23 Karst Processes and Speleology (Posters)

Tuesday, 26 March 2019
8:30 AM - 5:45 PM
Big Basin/Kaw Nation Rooms

DETECTION OF SINKHOLES AND OTHER KARST FEATURES USING ELECTRICAL RESISTIVITY TOMOGRAPHY IN RICHMOND, KENTUCKY

Paper number: 23-2
Program: Theme Sessions
Time: 8:30 AM – 5:45 PM

Authors

Abstract

Electrical resistivity tomography (ERT) is a geophysical technique for imaging the near-surface environment. The technique involves placing regularly-spaced (n, in meters) electrodes into the ground then systematically applying a constant current (I, in amps) on two electrodes while measuring voltage potentials (V, in volts) on other electrode pairs; apparent resistivity (r, in Ohm-meters) is then calculated from Ohms Law (R = V/I) and an inversion model is applied to produce a Resistivity Inversion Section. We use an Advanced Geosciences, Inc., SuperSting R1 (single-channel) resistivity unit with 28 electrodes, electrode spacing between 1 and 3 m, and a dipole-dipole array.

Richmond is situated in the outer Bluegrass Region of Kentucky. The bedrock consists of Ordovician limestone assigned to the Callow Creek, Ashlock, and Drakes formations, which are characterized by thinly bedded lime and dolomitic mudstones interbedded with argillaceous limestones. The lack of massive limestones generally inhibits the development of large karst features, but sinkholes are found throughout the region along southeast-northwest faults. First- and second-order streams in Richmond form trellis patterns that run approximately parallel and perpendicular to these faults, which has led previous workers to hypothesize that previously unrecognized sinkholes and solution valleys may occur along these and are therefore much more common than previously recognized in Richmond, Kentucky. In this study, we present the results of ERT surveys of several of these streams and compare them to ERT surveys of known sinkholes in the region to map karst features and asses karst hazards in the outer Bluegrass Region.

Geological Society of America Abstracts with Programs. Vol. 51, No. 2

doi: 10.1130/abs/2019SC-326286

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