Latest Research on Tsunami : Mar 2022

Mechanism of tsunami earthquakes

The mechanism of the Aleutian islands earthquake of 1946 and the Sanriku earthquake of 1896 is studied on the basis of the data on seismic waves from 5 to 100 s and on tsunamis. These earthquakes generated, despite their relatively small earthquake magnitude, two of the largest and most widespread tsunamis in history. The data obtained at different periods are interpreted in terms of the effective moment, Me. The effective moment at a certain period is defined as a seismic moment of a virtual step function dislocation that explains the observation at this period. The effective moment of the tsunami earthquakes increases rapidly towards 0.5 to 1.0 × 1029 dyne · cm as the period increases while, for ordinary earthquakes, it is more or less constant. This dependence can be explained in terms of a source deformation having a time constant of about 100 s. The Mc versus ƒ (frequency) diagram provides a diagnostic method of estimating the tsunami potential of earthquakes. If the

diagram for an earthquake has a steep upgrade towards low frequency implying an effective moment exceeding 1028 dyne · cm at zero frequency, the earthquake has a high tsunami potential. Since the determination of the effective moment at various periods can be made by a simple procedure, this method could be incorporated in the tsunami warning system. The abnormal slow deformation at the source of the tsunami earthquakes may be a manifestation of viscoelasticity of a weak zone beneath the inner margin of the trenches. The weak zone which is implied by large normal-fault earthquakes such as the 1933 Sanriku and the 1929 Aleutian islands earthquakes may be a result of frictional heating at the interface between the oceanic and the continental lithospheres.[1]


The tsunami phenomenon

With human activity increasingly concentrating on coasts, tsunamis (from Japanese tsu = harbour, nami = wave) are a major natural hazard to today’s society. Stimulated by disastrous tsunami impacts in recent years, for instance in south-east Asia (2004) or in Japan (2011), tsunami science has significantly flourished, which has brought great advances in hazard assessment and mitigation plans. Based on tsunami research of the last decades, this paper provides a thorough treatise on the tsunami phenomenon from a geoscientific point of view. Starting with the wave features, tsunamis are introduced as long shallow water waves or wave trains crossing entire oceans without major energy loss. At the coast, tsunamis typically show wave shoaling, funnelling and resonance effects as well as a significant run-up and backflow. Tsunami waves are caused by a sudden displacement of the water column due to a number of various trigger mechanisms. Such are earthquakes as the main trigger, submarine and subaerial mass wastings, volcanic activity, atmospheric disturbances (meteotsunamis) and cosmic impacts, as is demonstrated by giving corresponding examples from the past. [2]


Tsunami Deposits

Geological investigations of coastal sediments indicate that prehistoric tsunamis can be identified. Their characterisation has altered our knowledge of the past frequency and magnitude of tsunamis for different areas of the world. Yet there have been relatively few geological studies of modern tsunamis with virtually no direct observations of the processes associated with tsunami sediment transport and deposition. This paper discusses these issues and draws on the results of recent research to summarise our current knowledge on the nature of tsunami deposits.[3]


Landslide tsunami

In the creation of “surprise tsunami,” submarine landslides head the suspect list. Moreover, improving technologies for seafloor mapping continue to sway perceptions on the number and size of surprises that may lie in wait offshore. At best, an entirely new distribution and magnitude of tsunami hazards has yet to be fully appreciated. At worst, landslides may pose serious tsunami hazards to coastlines worldwide, including those regarded as immune. To raise the proper degree of awareness, without needless alarm, the potential and frequency of landslide tsunami have to be assessed quantitatively. This assessment requires gaining a solid understanding of tsunami generation by landslides and undertaking a census of the locations and extent of historical and potential submarine slides. This paper begins the process by offering models of landslide tsunami production, propagation, and shoaling and by exercising the theory on several real and hypothetical landslides offshore Hawaii, Norway, and the United States eastern seaboard. I finish by broaching a line of attack for the hazard assessment by building on previous work that computed probabilistic tsunami hazard from asteroid impacts.[4]


Probabilistic Analysis of Tsunami Hazards

Determining the likelihood of a disaster is a key component of any comprehensive hazard assessment. This is particularly true for tsunamis, even though most tsunami hazard assessments have in the past relied on scenario or deterministic type models. We discuss probabilistic tsunami hazard analysis (PTHA) from the standpoint of integrating computational methods with empirical analysis of past tsunami runup. PTHA is derived from probabilistic seismic hazard analysis (PSHA), with the main difference being that PTHA must account for far-field sources. The computational methods rely on numerical tsunami propagation models rather than empirical attenuation relationships as in PSHA in determining ground motions. Because a number of source parameters affect local tsunami runup height, PTHA can become complex and computationally intensive. Empirical analysis can function in one of two ways, depending on the length and completeness of the tsunami catalog. For site-specific studies where there is sufficient tsunami runup data available, hazard curves can primarily be derived from empirical analysis, with computational methods used to highlight deficiencies in the tsunami catalog. For region-wide analyses and sites where there are little to no tsunami data, a computationally based method such as Monte Carlo simulation is the primary method to establish tsunami hazards. Two case studies that describe how computational and empirical methods can be integrated are presented for Acapulco, Mexico (site-specific) and the U.S. Pacific Northwest coastline (region-wide analysis).[5]


Reference

[1] Kanamori, H., 1972. Mechanism of tsunami earthquakes. Physics of the earth and planetary interiors, 6(5), pp.346-359.

[2] Röbke, B.R. and Vött, A., 2017. The tsunami phenomenon. Progress in Oceanography, 159, pp.296-322.

[3] Dawson, A.G. and Shi, S., 2000. Tsunami deposits. Pure and applied geophysics, 157(6), pp.875-897.

[4] Ward, S.N., 2001. Landslide tsunami. Journal of Geophysical Research: Solid Earth, 106(B6), pp.11201-11215.

[5] Geist, E.L. and Parsons, T., 2006. Probabilistic analysis of tsunami hazards. Natural Hazards, 37(3), pp.277-314.

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