Quantifying Impacts of Solute Transport on Time Lapse ERT at a Michigan Ecotone

Abstract:

Electrical resistivity tomography (ERT) methods have increasingly been used to capture soil moisture dynamics in the vadose-zone. A primary challenge to this approach is limited confidence in the relationship between measured resistivity and water content. The translation between these two variables typically follows Archie’s Law, with parameters for each soil type fit using lab bench experiments at saturation with fixed pore water concentrations. Quality petrophysics is at the heart of electrical methods’ use as a proxy for soil moisture in the field, but sensitivity to both soil properties and pore water conductivity complicates transient problems.

Evapotranspirative processes throughout the growing season increase solute concentrations as incoming precipitation is limited by canopy interception. In temperate climates, signals from increased soil moisture often overwhelm the reduced conductivity from dilution during infiltration events, and thus many studies have accepted errors from a simplified petrophysics model which does not account for changing salinity. However, for the purpose of understanding the physiological interactions between the root zone and soil water, modeling changes in pore water conductivity is a critical aspect of capturing all of the dynamics of the system, and in fact my aid in mapping the extent of the root zone. The objective of this study is thus to incorporate solute transport processes into a coupled hydrogeophysical inversion model that will be tested at a Michigan forest-grass ecotone site with the goal of: 1) quantifying the errors in soil moisture distributions introduced by simplified pore water conductivity estimates, and 2) decoupling the contributions from solutes and soil moisture to resistivity measurements. These efforts will yield a fundamental understanding of the role solute transport plays in ERT inversions, and will improve the understanding of root uptake processes throughout the growing season.