A revised tsunami source model for the 1707 Hoei earthquake and simulation of tsunami inundation of Ryujin Lake, Kyushu, Japan

We report results of field surveys and numerical modeling of the tsunami generated by the Anak Krakatau volcano eruption on 22 December 2018. We conducted two sets of field surveys of the coastal areas destroyed by the Anak Krakatau tsunami in 26-30 December 2018 and 4-10 January 2020. Field surveys provided information about the maximum tsunami height as well as the most damaged area. The maximum tsunami height was up to 13 m. Most locations registered a wave height of 3-4 m. Tsunami inundation was limited to approximately 100 m. For modeling, we considered 12 source models and conducted numerical modeling. The scenarios have source dimensions of 1.5&#8211;4&#8239;km and initial tsunami amplitudes of 10&#8211;200&#8239;m. By comparing observed and simulated waveforms, we constrained the tsunami source dimension and initial amplitude in the ranges of 1.5&#8211;2.5&#8239;km and 100&#8211;150&#8239;m, respectively. The best source model involves potential energy of 7.14&#8239;&#215;&#8239;1013&#8211;1.05&#8239;&#215;&#8239;1014&#8239;J which is equivalent to an earthquake of magnitude 6.0&#8211;6.1.

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Tsunami Inundation Mapping in Lima, for Two Tsunami Source Scenarios

Journal of Disaster Research ◽

10.20965/jdr.2013.p0274 ◽

2013 ◽

Vol 8 (2) ◽

pp. 274-284 ◽

Cited By ~ 11

Author(s):

Bruno Adriano ◽

◽

Erick Mas ◽

Shunichi Koshimura ◽

Yushiro Fujii ◽

...

Keyword(s):

Numerical Modeling ◽

Remote Sensing Data ◽

Source Model ◽

Disaster Mitigation ◽

Tsunami Source ◽

Tsunami Inundation ◽

Maximum Extension ◽

Tsunami Disaster ◽

Inundation Mapping ◽

Runup Height

Within the framework of the project Enhancement of Earthquake and Tsunami Disaster Mitigation Technology in Peru (JST-JICA SATREPS), this study determines tsunami inundation mapping for the coastal area of Lima city, based on numerical modeling and two different tsunami seismic scenarios. Additionally, remote sensing data and geographic information system (GIS) analysis are incorporated in order to improve the accuracy of numerical modeling results. Moreover, tsunami impact is evaluated through application of a tsunami casualty index (TCI) using tsunami modeling results. Numerical results, in terms of maximum tsunami depth, show a maximum inundation height of 6 m and 15.8 m for a potential scenario (first source model) and for a past scenario (second source model), respectively. In terms of inundation area, the maximum extension is 1.3 km with a runup height of 5.3 m for the first scenario. The maximum extension is 2.1 km with a runup height of 11.4 m for the second scenario. The average TCI value obtained for the first scenario is 0.36 for the whole inundation domain. The second scenario gives a mean value of 0.64, where TCI equal to 1.00 represents the highest condition of risk. The results presented in this paper provide important information about understanding tsunami inundation features and, consequently, may be useful in designing an adequate tsunami evacuation plan for Lima city.

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On the landslide tsunami uncertainty and hazard

Landslides ◽

10.1007/s10346-020-01429-z ◽

2020 ◽

Vol 17 (10) ◽

pp. 2301-2315 ◽

Cited By ~ 1

Author(s):

Finn Løvholt ◽

Sylfest Glimsdal ◽

Carl B. Harbitz

Keyword(s):

Hazard Analysis ◽

Tsunami Hazard ◽

Tsunami Source ◽

Probabilistic Framework ◽

Tsunami Inundation ◽

Event Trees ◽

To Come ◽

Probabilistic Tsunami Hazard Analysis ◽

Landslide Tsunami ◽

Prognostic Modelling

Abstract Landslides are the second most frequent tsunami source worldwide. However, their complex and diverse nature of origin combined with their infrequent event records make prognostic modelling challenging. In this paper, we present a probabilistic framework for analysing uncertainties emerging from the landslide source process. This probabilistic framework employs event trees and is used to conduct tsunami uncertainty analysis as well as probabilistic tsunami hazard analysis (PTHA). An example study is presented for the Lyngen fjord in Norway. This application uses a mix of empirical landslide data combined with expert judgement to come up with probability maps for tsunami inundation. Based on this study, it is concluded that the present landslide tsunami hazard analysis is largely driven by epistemic uncertainties. These epistemic uncertainties can be incorporated in the probabilistic framework. Conducting a literature analysis, we further show examples of how landslide and tsunami data can be used to better constrain landslide uncertainties, combined with statistical and numerical analysis methods. We discuss how these methods, combined with the probabilistic framework, can be used to improve landslide tsunami hazard analysis in the future.

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Probabilistic Tsunami Hazard Analysis: High Performance Computing for Massive Scale Monte Carlo type Inundation Simulations

10.5194/egusphere-egu2020-8041 ◽

2020 ◽

Author(s):

Steven J. Gibbons ◽

Manuel J. Castro Díaz ◽

Sylfest Glimsdal ◽

Carl Bonnevie Harbitz ◽

Maria Concetta Lorenzino ◽

...

Keyword(s):

High Performance Computing ◽

High Performance ◽

Hazard Analysis ◽

Tsunami Hazard ◽

Propagation Model ◽

Tsunami Source ◽

Tsunami Inundation ◽

Center Of Excellence ◽

Probabilistic Tsunami Hazard Analysis ◽

Performance Computing

Probabilistic Tsunami Hazard Analysis (PTHA) is an approach to quantifying the likelihood of exceeding a specified metric of tsunami inundation at a given location within a given time interval. It provides scientific guidance for decision making regarding coastal engineering and evacuation planning. PTHA requires a discretization of many potential tsunami source scenarios and an evaluation of the probability of each scenario. The classical approach of PTHA has been the quantification of the tsunami hazard offshore, while estimates of the inundation at a given coastal site have been limited to a few scenarios. PTHA, with an adequate discretization of source scenarios, combined with high-resolution inundation modelling, has been out of reach with existing models and computing capabilities with tens to hundreds of thousands of moderately intensive numerical simulations being required. In recent years, more efficient GPU-based High Performance Computing (HPC) facilities, together with efficient GPU-optimized shallow water type models for simulating tsunami inundation, have made a regional and local long-term hazard assessment feasible. PTHA is one of the so-called Pilot Demonstrators of the EC-funded ChEESE project (Center of Excellence for Exascale Computing in the Solid Earth) where a workflow has been developed with three main stages: source specification and discretization, efficient numerical inundation simulation for each scenario using the HySEA numerical tsunami propagation model, and hazard aggregation. HySEA calculates tsunami offshore propagation and inundation using a system of telescopic topo-bathymetric grids. In this presentation, we illustrate the workflows of the PTHA as implemented for HPC applications, including preliminary simulations carried out on intermediate scale GPU clusters. Finally, we delineate how planned upscaling to exascale applications can significantly increase the accuracy of local tsunami hazard analysis.This work is partially funded by the European Union&#8217;s Horizon 2020 Research and Innovation Program under grant agreement No 823844 (ChEESE Center of Excellence, www.cheese-coe.eu).

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Numerical Simulation of Tsunami Run-Up and Inundation for the 2011 Tōhuku-Oki Tsunami: A Parametric Analysis for Tsunami Run-Up and Wave Height

Volume 8A: Ocean Engineering ◽

10.1115/omae2014-23138 ◽

2014 ◽

Author(s):

Debashis Basu ◽

Robert Sewell ◽

Kaushik Das ◽

Ron Janetzke ◽

Biswajit Dasgupta ◽

...

Keyword(s):

Wave Propagation ◽

Wave Height ◽

Seismic Waves ◽

Source Model ◽

Tsunami Source ◽

Computational Framework ◽

Wave Amplification ◽

Source Models ◽

Run Up ◽

Tsunami Run Up

This paper presents computational results for predicting earthquake-generated tsunami from a developed integrated computational framework. The computational framework encompasses the entire spectrum of modeling the earthquake-generated tsunami source, open-sea wave propagation, and wave run-up including inundation and on-shore effects. The present work develops a simplified source model based on pertinent local geologic and tectonic processes, observed seismic data (i.e., data obtained by inversion of seismic waves from seismographic measurements), and geodetic data (i.e., directly measured seafloor and land deformations). These source models estimated configurations of seafloor deformation used as initial waveforms in tsunami simulations. Together with sufficiently accurate and resolved bathymetric and topographic data, they provided the inputs needed to numerically simulate tsunami wave propagation, inundation and coastal impact. The present work systematically analyzes the effect of the tsunami source model on predicted tsunami behavior and the associated variability for the 2011 Tōhuku-Oki tsunami. Simulations were carried out for the 2011 Tōhuku -Oki Tsunami that took place on March 11, 2011, from an MW 9.1 earthquake. The numerical simulations were performed using the fully nonlinear Boussinesq hydrodynamics code, FUNWAVE-TVD (distributed by the University of Delaware). In addition, a sensitivity analysis was also carried out to study the effect of earthquake magnitude on the predicted wave height. The effect of coastal structure on the wave amplification at the shore is also studied. Simulated tsunami results for wave heights are compared to the available observational data from GPS (Global Positioning System) at the central Miyagi location.

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