Resistivity and induced polarization (IP) measurements (0.1-1000 Hz) were made on clay-free unconsolidated sediments from a sandy, alluvial aquifer in the Kansas River floodplain. The sensitivity of imaginary conductivity σ , a fundamental IP measurement, to lithological parameters, fluid conductivity, and degree of saturation was assessed. The previously reported power law dependence of IP on surface area and grain size is clearly observed despite the narrow lithologic range encountered in this unconsolidated sedimentary sequence. The grain-size σ relationship is effectively frequency independent between 0.1 and 100 Hz but depends on the representative grain diameter used. For the sediments examined here, d 90 , the grain diameter of the coarsest sediments in a sample, is well correlated with σ . The distribution of the internal surface in the well-sorted, sandy sediments investigated here is such that most of the sample weight is likely required to account for the majority of the internal surface. We find the predictive capability of the Börner model for hydraulic conductivity (K ) estimation from IP measurements is limited when applied to this narrow lithologic range.The relatively weak dependence of σ on fluid conductivity (σ w ) observed for these sediments when saturated with an NaCl solution (0.06-10 S/m) is consistent with competing effects of surface charge density and surface ionic mobility on σ as previously inferred for sandstone. Importantly, IP parameters are a function of saturation and exhibit hysteretic behavior over a drainage and imbibition cycle. However, σ is less dependent than the real conductivity σ on saturation. In the case of evaporative drying, the σ saturation exponent is approximately half of the σ exponent.Crosshole IP imaging illustrates the potential for lithologic discrimination of unconsolidated sediments. A fining-upward sequence correlates with an upward increase in normalized chargeability M n , a field IP parameter proportional to σ . The hydraulic conductivity distribution obtained from the Börner model discriminates a hydraulically conductive sand-gravel from overlying medium sand.

An electrical resistivity survey was completed at the Landusky mine. The survey consisted of 15 lines on the surface of the reclaimed Suprise pit, Queen Rose pit, and the region immediately south of Swift Gulch. Additionally, wells and seeps were used by energizing electrodes in direct contact with ground water to increase the sensitivity of the resistivity method at depth. The survey was conducted to locate potential acid rock drainage pathways that are contaminating Swift Gulch. The results showed that the lowest resistivity values were coincident with the Queen Rose pit. Furthermore, the low resistivity feature appeared to trend northeast along a known fault, consistent with the geologic understanding of the site. A scatter plot of resistivity values versus total dissolved solids (TDS) showed a strong correlation (R 2 = 0.85). A linear regression model suggests TDS at the lowest resistivity region to be approximately 2.5 times greater than that measured in ground water wells.

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Field validation for the long electrode electrical resistivity tomography (LE-ERT) method was attempted in order to demonstrate the performance of the technique in imaging a simple buried target. The experiment was an approximately 1/17 scale mock-up of a region encompassing a buried nuclear waste tank on the Hanford site. The target of focus was constructed by manually forming a simulated plume within the vadose zone using a tank waste simulant. The LE-ERT results were compared to ERT using conventional point electrodes on the surface and buried within the survey domain. Using a pole-pole array, both point and long electrode imaging techniques identified the lateral extents of the pre-formed plume with reasonable fidelity, but the LE-ERT was handicapped in reconstructing the vertical boundaries. The pole-dipole and dipole-dipole arrays were also tested with the LE-ERT method and were shown to have the least favorable target properties, including the position of the reconstructed plume relative to the known plume and the intensity of false positive targets. The poor performance of the pole-dipole and dipole-dipole arrays was attributed to an inexhaustive and non-optimal coverage of data at key electrodes, as well as an increased noise for electrode combinations with high geometric factors. However, when comparing the model resolution matrix among the different acquisition strategies, the pole-dipole and dipole-dipole arrays using long electrodes were shown to have significantly higher average and maximum values than any pole-pole array. The model resolution describes how well the inversion model resolves the subsurface. Given the model resolution performance of the pole-dipole and dipole-dipole arrays, it may be worth investing in tools to understand the optimum subset of randomly distributed electrode pairs to produce maximum performance from the inversion model.