Using Electrical Resistivity Imaging (ERI) to Improve Understanding of Hydraulic Redistribution by Root Zone Processes

Electrical resistivity imaging (ERI) was used in the New Jersey Pinelands to determine spatiotemporal resistivity changes in the vadose root zone of a pine forest following a major rainfall event. By imaging from the surface to 2.5 m depth, incorporating the shallow root zone, the spatial variability of hydraulic redistribution (HR) in tree and non-tree areas related to biological and physical processes has been captured.  Using a dipole-dipole type survey configuration, resistance measurements from a grid of 96 electrodes was collected over a period from May 2009 to July 2009.  Images were produced from a 3-D inversion of weighted apparent resistivity datasets.  To account for temperature variations, a sinusoidal diurnal temperature correction based on the 1-D heat conduction equation and measurements at 5 cm depth was applied to the resistivity results.  In laboratory studies,

Laboratory measurements on samples from the site revealed that Archie power-law parameters relating resistivity to moisture content exhibit significant spatial variability impractical to quantify over the extent of the field survey.  Hence, this study focused on inferring spatiotemporal variability in moisture dynamics from variation in changes of conductivity over time.  Conductivity depth profiles were generated for tree versus non-tree locations using resistivities from corresponding finite element mesh voxel coordinates.  These profiles reveal a stable temporal profile beneath trees relative to a pronounced decrease in conductivity over time for non-tree locations.  Relative changes in conductivity from 6 am versus 6 pm surveys revealed that both tree and non-tree locations are more conductive at 6 am, although changes are greatest at tree locations.  This finding is likely diagnostic of hydraulic lift in trees.  Regardless of location, the differences between 6 am and 6 pm surveys are consistent with HR, impacting moisture content across the entire survey area.