HR: 15:10h
AN: H43J-07 [Abstracts]
TI: Optimizing the Design of Electrical Resistivity Tomography Surveys for Hydrologic Monitoring
AU: Furman, A
EM: alexf@agri.gov.il
AF: Soil, Water and Environmental Sciences
ARO - Volcani Center, P.O. Box 6
Israel, Bet Dagan, 50250
Israel
AU: * Ferre, T P
EM: ty@hwr.arizona.edu
AF: University of Arizona, 1133 E. North Campus Drive, Tucson, AZ 85721-0011
United States
AU: Warrick, A W
EM: aww@ag.arizona.edu
AF: University of Arizona, P.O. Box 210038, Tucson, AZ 85721-0038
United States
AB:
Electrical resistivity tomography (ERT) has shown great promise for monitoring transient hydrologic processes. One great
advantage of ERT is the ability to use a large number of installed electrodes in a series of combinations to image the
subsurface in two or three dimensions. For slow processes, all electrode-pair combinations can be used to form a complete
data set for inversion of the subsurface electrical conductivity distribution. However, if the process is rapid compared with
the time required to measure all of the electrode-pair combinations, then a subset of the possible combinations must be
selected. In practice, it is too time-consuming to measure all electrode arrays, so some form of reduction of the arrays used
is performed. While many researches focus on improving the inversion of ERT data, we present an approach to tailoring ERT
surveys through the optimal selection of ERT arrays. The approach is based on examination of the spatial sensitivity of
individual ERT array and on the cumulative spatial sensitivity of a survey comprised of a fixed number of arrays.
Furthermore, our approach uses normalized local sensitivities (offsets) to avoid over-sampling of shallow regions of the
subsurface. Finally, our approach decouples the solution grid from the grid used to target the survey sensitivity, allowing
for more rapid survey optimization. As an example, we present the optimization of combined surface and borehole ERT
electrodes for monitoring the advance of a wetting front through homogeneous or layered media. We compare the spatial
sensitivity of optimized arrays with the sensitivity patterns of standard arrays comprised of a single array type (e.g.
Schlumberger).
DE: 1835 Hydrogeophysics
DE: 1866 Soil moisture
DE: 1875 Vadose zone
SC: Hydrology [H]
MN: Fall Meeting 2005