Southeastern Section - 54th Annual Meeting (March 17–18, 2005)

Paper No. 3
Presentation Time: 1:40 PM

KARST POTENTIAL AND DEVELOPMENT INDICES: TOOLS FOR MAPPING KARST USING GIS


CURRENS, James C., CRAWFORD, Matthew M. and PAYLOR, Randall L., Kentucky Geological Survey, Univ of Kentucky, 228 Mining and Minerals Building, Lexington, KY 40506-0107, rpaylor@uky.edu

The Kentucky Geological Survey’s Digital Mapping Program completed capturing and compiling statewide geologic map data at a 1:24,000 scale for use in GIS. These data have made it possible to produce derivative products and analyses efficiently. A detailed analysis of Kentucky’s extensive karst terrain is one such product. To prepare a statewide map and other products, an index of relative karst development was needed to systematically compare one region to others.

The direct evaluation of karst geomorphic features is the preferred approach; however, the data are not uniformly available across the state. Because of localized availability, a surrogate measure was needed to extend the analysis statewide. Some digital geologic polygons have sufficient data for calculating karst indices by both a geomorphic and lithologic method.

The karst development index (KDI) evaluates the development of karst geomorphic features and bulk karst porosity. Criteria included in the KDI are epikarst development (depth to bedrock), sinkhole distribution, cave and spring distribution, and conduit density. KDI data are compiled for all areas possible, and each of the criteria is placed in a weighted scoring matrix to determine a value.

The karst potential index (KPI) evaluates the lithologic characteristics of geologic polygons that lead to karst development. Criteria selected in the KPI are bedding thickness, grain size, percentage of calcite in carbonate rock, and percent insolubles. The KPI criteria are also weighted in a scoring matrix to determine a value.

The two measures have been designed and calibrated for specific use in Kentucky. The KDI data are being collected and geologic unit polygons identified that have adequate data for scoring. The KPI compilation is complete. The two scores will be correlated to determine if the KPI is a predictor of the KDI. Classifications of karst areas as “mature” versus “immature” and differentiating those classifications with respect to land-use planning and engineering have always been subjective. The measures developed here are intended to form a basis for ranking karst development, anticipate karst geologic hazards, and mitigate the impact of human activity on karst aquifers.