4.7 Article

Landslide Material Control on Tsunami Genesis-The Storegga Slide and Tsunami (8,100Years BP)

期刊

JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
卷 124, 期 6, 页码 3607-3627

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1029/2018JC014893

关键词

tsunamis; landslide dynamics; soil material sensitivity

资金

  1. project TsunamiLand (TSUNAMIs induced by large LANDslides, Norwegian Research Council) [231252/F20]
  2. Norwegian Geotechnical Institute

向作者/读者索取更多资源

Tsunami generation from subaqueous landslides is controlled by landslide kinematics, which in turn is governed by the material properties of the slide mass. Yet the effect of the material properties on tsunami genesis is poorly understood. Geomorphological observations of landslide runout put constraints on the landslide dynamics. In addition, observations of tsunami runup heights can improve our understanding of how the landslide material transforms from initiation to final runout. The giant prehistoric Storegga Slide off the mid-Norwegian coast caused a well-documented ocean-wide tsunami that offers a unique setting for coupling landslide material models to tsunami generation models. In this study we simulate the dynamics of the Storegga Slide and tsunami using the depth-averaged landslide model BingClaw, which implements visco-plastic rheology and remolding, and couple it to a standard tsunami propagation model. A broad sensitivity study varying the landslide material strength parameters in BingClaw shows that the initial soil yield strength and remolding rate are most important for the tsunami genesis but that the residual strength determined the final runout distance. BingClaw parameters were further optimized to obtain the observed runout distance and to minimize the relative error of the tsunami runup heights. As detailed time-dependent three-dimensional representations of landslide parameters cannot be determined through a field investigation of the landslide itself, these simulations of the Storegga Slide and tsunami can help in the selection of plausible parameter ranges for prognostic modeling in quantitative hazard assessments.

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