Landslides

Xu, Y., D.L. George, J.W. Kim, Z. Lu, M. Riley, T. Griffin, and J. de la Fuente (2022), Landslides, Technical Note, doi:10.1007/s10346-020-01533-0.
Abstract

The landslide complex at Gold Basin, Washington, has been drawing considerable attention after a catastrophic runout of the nearby landslide at Oso, Washington, in 2014. To evaluate potential threats of the Gold Basin landslide to the campground down the slope, remote sensing and numerical modeling were integrated to monitor recent landslide activity and simulate hypothetical runout scenarios. Bare-earth LiDAR DEM (digital elevation model) differencing, InSAR (Interferometric Synthetic Aperture Radar), and offset tracking of SAR images reveal that localized collapses at the headscarps have been the primary type of landslide activity at Gold Basin from 2005 to 2019, and currently no signs indicative of movement of a large centralized block or a deep-seated main body were detected. The maximum horizontal deformation rate is 5 m/year occurring primarily from headscarp recession of the middle lobe, and the annual landsliding volume of the whole landslide complex averages 1.03 × 105 m3. From threedimensional limit equilibrium analysis of generalized terrace structures, the maximum landslide volume is estimated as 2.0 × 106 m3. Simulations of hypothetical runout scenarios were carried out using the depth-averaged two-phase model D-claw with aboveobtained landslide geometry constraints. The simulation results demonstrate that debris flows with volume less than 105 m3 only pose limited threats to the campground, while volumes over 106 m3 could cause severe damages. Consequently, the estimated maximum landslide volume of 2.0 × 106 m3 suggests a potential risk to the campground nearby. Adaption of our methodology could prove useful for evaluating other similar landslides globally for hazards prevention and mitigation.

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Research Program
Interdisciplinary Science Program (IDS)
Funding Sources
NASA Interdisciplinary Research (IDS) in Earth Science Program (80NSSC17K0022)