Validation and inter-comparison of models for landslide tsunami generation

Kirby, James T.; Grilli, Stéphan T.; Horrillo, Juan; Liu, Philip L.‐F.; Nicolsky, Dmitry; Abadie, Stéphane; Ataie-Ashtiani, Behzad; Castro, Manuel J.; Clous, Lucie; Escalante, Cipriano; Fine, Isaac V.; Vida, José Manuel González; Løvholt, Finn; Lynett, Patrick; Ma, Gangfeng; Macías, Jorge; Ortega-Acosta, S.; Shi, Fengyan; Yavari-Ramshe, S.; Zhang, Cheng

doi:10.1016/j.ocemod.2021.101943

Cited by 28 publications

(9 citation statements)

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“…For instance, we do not take into account material heterogeneity, segregation and fragmentation processes, bed erosion and incorporation of air and/or water, or density variations that can be caused by the expansion or contraction of the material and their impact on pore fluid pressure [see Delannay et al, 2017 for a review of processes]. HySEA was developed by the EDANYA group [Asunción-Hernández et al, 2012, Asunción et al, 2013, Castro Díaz et al, 2005, 2006, 2008a,b, Macías et al, 2015 and has been successfully used to simulate tsunamis generated by landslides [Kirby et al, 2022 (for a benchmarking exercise); Macías et al, 2021, Esposti Ongaro et al, 2021. From the depth-averaged equations, six unknowns are solved by the model, (h 1 , u 1x , u 1y ) and (h 2 , u 2x , u 2y ), representing the vertical height and horizontal velocity of the fluid (index 1) and granular layer (index 2), respectively, averaged in the vertical direction.…”

Section: Hyseamentioning

confidence: 99%

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Numerical simulation of submarine landslides and generated tsunamis: application to the on-going Mayotte seismo-volcanic crisis

Poulain¹,

Friant²,

Pedreros³

et al. 2023

Comptes Rendus. Géoscience

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Section: Hyseamentioning

confidence: 99%

“…Kirby et al, 2013, Popinet, 2015, Zhou et al, 2011 are available. In particular, these non-hydrostatic models are necessary at least to accurately simulate tsunami wavelengths of about the same order of magnitude as the wa-ter depth [Gylfadóttir et al, 2017, Kirby et al, 2022Yavari-Ramshe and Ataie-Ashtiani, 2016].…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of submarine landslides and generated tsunamis: application to the on-going Mayotte seismo-volcanic crisis

Poulain¹,

Friant²,

Pedreros³

et al. 2023

Comptes Rendus. Géoscience

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“…In recent years, the interest on landslide tsunamis has been boosted through a series of works providing new insights on their peculiar characteristics (Heller et al 2016;Evers et al 2019;Heidarzadeh et al 2020;Løvholt et al 2020;Snelling et al 2020;Ruffini et al 2021;Iorio et al 2021). Comprehensive reviews of the approaches adopted for simulating landslide motion and water interactions, as well as available numerical techniques, can be found in Heidarzadeh et al (2014), Yavari-Ramshe and Ataie-Ashtiani (2016), and in Kirby et al (2022) which compares different codes applied to benchmarks with real case.…”

Section: Original Papermentioning

confidence: 99%

Tsunami potential source in the eastern Sea of Marmara (NW Turkey), along the North Anatolian Fault system

et al. 2022

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Based on morphobathymetric and seismic reflection data, we studied a large landslide body from the eastern Sea of Marmara (NW Turkey), along the main strand of the North Anatolian Fault, one of the most seismically active geological structures on Earth. Due to its location and dimensions, the sliding body may cause tsunamis in case of failure possibly induced by an earthquake. This could affect heavily the coasts of the Sea of Marmara and the densely populated Istanbul Metropolitan area, with its exposed cultural heritage assets. After a geological and geometrical description of the landslide, thanks to high-resolution marine geophysical data, we simulated numerically possible effects of its massive mobilization along a basal displacement surface. Results, within significant uncertainties linked to dimensions and kinematics of the sliding mass, suggest generation of tsunamis exceeding 15–20 m along a broad coastal sector of the eastern Sea of Marmara. Although creeping processes or partial collapse of the landslide body could lower the associated tsunami risk, its detection stresses the need for collecting more marine geological/geophysical data in the region to better constrain hazards and feasibility of specific emergency plans.

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“…Landslide-generated tsunamis have been benchmarked. At the laboratory scale, benchmarking mainly focused on comparison between simulated and recorded water waves on gauges (Kirby et al 2022). Indeed, experimental data rarely provide both the detailed time evolution of the granular mass and the water waves.…”

Section: E X P E R I M E N Ta L Datamentioning

confidence: 99%

“…Indeed, wave dispersion can be significant (Glimsdal et al 2013;Ma et al 2015) when the water wavelength is smaller than or about the same order of magnitude as the water depth (Yavari-Ramshe & Ataie-Ashtiani 2016). For more than two decades, more advanced depth-averaged models to describe water wave propagation have been developed based on Boussinesq-type equations (non-hydrostatic pressure), that are weakly or fully dispersive (Kirby et al 1998;Zhou et al 2011;Shi et al 2012;Popinet 2015;Kirby et al 2022), as is the case for the HySEA model (Macias et al 2021b). Such depth-averaged non-hydrostatic models are also valid only for a sufficiently small ratio of the water depth to the tsunami wavelength, a limitation inadequately discussed in the literature (Macias et al 2021a).…”

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confidence: 99%

Performance and limits of a shallow-water model for landslide-generated tsunamis: from laboratory experiments to simulations of flank collapses at Montagne Pelée (Martinique)

Poulain

Friant

Mangeney

et al. 2022

Geophysical Journal International

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Summary We investigate the dynamics and deposits of granular flows and the amplitude of landslide-generated water waves using the HySEA depth-averaged shallow-water numerical model, both at laboratory and field scales. We evaluate the different sources of error by quantitatively comparing the simulations with (i) new laboratory experiments of granular collapses in different conditions (dry, immersed, dry flow entering water) and slope angles and (ii) numerical simulations made with the SHALTOP code that describes topography effects better than most depth-averaged landslide-tsunami models. For laboratory configurations, representing the limits of the shallow-water approximation in such models, we show that topography and non-hydrostatic effects are crucial. When topography effects are accounted for empirically—by artificially increasing the friction coefficient and performing non-hydrostatic simulations—the model is able to reproduce the granular mass deposit and the waves recorded at gauges located at a distance of more than 2–3 times the characteristic dimension of the slide with an error ranging from 1 per cent to 25 per cent depending on the scenario, without any further calibration. Taking into account this error estimate, we simulate landslides that occurred on Montagne Pelée volcano, Martinique, Lesser Antilles as well as the generated waves. Multiple collapse simulations support the assumption that large flank collapses on Montagne Pelée likely occurred in several successive sub-events. This result has a strong impact on the amplitude of the generated waves and thus on the associated hazards. In the context of the ongoing seismic volcanic unrest at Montagne Pelée volcano, we calculate the debris avalanche and associated tsunamis for two potential flank-collapse scenarios.

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Validation and inter-comparison of models for landslide tsunami generation

Cited by 28 publications

References 100 publications

Numerical simulation of submarine landslides and generated tsunamis: application to the on-going Mayotte seismo-volcanic crisis

Numerical simulation of submarine landslides and generated tsunamis: application to the on-going Mayotte seismo-volcanic crisis

Tsunami potential source in the eastern Sea of Marmara (NW Turkey), along the North Anatolian Fault system

Performance and limits of a shallow-water model for landslide-generated tsunamis: from laboratory experiments to simulations of flank collapses at Montagne Pelée (Martinique)

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