GSA Annual Meeting in Seattle, Washington, USA - 2017

Paper No. 82-27
Presentation Time: 9:00 AM-5:30 PM

EVALUATING THE EFFECTIVENESS OF ERT FOR ASSESSING SUBSURFACE STRUCTURE AT THE LANDSCAPE EVOLUTION OBSERVATORY


LITWIN, David1, MEIRA, Antonio2 and TROCH, Peter2, (1)Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, (2)Department of Hydrology and Water Resources, University of Arizona, Tucson, AZ 85721, dlitwin2@illinois.edu

The structure of the subsurface plays an important role in mediating interactions between microbiology, geochemistry, and hydrology in the critical zone. In particular, it controls the space available for air, water, and life, and thus affects geochemical properties, which in turn influence hydrologic properties. These interactions are greatly informed by our understanding of the subsurface. Increasing this understanding may be accomplished with a variety of destructive and non-destructive methods. Geo-electrical techniques are commonly used for non-destructive measurements of water content, solute concentration, and general substrate properties, though they are rarely used to capture details of subsurface structure. However, under proper conditions, electrical resistance tomography (ERT) shows promise for this task. The large scale of the Landscape Evolution Observatory (LEO) at Biosphere 2 and its interdisciplinary focus are especially well suited to test the ability of ERT to derive patterns of subsurface structure that can be linked with hydro-ecological patterns. Here we propose a method that takes advantage of this controlled environment in order to determine the spatial distribution of porosity in the LEO hillslopes. This method is based in a simple application of the principles of electrical current flow in soils and shows promising results when idealized scenarios are considered. However, it must be tested for robustness against the inherent errors in modeled or measured data. This study presents a synthetic experiment designed specifically to characterize the influence of error in the measured variable (electrical resistance) on the retrieved porosity fields.