Northeastern Section - 47th Annual Meeting (18–20 March 2012)

Paper No. 8
Presentation Time: 8:00 AM-12:00 PM

NEAR-SURFACE SITE CHARACTERIZATION OF THE FENTON RIVER WELLFIELD IN EAST CENTRAL CONNECTICUT USING MULTIPLE GEOPHYSICAL TECHNIQUES


MORTON, Sarah L.C., Civil & Environmental Engineering, University of Connecticut, 261 Glenbrook Road, Unit 2037, Storrs, CT 06269, LIU, Lanbo, University of Connecticut, Civil &Environmental Engineering, 261 Glenbrook Road, Unit 2037, Storrs, CT 06269, LANE Jr, John W., Office of Groundwater, Branch of Geophysics, U.S. Geological Survey, 11 Sherman Place, Unit 5015, Storrs-Mansfield, CT 06269 and VOYTEK, Emily B., Office of Groundwater, Branch of Geophysics, U.S. Geological Survey, 11 Sherman Place, Unit 5015, Storrs, CT 06269, sarah.morton@uconn.edu

The Fenton River wellfield in Storrs, Connecticut, is one of two major water-supply wellfields for the University of Connecticut’s main campus. The site consists of stratified glacial deposits over metamorphic bedrock. In order to optimize the temporal-spatial pumping scenario of the Fenton River wellfield and to classify the seismic hazard at this location, multiple surface geophysical surveys were conducted to characterize the subsurface hydrogeological conditions.

The first survey consisted of sixteen ambient noise seismic measurements collected along a profile within the wellfield. The resonant frequency from the horizontal-to-vertical spectral ratio (HVSR) was calculated at each seismometerlocation along the profile.The data were synthetically modeled to create a 1D shear-wave velocity structureand to estimate material thickness overlying the bedrock.Seismic refraction data were also collected along the same profile using a linear array of 48 geophones and a sledgehammer source.The depth to bedrock estimated from the passive seismic data was used to constrain inversion of the seismic refraction data. Results from the refraction data show a more detailed model of the subsurface when compared to the model from passive seismic data. These results are compared to GPR and well log data for verification of the site model.