Characterization of large tsunamigenic landslides and their effects using digital surface models: A case study from Taan Fiord, Alaska

On 17 October 2015, a large landslide entered the marine waters of Taan Fiord, Alaska, and generated a displacement wave with a 193 m runup. The wave scoured the surrounding hillslopes of soil and vegetation and deposited significant volumes of material into the fjord, onto hillslopes on the opposite side of the fjord, and on top of Tyndall Glacier. For this study, we generated six, 2-m posting Digital Surface Models (DSMs) using DigitalGlobe/Maxar satellite imagery acquired near-annually between 2012 and 2019, and the Surface Extraction with TIN-based Search-space Minimization (SETSM) high-performance computing algorithm. We aligned the DSMs to exposed bedrock in the 01 March 2014 DSM acquisition, and then used them to characterize topographic and volumetric changes from before and after the 2015 Taan Fiord rock avalanche. We find that the landslide mobilized roughly 77. 0 ± 0.9 Mm3 of material, of which approximately 56.3 Mm3 were deposited in the fjord waters. Furthermore, we quantified an additional 27.2 ± 3.8 Mm3 of material scoured from fjord-adjacent hillslopes and deposited in the fjord waters, providing new constraints on the subaqueous deposition. This is the first time that DSMs have been used to estimate the volume of scour caused by a tsunami and the subsequent changes in extent and volume with time. Our results for the landslide and runout are consistent with field measurements published previously. This study offers improved estimates of both subaerial and subaqueous deposition for the 2015 Taan Fiord landslide and describes additional regional environmental conditions. We identify precursory motion prior to the 2015 landslide, characterize several smaller-scale landslides in the larger Taan Fiord region, delineate terminus positions and associated ice dynamics of the Tyndall Glacier, and detail seasonal changes in vegetation growth and snow melt/accumulation. This work provides important new insights into the geomorphic features and dynamics of this landslide and subsequent tsunami. The interdisciplinary applications associated with DSMs and the accuracy of the measurements presented here demonstrate that these methods are an effective tool to improve our understanding of the pre- and post-landslide processes, for monitoring areas at risk for landslides and other natural hazards, and for rapid response to catastrophic events.