GSA Connects 2022 meeting in Denver, Colorado

Paper No. 20-6
Presentation Time: 9:00 AM-1:00 PM

REMOTE MAPPING AND MORPHOMETRIC ANALYSIS OF LARGE-SCALE LANDSLIDES IN NORTHERN AND CENTRAL NEVADA, USA


DOYLE, Mason, Department of Geology, University of Cincinnati, Cincinnati, OH 45221, SHEEHAN, Christopher, Boston College, Department of Earth and Environmental Sciences, Devlin Hall 213, 140 Commonwealth Avenue, Chestnut Hill, MA 02467 and STURMER, Daniel, Department of Geology, University of Cincinnati, PO Box 210013, Cincinnati, OH 45221-0013

Landslide events weave catastrophe in their wake, destroying mountainsides and pulverizing hillsides into breccia. The evidence of a recent landslide is obvious, including a fresh, steep headwall scarp, hummocky, chaotic deposit, and damage to any infrastructure present. However, these indicators disappear over time for ancient landslide events as scarps and hummocky deposits erode and are covered by vegetation. Evidence of these events may fade in the field, but remote sensing techniques may be able to detect more subtle patterns of eroded ancient landslides. Therefore the goal of this study is to analyze the evolution and modification of known large-scale landslide deposits and scarps through time to identify critical morphometric features that differentiate ancient landslide deposits and scarps.

We used a combination of published geologic maps, Google Earth, QGIS, and MATLAB to evaluate morphometric characteristics of known landslide deposits and headwall scarps from several mountain ranges in northern and central Nevada. We focused on previously mapped landslide deposits that cover >1km2. The landslides range in age from Oligocene to Quaternary, incorporating a wide variety of lithologies. The landslides occurred in several geomorphic and tectonic provinces, including the Basin and Range, Walker Lane, and basalt plateaus.

Each analysis began with mapping landslide deposits and headwalls in Google Earth based on published mapping from the USGS and Nevada Bureau of Mines and Geology identifying the landslide deposits. The deposit and scarp polygons were transferred to QGIS and used to clip polygons from10 m DEMs for further analysis. Drainage basins were also mapped on 10 m DEMs for each range analyzed. Geomorphic parameters, including slope, curvature, and roughness, were then analyzed comparing the landslide deposits and headwall scarps to the drainage basins. Analysis is on-going but ultimately these analyses will lead to improved understanding of how morphology of landslide deposits and scarps is modified and preserved through geologic time.