HR: 1340h
AN: H23G-1721    [Abstracts]
TI: Identifying an Optimal ERT Measurement Set to Estimate Contaminant Plume Mass
AU: * Hinnell, A C
EM: ahinnell@hwr.arizona.edu
AF: Department of Hydrology and Water Resources, University of Arizona, 1133 E James E Rogers Way, Tucson, AZ 85721-0011,
AU: Ferre, T P
EM: ty@hwr.arizona.edu
AB: Heterogeneous hydrologic properties lead to complex pathways for solute transport and spatially nonuniform distributions of solute mass through time. This nonuniformity presents challenges for characterizing solute mass distributions using conventional point sampling. Furthermore, it is unclear how relatively few point measurements can be combined to give reasonable estimates of the total solute mass. These challenges have led to increased interest in the use of geophysical (especially electrical) methods to characterize solute distributions through space and time. Although individual measurements of electrical resistance are rapid, collecting sufficient data to constrain the estimation of the electrical resistivity structure can be expensive. The objective of this study is to determine whether an optimal set of ERT measurements can be identified for the purpose of estimating the total solute mass in a plume through time. An optimal measurement set produces an estimate of the solute mass with the required accuracy and precision using the least number of measurements. Underlying this effort is the hypothesis that the larger support volume and smaller per-measurement cost of ERT measurements can improve estimates of total solute mass. However, these improvements will only be realized if the design of the ERT network explicitly considers the effects of subsurface heterogeneity on the spatial sensitivity of individual ERT measurements and on the entire ERT survey. We compare this approach to ERT survey designs that maximize the sensitivity of the ERT measurements without consideration of state dependent sensitivity. Finally, we show how genetic algorithms can be used to efficiently design optimal ERT surveys and how the optimal surveys used together with coupled flow, transport and ERT modeling improve plume characterization in heterogeneous media.
DE: 0925 Magnetic and electrical methods (5109)
DE: 1832 Groundwater transport
DE: 1835 Hydrogeophysics
SC: Hydrology [H]
MN: 2007 Fall Meeting