Abstract

Karst terrain is landscape underlain by limestone that has been chemically dissolved by acidic groundwater, producing subsurface voids that pose risks for sinkholes if the overlaying soils can no longer support their own weight and collapse. The western counties of Virginia are heavy in karst due to their natural, geographic boundary of the western Ridge Province and the eastern Blue Ridge Mountain Range. As a result, the Commonwealth of Virginia Hazard Mitigation Plan recommends that the Virginia Department of Transportation (VDOT) develop a method to determine the roadways and regions most susceptible to experiencing sinkholes, in an effort to reduce the number of reported sinkhole damage to property. While many noninvasive methods exist to detect subsurface voids, such as electric resistivity imaging, ground penetrating radar, and seismic surveys, these methods are time consuming and costly. This study proposes the use of a geographic information system (GIS) to create a susceptibility map, pinpointing regions in the karst counties of Virginia, in particular, along interstates, most at risk of future sinkhole development, determined by five factors that have previously been shown to play a role in the acceleration of sinkhole formation in Virginia: bedrock type, proximity to fault lines, drainage class, slope of incised river banks, and minimum soil depth to bedrock. The analysis compares a 1:24,000 scale map of existing sinkholes developed by Virginia Department of Mines Minerals and Energy (DMME) geologist, David Hubbard, with a series of risk maps representing differing combinations of each of the five risk factors to determine which weighted combination is most appropriate to use for a final representative risk map. The layers representing each risk factor are created using publicly available tabular and spatial data taken from the USDA Soil Survey Geographic (SSURGO) Database, the USGS National Map, the USGS Mineral Resources Online Data, and the National Weather Service. The methodology used to gather information specifically from the SSURGO database is highlighted within this paper. Data from the SSURGO database is used to create the bedrock type, drainage class, and minimum soil depth to bedrock layers. A substantial benefit to this methodology is that the new technique can be adjusted to accommodate for sinkhole susceptibility in regions across the world, by simply adjusting the input risk layers to consider sinkhole risk potential based on the specific geology of a particular region.

DOI

http://dx.doi.org/10.5038/9780991000951.1048

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A Method of Mapping Sinkhole Susceptibility Using a Geographic Information System: A Case Study for Interstates in the Karst Counties of Virginia

Karst terrain is landscape underlain by limestone that has been chemically dissolved by acidic groundwater, producing subsurface voids that pose risks for sinkholes if the overlaying soils can no longer support their own weight and collapse. The western counties of Virginia are heavy in karst due to their natural, geographic boundary of the western Ridge Province and the eastern Blue Ridge Mountain Range. As a result, the Commonwealth of Virginia Hazard Mitigation Plan recommends that the Virginia Department of Transportation (VDOT) develop a method to determine the roadways and regions most susceptible to experiencing sinkholes, in an effort to reduce the number of reported sinkhole damage to property. While many noninvasive methods exist to detect subsurface voids, such as electric resistivity imaging, ground penetrating radar, and seismic surveys, these methods are time consuming and costly. This study proposes the use of a geographic information system (GIS) to create a susceptibility map, pinpointing regions in the karst counties of Virginia, in particular, along interstates, most at risk of future sinkhole development, determined by five factors that have previously been shown to play a role in the acceleration of sinkhole formation in Virginia: bedrock type, proximity to fault lines, drainage class, slope of incised river banks, and minimum soil depth to bedrock. The analysis compares a 1:24,000 scale map of existing sinkholes developed by Virginia Department of Mines Minerals and Energy (DMME) geologist, David Hubbard, with a series of risk maps representing differing combinations of each of the five risk factors to determine which weighted combination is most appropriate to use for a final representative risk map. The layers representing each risk factor are created using publicly available tabular and spatial data taken from the USDA Soil Survey Geographic (SSURGO) Database, the USGS National Map, the USGS Mineral Resources Online Data, and the National Weather Service. The methodology used to gather information specifically from the SSURGO database is highlighted within this paper. Data from the SSURGO database is used to create the bedrock type, drainage class, and minimum soil depth to bedrock layers. A substantial benefit to this methodology is that the new technique can be adjusted to accommodate for sinkhole susceptibility in regions across the world, by simply adjusting the input risk layers to consider sinkhole risk potential based on the specific geology of a particular region.

 

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