivity assumptions typical of agricultural areas. We performed joint inversion of horizontal and vertical dipole configurations at two coil separations for layer over half-space models with electrical properties of silt, loam, clay, and saline waters. Generally, the inversion code resolved layer thickness to better than 25% and electrical conductivity to better than 20% if the layer is less than 3-m thick. We then inverted field measurements acquired in salt-scalded areas in the Yass River Valley, New South Wales, Australia, to determine a layer over a half-space. With Kennedy's formulation concerning the relationship between porosity, water saturation and electrical conductivity, we used the field results to predict autumn water saturation for the top layer to be 13% and the bottom layer to be 15%. In the spring, we used the field results to predict saturation of 50% for the top layer and 51% for the bottom layer, leading to a seasonal variation in soil saturation of approximately 36%. Predicted saturation was spatially consistent across the traverse line, suggesting that the developed methodology was successful.