ABSTRACT. Geophysical investigations on rock glaciers are often difficult because rock glaciers are covered by an unconsolidated debris mantle a few meters thick, are typically <50 m thick and are composed of an ice^rock mixture of unknown composition. Transient electromagnetics (TEM) is a method that allows some of these difficulties to be minimized, and data collection is relatively efficient. TEM, with calibration from terminus exposure, was used to determine the thickness ($60 m) of Fireweed rock glacier, Alaska, U.S.A., under complex valley geometry. A conductive layer beneath the rock glacier was identified, and its distribution is consistent with a till-like layer. Seismic refraction, used to resolve the debris-mantle thickness (2^4 m), suggests the presence of a discontinuity at 18^28 m depth within the rock glacier. The discontinuity is also indicated in the radio-echo sounding and theTEM data, but to a lesser extent. This discontinuity is important because the motion of the rock glacier may occur across this as a''shear plane'' . INTRODUCTIONEstimates of the thickness and cross-sectional shape of a rock glacier are important for understanding its stress distribution and motion. On ice glaciers this geometry is routinely determined using seismic and ice-radar methods. These methods are difficult to apply to rock glaciers because rock glaciers are thinner, are composed of a mixture of ice and rock of unknown composition and are covered by a 23 m thick layer of unconsolidated rock (the ''debris mantle''). Radio-echo sounding (RES) is difficult because the absorption and scattering of radar waves are stronger in rockglacier ice^rock mixtures than in clean ice and the basal interface may not be distinct. However, Berthling and others (2000), Degenhardt and others (2000), Isaksen and others (2000), Vonder Mu« hll and others (2001) and were successful in using ground-penetrating radar (GPR) to discern the basal interface and/or internal structures of some rock glaciers. Seismic methods are complicated by the debris mantle, which limits the transfer energy from the source (usually an explosion) into the rock glacier and inhibits geophone coupling. Seismic field techniques have been devised to overcome these problems , but are difficult to apply on a routine basis and have shown limited success. Direct-current (d.c.) electrical resistivity has been widely used in rock-glacier soundings (Fisch and others,1977; Evin and others, 1997;), but the debris mantle again poses problems with electrical coupling and requires laborintensive field set-ups. We have used all of these methods, with the exception of GPR, to investigate the geometry of Fireweed rock glacier with limited success. We have found that transient electromagnetic (TEM) methods provide the best means of investigating the internal structure and thickness distribution of the rock glacier. TEM methods do not require a high degree of physical or electrical coupling with the surface substrate. Here we discuss the methods and results for each of the techniq...

A nonlinear inversion scheme is described for the inversion of gravity data into a three‐dimensional polyhedral model. As presented, the inversion scheme is quite general and could have application to a wide range of nonlinear problems. Constraints, in the form of independent geologic information, play an essential role in the analysis. The parameterization of the problem allows inclusion of exact linear constraints to limit possible model shapes and to construct multiple body models. It also significantly reduces the degrees of freedom in a problem and can help the stability of the iterative process. Plausibility constraints are used to limit the total departure of the solution from a starting model known to a specified level of confidence. The optimal trade‐off between fitting noisy data and remaining close to a plausible starting model is determined empirically for each problem. The utility of the inversion scheme is illustrated with an example of estimating depth to bedrock from gravity data in Avra Valley, Arizona. The basin is modeled using three‐dimensional polyhedra. The analysis indicates two deep portions in the elongate basin separated by a 0.8‐km‐deep saddle point. Uncertainties in the solution are estimated, and the three controlling factors are independent control of depth to bedrock, data density, and basin depth.

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In this paper, we describe an instrument system for performing continuous resistivity profiling in shallow freshwater and marine environments. Using a streamer cable containing 9 electrodes, the system continuously samples the dipole-dipole resistivity at n-spacings 1 through 6. The system can be installed aboard a variety of small inboard or outboard powered vessels in a few hours. Hand-held or marine GPS units provide location information that is recorded by a laptop computer. With this system, up to 40 line-km/day of dipole-dipole data have been collected. The resistivity data are merged with the GPS positions as a post-processing step. The final step in the post-processing is the inversion of overlapping segments of each profile using a 2-D smooth model. The inversions provide high resolution images of the geoelectric cross-section. The depth of investigation ranges from 20-30 m, with a 10 m dipole spacing. Over the last 4-years, we have performed surveys on the Ohio River, near Louisville, KY, on tidal estuaries and bays along the Atlantic coast in Delaware, Maryland, Virginia, and North Carolina, and in Tampa Bay, Florida. Data from these surveys will be used to illustrate the final deliverable from a survey.

The largest costs associated with subsurface Unexploded Ordnance (UXO) remediation are associated with removing non-UXO debris. Discrimination between UXO and non-UXO is important for both cost and safety reasons. A neural network was developed to distinguish between UXO and non-UXO clutter using Time Domain Electromagnetic Method (TEM) data. There are two stages for the learning process of neural network: training and testing. A synthetic dataset was created using actual acquisition configurations, with varying amounts of random noise. This dataset included 934 UXO targets representing 7 different UXO types, and 789 clutter objects based on four templates with varying size and random asymmetry. The results show 97% accuracy for correctly classifying clutter, and 97% accuracy for correctly classifying UXO.