2014 GSA Annual Meeting in Vancouver, British Columbia (19–22 October 2014)

Paper No. 116-5
Presentation Time: 10:00 AM

SPATIAL ANALYSIS OF KARST FEATURE OCCURENCE IN HARPERS FERRY NATIONAL HISTORICAL PARK


CARLSON, Brandee, National Park Service, Harpers Ferry, 2500 Smith Ave, Taylor, TX 76574

Karst features within Harpers Ferry National Historical Park (HAFE) were inventoried, mapped, and analyzed for spatial patterns. Mapping and inventorying karst features provides HAFE with the ability to properly manage features, maintain and enhance groundwater quality and quantity, and support the health of subterranean ecosystems. Furthermore, the spatial distribution of karst features offers insight to the factors that control karst formation over an area. Preliminary determination of potential karst features was assessed using 1m resolution Light Detection and Ranging (LiDAR) surveys of the study area and various processing methods in ArcGIS (v.10.2.2). Depressions were automatically generated by filling the LiDAR digital elevation model (DEM) to its fill-point and subtracting the original DEM. Topographic Position Index (TPI) rasters, slopeshade, and aerial imagery were also used to manually delineate depressions. Potential karst features were field-checked and a Global Positioning System (GPS) was used to record the location of each feature. Using various statistical analyses in ArcGIS, karst feature locations were determined to be non-random. The location of features were inspected with respect to structural and anthropogenic controls such as geologic formation, surface slope, and proximity to wells, fractures, faults, quarries, fold axes, and streams. Fractures and lithology show a strong correlation to karst feature location, and the surface slope surrounding karst features is generally low (<10 degrees). To determine the influence of anthropogenic controls in the study area, such as wells and quarries, updated data sets and monitoring programs are suggested. A karst susceptibility map was generated for HAFE based on the current clustering of features. The results provide insight for park management programs ranging from water quality and quantity to ecological protection and karst feature preservation.