Analysis of Sinkhole Susceptibility and Karst Distribution in the Northern Shenandoah Valley, Virginia: Implications for Low Impact Development (LID) Site Suitability Models
Increased stormwater runoff due to urban development in the northern Shenandoah Valley (NSV) region of Virginia has prompted local officials and representatives to consider Low Impact Development (LID) as a stormwater management technique. LID is based on infiltrating stormwater runoff at the source through practices such as bioretention, rain gardens, and grass swales. The karst terrain that underlies the Shenandoah Valley presents a major barrier to the use of LID. Infiltration of surface runoff in karst landscapes may threaten groundwater quality and the stability of the bedrock. In 2004 the Center for Geospatial Information Technology (CGIT) at Virginia Tech developed an LID site suitability model for the NSV region incorporating karst as a key component in distinguishing unsuitable from suitable conditions for LID. But, due to the difficulty of mapping karst, the karst layer used in the site suitability model is very coarse in resolution, based primarily on carbonate versus non-carbonate rock.
This study uses a 1:24,000 scale sinkhole map derived from sinkhole boundaries identified by geologist David Hubbard (1984) of the Virginia Department of Mines and Minerals (DMME) to develop a more detailed karst map for a sub-watershed of the NSV region. The analysis uses geospatial techniques to determine the relationship between sinkhole distribution and four major landscape factors: bedrock type, soil depth to bedrock, proximity to geologic faults, and proximity to surface streams. The analysis identified three major trends in sinkhole occurrence: (1) sinkholes are more abundant in relatively pure carbonate rocks of Ordivician age; (2) sinkhole occurrence increases with proximity to fault lines; and (3) sinkholes are sparse near streams, most abundant 600 to 1400 feet away from surface streams. Based on these findings a sinkhole susceptibility index was produced using weighted overlay analysis in ArcGIS. The sinkhole susceptibility index provides a more detailed karst layer for the LID site suitability maps and can be used by the NSV region as a predictive tool for future sinkhole occurrence.