scholarly journals A Universal Parameter to Predict Subaerial Landslide Tsunamis?

2014 ◽  
Vol 2 (2) ◽  
pp. 400-412 ◽  
Author(s):  
Valentin Heller ◽  
Willi Hager
Keyword(s):  
Subaerial Landslide ◽  
Landslide Tsunamis

Landslide tsunamis, from origin to hazard, an overview from the SLATE project

2021 ◽  
Author(s):  
Finn Løvholt ◽  
Matthias Rauter ◽  
Thomas Zengaffinen-Morris ◽  
Carl Harbitz
Keyword(s):  
Numerical Models ◽  
Hazard Analysis ◽  
Navier Stokes ◽  
Tsunami Height ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Research Activities ◽  
Subaerial Landslide ◽  
Landslide Dynamics ◽  
Landslide Tsunamis

<p>Landslide tsunamis, despite their importance for the overall tsunami hazard, is not as well understood as earthquake tsunamis. Several uncertain factors contribute to the lack of understanding, such as the variability in the source mechanisms, the dynamics of the landslide and the tsunami generation, as well as the temporal probability of occurrence of landslide events. Here, we present an overview of research activities on landslide tsunami analyses in the H2020 ITN-SLATE project. This research originates from two PhD student projects within SLATE, which have so far resulted in at least six publications with several more in the pipeline. In the SLATE project, we show that both translational and rotational dynamic attributes of the landslide are good indicators of the tsunamigenic potential of slumps using the visco-plastic landslide model BingClaw, by correlating the acceleration times mass and also angular momentum with the induced tsunami height. Moreover, we have employed Navier-Stokes simulations to hindcast model experiments of subaerial landslide tsunamis. By using the experience modelling this benchmark to model tsunamis in many other geometrical settings, the Navier-Stokes model is further employed to test generality and discuss several existing parametric relationships from literature so far available only empirically. New 3D formulations for granular landslide dynamics have further been established. Numerical models have also been set up to simulate real cases such as Anak Krakatoa. Finally, a broad parametric study that constrain the landslide dynamics for a landslide probabilistic hazard analysis is undertaken, to show how using past observations can effectively reduce uncertainties related to landslide dynamics. Combining an overview of the study with some highlights, we show how SLATE has contributed to increasing our understanding of landslide tsunamis and their hazard. We also discuss how the outcome of this project provides a platform for further research. This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 721403.</p>

scholarly journals On the characteristics of landslide tsunamis

2015 ◽  
Vol 373 (2053) ◽  
pp. 20140376 ◽  
Author(s):  
F. Løvholt ◽  
G. Pedersen ◽  
C. B. Harbitz ◽  
S. Glimsdal ◽  
J. Kim
Keyword(s):  
Laboratory Experiments ◽  
Tsunami Generation ◽  
Long Run ◽  
Subaerial Landslide ◽  
Modelling Techniques ◽  
Landslide Deformation ◽  
Landslide Tsunami ◽  
Weak Influence ◽  
Positive Interference ◽  
Landslide Tsunamis

This review presents modelling techniques and processes that govern landslide tsunami generation, with emphasis on tsunamis induced by fully submerged landslides. The analysis focuses on a set of representative examples in simplified geometries demonstrating the main kinematic landslide parameters influencing initial tsunami amplitudes and wavelengths. Scaling relations from laboratory experiments for subaerial landslide tsunamis are also briefly reviewed. It is found that the landslide acceleration determines the initial tsunami elevation for translational landslides, while the landslide velocity is more important for impulsive events such as rapid slumps and subaerial landslides. Retrogressive effects stretch the tsunami, and in certain cases produce enlarged amplitudes due to positive interference. In an example involving a deformable landslide, it is found that the landslide deformation has only a weak influence on tsunamigenesis. However, more research is needed to determine how landslide flow processes that involve strong deformation and long run-out determine tsunami generation.

Submarine Landslides and Their Tsunami Hazard

2016 ◽  
Vol 49 (1) ◽  
Author(s):  
David R. Tappin
Keyword(s):  
Papua New Guinea ◽  
New Guinea ◽  
Submarine Landslide ◽  
Tsunami Hazard ◽  
Publication Date ◽  
Submarine Landslides ◽  
Critical Importance ◽  
Grand Banks ◽  
Landslide Mechanisms ◽  
Landslide Tsunamis

Most tsunamis are generated by earthquakes, but in 1998, a seabed slump offshore of northern Papua New Guinea (PNG) generated a tsunami up to 15 m high that killed more than 2,200 people. The event changed our understanding of tsunami mechanisms and was forerunner to two decades of major tsunamis that included those in Turkey, the Indian Ocean, Japan, and Sulawesi and Anak Krakatau in Indonesia. PNG provided a context to better understand these tsunamis as well as older submarine landslide events, such as Storegga (8150 BP); Alika 2 in Hawaii (120,000 BP), and Grand Banks, Canada (1929), together with those from dual earthquake/landslide mechanisms, such as Messina (1908), Puerto Rico (1928), and Japan (2011). PNG proved that submarine landslides generate devastating tsunamis from failure mechanisms that can be very different, whether singly or in combination with earthquakes. It demonstrated the critical importance of seabed mapping to identify these mechanisms as well as stimulated the development of new numerical tsunami modeling methodologies. In combination with other recent tsunamis, PNG demonstrated the critical importance of these events in advancing our understanding of tsunami hazard and risk. This review recounts how, since 1998, understanding of the tsunami hazard from submarine landslides has progressed far beyond anything considered possible at that time. ▪ For submarine landslide tsunamis, advances in understanding take place incrementally, usually in response to major, sometimes catastrophic, events. ▪ The Papua New Guinea tsunami in 1998, when more than 2,200 people perished, was a turning point in first recognizing the significant tsunami hazard from submarine landslides. ▪ Over the past 2 to 3 years advances have also been made mainly because of improvements in numerical modeling based on older tsunamis such as Grand Banks in 1929, Messina in 1908, and Storegga at 8150 BP. ▪ Two recent tsunamis in late 2018, in Sulawesi and Anak Krakatau, Indonesia, where several hundred people died, were from very unusual landslide mechanisms—dual (strike-slip and landslide) and volcanic collapse—and provide new motivations for understanding these tsunami mechanisms. ▪ This is a timely, state of the art review of landslide tsunamis based on recent well-studied events and new research on older ones, which provide an important context for the recent tsunamis in Indonesia in 2018. Expected final online publication date for the Annual Review of Earth and Planetary Sciences, Volume 49 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Landslide tsunamis: Comparison between depth-averaged and Navier–Stokes models

2021 ◽  
pp. 104022
Author(s):  
Alexandre Paris ◽  
Philippe Heinrich ◽  
Stéphane Abadie
Keyword(s):  
Navier Stokes ◽  
Landslide Tsunamis

Landslide Tsunamis: Recent Findings and Research Directions

2003 ◽  
Vol 160 (10-11) ◽  
pp. 1793-1809 ◽  
Author(s):  
J.-P. Bardet ◽  
C. E. Synolakis ◽  
H. L. Davies ◽  
F. Imamura ◽  
E. A. Okal
Keyword(s):  
Research Directions ◽  
Landslide Tsunamis

scholarly journals Reciprocal Green's functions and the quick forecast of submarine landslide tsunamis

2020 ◽  
Vol 20 (3) ◽  
pp. 771-781 ◽  
Author(s):  
Guan-Yu Chen ◽  
Chin-Chih Liu ◽  
Janaka J. Wijetunge ◽  
Yi-Fung Wang
Keyword(s):  
Green's Functions ◽  
Green’S Functions ◽  
Submarine Landslide ◽  
Tsunami Source ◽  
Submarine Earthquakes ◽  
Temporal Derivative ◽  
Submarine Mass Failure ◽  
Tsunami Waveform ◽  
Tsunami Scenarios ◽  
Landslide Tsunamis

Abstract. Although tsunamis generated by submarine mass failure are not as common as those induced by submarine earthquakes, sometimes the generated tsunamis are higher than a seismic tsunami in the area close to the tsunami source, and the forecast is much more difficult. In the present study, reciprocal Green's functions (RGFs) are proposed as a useful tool in the forecast of submarine landslide tsunamis. The forcing in the continuity equation due to depth change in a landslide is represented by the temporal derivative of the water depth. After a convolution with reciprocal Green's function, the tsunami waveform can be obtained promptly. Thus, various tsunami scenarios can be considered once a submarine landslide happens, and a useful forecast can be formulated. When a submarine landslide occurs, the various possibilities for tsunami generation can be analyzed and a useful forecast can be devised.

scholarly journals Modeling the Slump-Type Landslide Tsunamis Part I: Developing a Three-Dimensional Bingham-Type Landslide Model

2020 ◽  
Vol 10 (18) ◽  
pp. 6501 ◽  
Author(s):  
Tso-Ren Wu ◽  
Thi-Hong-Nhi Vuong ◽  
Chun-Wei Lin ◽  
Chun-Yu Wang ◽  
Chia-Ren Chu
Keyword(s):  
Strain Rate ◽  
Stokes Equations ◽  
Laboratory Data ◽  
Three Dimensional ◽  
Viscosity Model ◽  
Navier Stokes ◽  
Observation Data ◽  
Yield Strain ◽  
Slide Material ◽  
Landslide Tsunamis

This paper incorperates Bingham and bi-viscosity rheology models with the Navier–Stokes solver to simulate the dynamics and kinematics processes of slumps for tsunami generation. The rheology models are integrated into a computational fluid dynamics code, Splash3D, to solve the incompressible Navier–Stokes equations with volume of fluid surface tracking algorithm. The change between un-yield and yield phases of the slide material is controlled by the yield stress and yield strain rate in Bingham and bi-viscosity models, respectively. The integrated model is carefully validated by the theoretical results and laboratory data with good agreements. This validated model is then used to simulate the benchmark problem of the failure of the gypsum tailings dam in East Texas in 1966. The accuracy of predicted flood distances simulated by both models is about 73% of the observation data. To improve the prediction, a fixed large viscosity is introduced to describe the un-yield behavior of tailings material. The yield strain rate is obtained by comparing the simulated inundation boundary to the field data. This modified bi-viscosity model improves not only the accuracy of the spreading distance to about 97% but also the accuracy of the spreading width. The un-yield region in the modified bi-viscosity model is sturdier than that described in the Bingham model. However, once the tailing material yields, the material returns to the Bingham property. This model can be used to simulate landslide tsunamis.

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