Data to support modeling of the 2015 Tyndall Glacier landslide, Alaska
Dates
Publication Date
2017-09-25
Citation
Cannon, C.M., 2017, Data to support modeling of the 2015 Tyndall Glacier landslide, Alaska: U.S. Geological Survey data release, https://doi.org/10.5066/F73R0RR3.
Summary
Landslide-generated tsunamis pose significant hazards, but developing models to assess these hazards presents unique challenges. George and others (2017) present a new methodology in which a depth-averaged two-phase landslide model (D-Claw) is used to simulate all stages of landslide dynamics and subsequent tsunami generation, propagation, and inundation. Because the model describes the evolution of solid and fluid volume fractions, it treats both landslides and tsunamis as special cases of a more general class of phenomena. Therefore, the landslide and tsunami can be seamlessly and efficiently simulated as a single-layer continuum with evolving solid-grain concentrations, and with wave generation via mass displacement and direct longitudinal [...]
Summary
Landslide-generated tsunamis pose significant hazards, but developing models to assess these hazards presents unique challenges. George and others (2017) present a new methodology in which a depth-averaged two-phase landslide model (D-Claw) is used to simulate all stages of landslide dynamics and subsequent tsunami generation, propagation, and inundation. Because the model describes the evolution of solid and fluid volume fractions, it treats both landslides and tsunamis as special cases of a more general class of phenomena. Therefore, the landslide and tsunami can be seamlessly and efficiently simulated as a single-layer continuum with evolving solid-grain concentrations, and with wave generation via mass displacement and direct longitudinal momentum transfer: dominant physical mechanisms that are unresolved with traditional modeling approaches. To test their methodology, George and others (2017) used D-Claw to model a large subaerial landslide and resulting tsunami that occurred on October, 17, 2015, in Taan Fiord near the terminus of Tyndall Glacier, Alaska. Modeled shoreline inundation patterns compare well with observations derived from satellite imagery. This data release contains topographic datasets used to model the landslide and a Normalized difference vegetation index (NDVI) change image used to assess the model results. These data are intended to accompany the journal article by George and others (2017): George, D.L., Iverson, R.M., and Cannon, C.M., 2017, New methodology for computing tsunami generation by subaerial landslides: application to the 2015 Tyndall Glacier Landslide, Alaska, Geophysical Research Letters, 44, doi:10.1002/2017GL074341.
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Type: Citation
George, D.L., Iverson, R.M., and Cannon, C.M., 2017, New methodology for computing tsunami generation by subaerial landslides: application to the 2015 Tyndall Glacier Landslide, Alaska, Geophysical Research Letters, 44, doi:10.1002/2017GL074341
Data in this release are intended to support analysis of a landslide that occurred near the terminus of Tyndall Glacier on October 17, 2015 and generated a tsunami in Taan Fiord, an arm of Icy Bay, Alaska. "Terrain model for Icy Bay, Alaska” is a digital terrain model of the Icy Bay, Alaska region compiled from Interferometric Synthetic Aperture Radar (IFSAR) topography merged with bathymetry interpolated from various hydrographic surveys. “Terrain model for Icy Bay, Alaska with slip surface for 2015 landslide” is a version of the digital terrain model with elevations in the landslide source area replaced by inferred elevations of the surface on which the landslide moved (slip surface). “NDVI change for Icy Bay, Alaska from May 2015 to May 2016” represents changes in Normalized difference vegetation index (NDVI) and was used to assess changes in vegetation patterns resulting from the landslide and tsunami for comparison with model results.
