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Optimising Landslide-Tsunami Prediction Based on Physical Model Tests

Author(s): Valentin Heller; Johannes Spinneken

Linked Author(s): Valentin Heller

Keywords: No Keywords

Abstract: Subaerial landslide-tsunamis and impulse waves are generated by mass movements such as landslides, rock falls or glacier calving. To predict landslide-tsunamis (impulse waves) a number of empirical formulae have been proposed. Unfortunately, if they are applied to the 1958Lituya Bay case, the prediction of the tsunami height or amplitude is varying by up to a factor of five. At first sight the experimental conditions under which the various formulae were devised appear to be very similar. However subtle differences in the experimental set-up may lead to considerable deviations in the empirical predictions. To address this shortcoming, a comparative experimental study is presented. This study focuses on block model experiments being undertaken in a wave flume. The overall test programme concerns the investigation of three commonly ignored block model parameters: (i) the blockage ratio, (ii) the slide front angle and (iii) the transition at the slope toe. A systematical parameter variation is on-going. Herein, the experimental set-up, the repeatability and initial results based on the variation of (i) and (ii) are presented. Results from repeated tests suggest that the methodology applied herein is highly repeatable, considering that landslide-tsunami prediction is associated with a considerable uncertainty. One test for each parameter configuration was therefore regarded as sufficient. Both test parameters (i) and (ii) above were found to significantly affect the wave features: the relative wave amplitudes vary up to 37% due to (i) and up to 76% due to (ii). Those results help not only decreasing the discrepancies between landslide-tsunami predictions based on different empirical equations, but are also the first step in filling an important gap: to consider the effect of the slide type (block versus granular model slide) in generic predictive formulae. This will directly aid in predicting the effects of landslidetsunamis (impulse waves) with higher reliability.


Year: 2012

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