Modeling coastal tsunami hazard from submarine mass failures: effect of slide rheology, experimental validation, and case studies off the US East Coast

Grilli, Stéphan T.; Shelby, Mike; Kimmoun, Olivier; Dupont, Guillaume; Nicolsky, Dmitry; Ma, Gangfeng; Kirby, James T.; Shi, Fengyan

doi:10.1007/s11069-016-2692-3

Cited by 81 publications

(111 citation statements)

References 99 publications

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“…This slump model was used to model the run-up due to the 1998 Papua New Guinea landslide (Synolakis et al 2002;Watts et al 2003;Tappin et al 2008), the prognostic modelling of future events (Grilli et al 2017) and as a complementary model of the 2011 Tohoku tsunami in combination with the co-seismic fault motion (Tappin et al 2014). The model consists of an elliptically shaped smooth block formed according to the function:…”

Section: Rotational Slump Sourcementioning

confidence: 99%

Modelling the 1929 Grand Banks slump and landslide tsunami

Løvholt

Schulten

Mosher

et al. 2018

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On 18 November 1929, an M w 7.2 earthquake occurred south of Newfoundland, displacing >100 km 3 of sediment volume that evolved into a turbidity current. The resulting tsunami was recorded across the Atlantic and caused fatalities in Newfoundland. This tsunami is attributed to sediment mass failure because no seafloor displacement due to the earthquake has been observed. No major headscarp, single evacuation area nor large mass transport deposit has been observed and it is still unclear how the tsunami was generated. There have been few previous attempts to model the tsunami and none of these match the observations. Recently acquired seismic reflection data suggest that rotational slumping of a thick sediment mass may have occurred, causing seafloor displacements up to 100 m in height. We used this new information to construct a tsunamigenic slump source and also carried out simulations assuming a translational landslide. The slump source produced sufficiently large waves to explain the high tsunami run-ups observed in Newfoundland and the translational landslide was needed to explain the long waves observed in the far field. However, more analysis is needed to derive a coherent model that more closely combines geological and geophysical observations with landslide and tsunami modelling.

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Section: Rotational Slump Sourcementioning

confidence: 99%

Modelling the 1929 Grand Banks slump and landslide tsunami

Løvholt

Schulten

Mosher

et al. 2018

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“…In the present paper, the aim is to propose a more realistic source prediction by calibrating the previous Navier-Stokes model with respect to recent experimental measurements of waves generated by granular slides. The experimental results considered are: Viroulet et al (2013) (see also 15 Viroulet et al (2014)) for subaerial slides and Grilli et al (2017) for submarine slides. Viroulet et al (2013) conducted a 2D physical experiment with glass beads in order to represent an equivalent granular slide.…”

Section: Methodsmentioning

confidence: 99%

“…The experiment presented in Grilli et al (2017) was also simulated using THETIS. The experiment consisted of 2 kg of 4 mm glass beads released underwater over a slope of 35 • in a water depth of 0.330 m. The slide was modeled as a Newtonian 10 fluid, first with parameters defined in Grilli et al (2017), i.e., a viscosity of 0.01 Pa·s and a density of 1951 kg·m −3 . A few…”

Section: Methodsmentioning

confidence: 99%

La Palma landslide tsunami: computation of the tsunami source with a calibrated multi-fluid Navier–Stokes model and wave impact assessment with propagation models of different types

Abadie¹,

Paris

Ata

et al. 2019

Preprint

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In this paper, we present a new source assessment of the La Palma collapse scenario previously described and studied in Abadie et al. (2012). Three scenarios (i.e., slide volumes of 20, 40 and 80 km 3 ) are considered, from the initiation of the slide to the water waves generation, using THETIS, a 3D Navier-Stokes model. The slide is considered as a Newtonian fluid whose viscosity is adjusted to approximate a granular behavior. After 5 minutes of propagation with THETIS, the generated water wave is transferred into FUNWAVE-TVD for 15 minutes of Boussinesq model simulation. Then, four different depth-averaged 5 codes are used to propagate the wave to the Guadeloupe area, Europe and French coasts. Finally, the wave impact in terms of run-up is evaluated through direct computations in specific areas or using theoretical formulas. Although the wave source appears reduced due to the rheology used compared to former works, the wave impact is still significant for the maximum slide volume considered on surrounding islands and coasts, as well as on remote most exposed coasts such as Guadeloupe. In Europe and in France, the wave impact is moderate (for specific areas in Spain and Portugal) to weak (Atlantic French coast). 10The comparison between the different wave models in overlapping computational regions shows an overall agreement in terms of first wave amplitude and time of arrival, but differences appear in the trailing waves.

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“…The simplest models assume a translational block or rotational slump (Bondevik et al, 2005;Grilli & Watts, 2005). Landslide flow models include viscous shallow-water type models (e.g., Fine et al, 2005), Coulomb-type friction or granular landslide models (e.g., Giachetti et al, 2011;Grilli et al, 2017;Kelfoun, 2011), or layered viscoplastic models including yield strength remolding. The latter may be used also to model retrogressive failure, which may be important for large clay-rich submarine landslides (Haugen et al, 2005;Løvholt et al, 2016, Løvholt, Pedersen, et al, 2015.…”

Section: /2017rg000579mentioning

confidence: 99%

Probabilistic Tsunami Hazard Analysis: Multiple Sources and Global Applications

Grezio

Babeyko²,

Baptista

et al. 2017

Reviews of Geophysics

198

165

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Applying probabilistic methods to infrequent but devastating natural events is intrinsically challenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluated because of the different causes generating tsunamis (earthquakes, landslides, volcanic activity, meteorological events, and asteroid impacts) with varying mean recurrence rates. Probabilistic Tsunami Hazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scales with the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhance knowledge of the potential tsunamigenic threat by estimating the probability of exceeding specific levels of tsunami intensity metrics (e.g., run‐up or maximum inundation heights) within a certain period of time (exposure time) at given locations (target sites); these estimates can be summarized in hazard maps or hazard curves. This discussion presents a broad overview of PTHA, including (i) sources and mechanisms of tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generation mechanisms, (ii) developments in modeling the propagation and impact of tsunami waves, and (iii) statistical procedures for tsunami hazard estimates that include the associated epistemic and aleatoric uncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of the rapid development of PTHA methods during the last decade and the globally distributed applications, including the importance of considering multiple sources, their relative intensities, probabilities of occurrence, and uncertainties in an integrated and consistent probabilistic framework.

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Modeling coastal tsunami hazard from submarine mass failures: effect of slide rheology, experimental validation, and case studies off the US East Coast

Cited by 81 publications

References 99 publications

Modelling the 1929 Grand Banks slump and landslide tsunami

Modelling the 1929 Grand Banks slump and landslide tsunami

La Palma landslide tsunami: computation of the tsunami source with a calibrated multi-fluid Navier–Stokes model and wave impact assessment with propagation models of different types

Probabilistic Tsunami Hazard Analysis: Multiple Sources and Global Applications

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