2007 GSA Denver Annual Meeting (28–31 October 2007)

Paper No. 3
Presentation Time: 8:35 AM

RESISTIVITY PROFILING AND GPR FOR CHARACTERIZATION OF URBAN FILL AND BURIED INFRASTRUCTURE


EATON, Timothy T., School of Earth and Environmental Sciences, Queens College CUNY, 65-30 Kissena Blvd, Flushing, NY 11367, CRANGANU, Constantin, Geology, Brooklyn College, 2900 Bedford Avenue, Brooklyn, NY 11210 and NITSCHE, Frank, Lamont-Doherty Earth Observatory, of Columbia Univ, Palisades, NY 10964, Timothy.Eaton@qc.cuny.edu

Urban environments present complex subsurface conditions because of the long history of land use. Different materials can create preferential flowpaths for groundwater flow and contaminant transport, and affect quality of coastal discharge to surface waters. Buried infrastructure or foundations can impede site remediation. High resolution geophysical methods are useful and cost-effective for such site characterization, however unexpected findings and non-uniqueness create interpretation challenges for shallow aquifer sediments. Several examples of investigations in the highly urbanized landscape of Queens, NY show how resistivity profiling and ground penetrating radar (GPR) reveal materials and structures in the subsurface.

In some cases, where sediments are relatively undisturbed, materials consistent with Pleistocene stratigraphy can be imaged. A low resistivity lense was identified on the Queens College campus where a soil boring was reported to traverse thick clay. Elsewhere, data are more ambiguous because high resistivity materials can result from unsaturated sand or anthropogenic fill for landscaping. In lowland areas, where stream channel meanders are known from historical maps, fill materials may be difficult to discern unless material properties (fly ash, debris) have distinctively different properties from surrounding sediment. In such cases, and for identifying urban infrastructure, such as conduits, stormwater mains or foundations, GPR can be useful. Multiple methods are always recommended for reducing interpretation uncertainty.