Northeastern Section (39th Annual) and Southeastern Section (53rd Annual) Joint Meeting (March 25–27, 2004)

Paper No. 1
Presentation Time: 8:00 AM-12:00 PM

DIGITAL GEOLOGIC DATA AND A NEW KARST POTENTIAL INDEX MAP: A WORK IN PROGRESS


CRAWFORD, Matthew M., Geospatial Analysis, Kentucky Geol Survey, 228 Mining and Mineral Resources Bldg, Lexington, KY 40506/0107 and CURRENS, James C., Kentucky Geological Survey, Univ of Kentucky, 228 Mining and Mineral Resources Building, Lexington, KY 40506-0107, mcrawford@uky.edu

One goal of the Kentucky Geological Survey’s digital geologic mapping program is to allow users to create derivative map products and customized sets of data. Geographic information system (GIS) technology allows for powerful analysis of currently available data in many areas of geology.

The work in progress presented here proposes an objective tool for semiquantitative analysis using GIS and geologic data designed to classify and rank karst development in Kentucky. Many classification schemes of karst development have been proposed over the long history of karst geomorphology. A new classification scheme was designed to take advantage of digital geologic maps and because of the availability of karst data.

Classification of karst areas as “mature” versus “immature” has traditionally been subjective. The ability to differentiate karst areas that require engineering caution, natural hazard mitigation, or environmental protection from areas that can be developed without extensive onsite investigation could save significant construction and land-use planning expenses where environmental damage would be less. The measures developed here are not intended to predict the frequency or specific location of karst hazards, but to form the basis ranking analysis for aquifer sensitivity, cover-collapse sinkhole susceptibility, and sinkhole flooding.

The “Geologic Map of the Harrodsburg 30 x 60 Minute Quadrangle” was used to create a table of lithologic characteristics relating to each geologic map unit. The Karst Potential Index is an empirically derived scoring matrix (score x weight) of four factors: percentage of calcite of a rock, bedding thickness, grain size, and percentage of insolubles. Because of the simplicity in the quantitative scheme and the easy revisions that can be made to digital geology, the index value can be adjusted to the best classification possible to produce an accurate map.

A mechanism for correlating a Karst Potential Index score with known occurrences of karst features, also represented as a quantitative scoring matrix, is under development.