GSA Annual Meeting in Phoenix, Arizona, USA - 2019

Paper No. 150-4
Presentation Time: 2:20 PM


CRAWFORD, Matthew M.1, KOCH, Hudson J.1, DORTCH, Jason M.2 and KILLEN, Ashton A.3, (1)Kentucky Geological Survey, University of Kentucky, 228 Mining and Mineral Resources Building, Lexington, KY 40506, (2)Kentucky Geological Survey, University of Kentucky, Lexington, KY 40506, (3)Department of Physics, Earth Science, and Space Systems Engineering, Morehead State University, 101 Space Science Center, Morehead State University, Morehead, KY 40351

We are developing methods for determining landslide susceptibility in eastern Kentucky as part of a multi-county risk assessment and reduction project. A map-based infinite slope analysis program, PISA-m, was used to probabilistically calculate stability, Prob [FS < 1], based on slope angle, geotechnical property (including pore water pressure), and land cover (root strength) maps. PISA-m uses probability distributions of parameters assigned to each geotechnical map unit to account for uncertainty in the available geotechnical data. A map of Prob [FS < 1] shows the time-independent probability of sliding, which we used as the basis for an associated susceptibility classification. Excluding areas of low slope, which we assume to have low susceptibility, the mean value of Prob [FS < 1] is 0.3 and approximately 10% of the county area is classified as moderate to high susceptibility. We developed an empirical slope morphology-based landslide susceptibility model for comparison with the physics-based probabilistic results. A GIS weighted sum tool calculates susceptibility values using similar information as the PISA-m model in addition to variables such as curvature and hillslope erosion potential. We are currently comparing results from the two methods to the locations of landslide features identified using LiDAR-derived slope angle, topographic contour, topographic curvature, and topographic roughness maps. We digitized 973 landslide extents and catalogued them in a GIS database using a confidence rating system based on the clarity of geomorphic features (scarps, flanks, toe bulges, and hummocky terrain). Of the mapped landslides, 56% were classified as high confidence and 40% as moderate confidence. Evaluating the mapped landslide feature locations relative to the susceptibility model maps will support a subsequent risk assessment and increase our understanding of landslide hazards in the area.