Influence of timescales on the generation of seismic tsunamis

Gal, Marine Le; Violeau, Damien; Benoît, Michel

doi:10.1016/j.euromechflu.2017.03.008

Cited by 15 publications

(4 citation statements)

References 22 publications

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“…Tsunamigenic strength is primarily controlled by the fault dislocation (slip) and rupture areal extent (proportional to the seismic moment and hence linked to the magnitude), the geometry and the dynamics of the fault displacement, as well as the depth of the fault and the distance from the coast. Also, more complex features of the seismic source may have primary effects, like, for example, the spatial variability of dislocations (causing local slip concentrations) as well as spatiotemporal evolution of the seismic rupture, especially for large earthquakes featuring slow ruptures [159]. Seafloor deformation is modelled based on principles of continuum mechanics.…”

Section: Tsunami Generation Modelsmentioning

confidence: 99%

Tsunami risk management for crustal earthquakes and non-seismic sources in Italy

et al. 2021

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Destructive tsunamis are most often generated by large earthquakes occurring at subduction interfaces, but also other “atypical” sources—defined as crustal earthquakes and non-seismic sources altogether—may cause significant tsunami threats. Tsunamis may indeed be generated by different sources, such as earthquakes, submarine or coastal landslides, volcano-related phenomena, and atmospheric perturbations. The consideration of atypical sources is important worldwide, but it is especially prominent in complex tectonic settings such as the Mediterranean, the Caribbean, or the Indonesian archipelago. The recent disasters in Indonesia in 2018, caused by the Palu-Sulawesi magnitude Mw 7.5 crustal earthquake and by the collapse of the Anak-Krakatau volcano, recall the importance of such sources. Dealing with atypical sources represents a scientific, technical, and computational challenge, which depends on the capability of quantifying and managing uncertainty efficiently and of reducing it with accurate physical modelling. Here, we first introduce the general framework in which tsunami threats are treated, and then we review the current status and the expected future development of tsunami hazard quantifications and of the tsunami warning systems in Italy, with a specific focus on the treatment of atypical sources. In Italy, where the memory of historical atypical events like the 1908 Messina earthquake or the relatively recent 2002 Stromboli tsunami is still vivid, specific attention has been indeed dedicated to the progressive development of innovative strategies to deal with such atypical sources. More specifically, we review the (national) hazard analyses and their application for coastal planning, as well as the two operating tsunami warning systems: the national warning system for seismically generated tsunamis (SiAM), whose upstream component—the CAT-INGV—is also a Tsunami Service Provider of the North-eastern Atlantic, the Mediterranean and connected seas Tsunami Warning System (NEAMTWS) coordinated by the Intergovernmental Coordination Group established by the Intergovernmental Oceanographic Commission (IOC) of UNESCO, and the local warning system for tsunamis generated by volcanic slides along the Sciara del Fuoco of Stromboli volcano. Finally, we review the state of knowledge about other potential tsunami sources that may generate significant tsunamis for the Italian coasts, but that are not presently considered in existing tsunami warning systems. This may be considered the first step towards their inclusion in the national tsunami hazard and warning programs.

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Section: Tsunami Generation Modelsmentioning

confidence: 99%

Tsunami risk management for crustal earthquakes and non-seismic sources in Italy

et al. 2021

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“…Usually, uniform slip models are used for far-field scenarios because the seismic moment, source mechanism, and radiation pattern are more influential in tsunami amplitude (Geist & Parsons, 2006). On the contrary, the near-field requires a detailed consideration of the seismic source since complexities in slip distribution, crustal structure, and temporal evolution of the seafloor displacement can affect the tsunami amplitude (Le Gal et al, 2017). Even though this is rarely taken into account in tsunami hazard studies (Grezio et al, 2017;Li et al, 2016;Melgar et al, 2016;Sepulveda et al, 2019), in this work-focused on near-field tsunamis impact-we use non-uniform slip distribution to generate kinematic based deformation models.…”

Section: Synthetic Earthquake Catalogmentioning

confidence: 99%

Regional Probabilistic Tsunami Hazard Analysis for the Mexican Subduction Zone From Stochastic Slip Models

et al. 2021

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“…Another factor controlling the efficiency of tsunami generation by large earthquakes may be temporal evolution of the seafloor displacement (Le Gal et al, ). A rupture velocity of 1 km/s and a rise time of 180 s yielded the best fit between tide gauge data and model simulations in the 2004 Sumatra‐Andaman earthquake (Fujii & Satake, ).…”

Section: Tsunami Generation and Propagation: Causes Mechanisms And mentioning

confidence: 99%

Probabilistic Tsunami Hazard Analysis: Multiple Sources and Global Applications

Grezio

Babeyko²,

Baptista

et al. 2017

Reviews of Geophysics

210

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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Influence of timescales on the generation of seismic tsunamis

Cited by 15 publications

References 22 publications

Tsunami risk management for crustal earthquakes and non-seismic sources in Italy

Tsunami risk management for crustal earthquakes and non-seismic sources in Italy

Regional Probabilistic Tsunami Hazard Analysis for the Mexican Subduction Zone From Stochastic Slip Models

Probabilistic Tsunami Hazard Analysis: Multiple Sources and Global Applications

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