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Long-term electrical resistivity monitoring of recharge-induced contaminant plume behavior
- Gasperikova, Erika, Hubbard, Susan S., Watson, David B., Baker, Gregory S., Peterson, John E., Kowalsky, Michael B., Smith, Meagan, Brooks, Scott
- Journal of contaminant hydrology 2012 v.142-143 pp. 33-49
- data collection, electrical resistance, hydrology, models, monitoring, nitrates, ponds, rain, seasonal variation, tomography, total dissolved solids, Tennessee
- Geophysical measurements, and electrical resistivity tomography (ERT) data in particular, are sensitive to properties that are related (directly or indirectly) to hydrological processes. The challenge is in extracting information from geophysical data at a relevant scale that can be used to gain insight about subsurface behavior and to parameterize or validate flow and transport models. Here, we consider the use of ERT data for examining the impact of recharge on subsurface contamination at the S-3 ponds of the Oak Ridge Integrated Field Research Challenge (IFRC) site in Tennessee. A large dataset of time-lapse cross-well and surface ERT data, collected at the site over a period of 12months, is used to study time variations in resistivity due to changes in total dissolved solids (primarily nitrate). The electrical resistivity distributions recovered from cross-well and surface ERT data agrees well, and both of these datasets can be used to interpret spatiotemporal variations in subsurface nitrate concentrations due to rainfall, although the sensitivity of the electrical resistivity response to dilution varies with nitrate concentration. Using the time-lapse surface ERT data interpreted in terms of nitrate concentrations, we find that the subsurface nitrate concentration at this site varies as a function of spatial position, episodic heavy rainstorms (versus seasonal and annual fluctuations), and antecedent rainfall history. These results suggest that the surface ERT monitoring approach is potentially useful for examining subsurface plume responses to recharge over field-relevant scales.