HR: 08:30h
AN: H11G-02    [Abstracts]
TI: Characterizing Long-Term Near-Surface Soil Moisture Variability in Natural Environments using Electrical Resistivity Imaging and Hydrological Modeling
AU: * Jayawickreme, D H
EM: jayawick@msu.edu
AF: Department of Geological Sciences, Michigan State University, 206 Natural Science Building, East Lansing, MI 48824, United States
AU: Malkowski, M A
EM: malkow12@msu.edu
AF: Department of Geological Sciences, Michigan State University, 206 Natural Science Building, East Lansing, MI 48824, United States
AU: Van Dam, R L
EM: rvd@msu.edu
AF: Department of Geological Sciences, Michigan State University, 206 Natural Science Building, East Lansing, MI 48824, United States
AU: Hyndman, D W
EM: hyndman@msu.edu
AF: Department of Geological Sciences, Michigan State University, 206 Natural Science Building, East Lansing, MI 48824, United States
AB: The sensitivity of electrical conductivity to changes in moisture content of subsurface materials makes time-lapse electrical resistivity imaging (ERI) an ideal method to monitor transient moisture conditions in natural settings. Recent work has highlighted the usefulness of the ERI method for monitoring infiltration and solute transport processes in the vadose zone, yet most of these studies have been conducted in controlled settings. As a result, only limited knowledge exist on the applicability of ERI for monitoring long-term characteristics of near-surface soil moisture under natural conditions. Here we present results from a year-long application of ERI to monitor and quantify the effects of seasonal climate variability and vegetation dynamics on soil moisture beneath different vegetation types at a natural field site in Mid-Michigan. The site has been equipped with a permanent array of 84 surface resistivity electrodes spanning a 124 meter transect, 4 sets of 14 borehole electrodes, and multiple soil moisture and temperature sensors. Subsurface changes in resistivity were interpreted using standard 1D inversions and 2D difference inversions and have been corrected for temperature fluctuations. Laboratory measurements of the conductivity- soil water content relationships were used in conjunction with differential resistivity inversions to estimate changes in soil moisture distribution. Our combined vadose zone soil water infiltration modeling results and ERI interpretations show that ERI can successfully monitor the influence of seasonal vegetation changes and climatic variability on soil moisture and groundwater recharge. We will discuss challenges and uncertainties associated with the use of ERI method for environmental monitoring and hydrogeological applications.
DE: 1813 Eco-hydrology
DE: 1835 Hydrogeophysics
DE: 1838 Infiltration
DE: 1843 Land/atmosphere interactions (1218, 1631, 3322)
DE: 1847 Modeling
SC: Hydrology [H]
MN: 2007 Fall Meeting