2016 年 11 巻 4 号 p. 613-614
The 2011 Heisei tsunami far exceeded the level previously anticipated, resulting in devastating impacts in Japan. This event made it clear that preparation for tsunami hazards, based on past historical data alone, is inadequate. It is because tsunami hazards are characterized by a lack of historical data – due to the fact tsunamis are rare, high impact phenomena. Hence, it is important to populate a dataset with more data by including events that might have occurred outside the recorded historical timeframe, such as those inferred from geologic evidence. The dataset can also be expanded with “imaginary” experiments performed numerically using proper models. Unlike historical data that directly represent actual tsunami events as fact, geologic evidence (for example, sediment deposits) remains a conjecture for tsunami occurrences, and tsunami runup conditions evaluated using geologic data are uncertain. Theoretical approaches require making hypotheses, assumptions, and approximations. Numerical simulations require not only the accurate initial and boundary conditions but also adequate modeling techniques and computational capacity. Therefore, it is crucial to quantify the uncertainties involved in geologic, theoretical, and modeling approaches.
Approximately 30 years ago, research on paleo-tsunamis based on geologic evidence was initiated and has been significantly advanced in the intervening years. During the same period, substantial advances in computational modeling used to predict tsunami propagation and runup processes were made. Understanding tsunami behavior, characteristics, and physics have resulted primarily from the well-organized international effort of field surveys initiated by the 1992 Nicaragua Tsunami event. Such rapidly advancing knowledge and technologies were unfortunately not sufficiently implemented in practice in a timely manner. Had this been the case, the disaster of the 2011 event would have been reduced, possibly avoiding the infamous nuclear meltdown at the Fukushima Dai-ichi Nuclear Power Plant.
Having learned lessons from the 2011 Heisei Tsunami, Japan is now attempting to develop a robust tsunami-mitigation strategy that consists of two-tier criteria: Level 1 Tsunami for structure-based tsunami protection and Level 2 Tsunami for evacuation-based disaster reduction. Tsunami intensities of Levels 1 and 2 are determined by experts’ analysis and judgments. In the United States, a probabilistic tsunami hazard analysis is now widely adopted: for example, the latest ASCE-7 inundation maps are based on the hazard level of a 2,500-year return period. But again, due to the lack of data, the probabilistic analysis must rely mainly on imaginary experiments and experts’ judgments.
The topic of this special issue focuses on the theme of uncertainty involved in tsunami hazard prediction. We review and examine uncertainties associated with tsunami simulations, near-shore effects, flow velocities, tsunami effects on buildings, coastal infrastructure, and sediment transport and deposits. Substantial uncertainty regarding tsunami hazards is likely the result of tsunami generation processes. This component, however, is not discussed here because it is closely related to the topic of probabilistic ‘seismic’ hazard analysis.
This special issue is a compilation of seven papers addressing the current status of predictabilities, and will hopefully stimulate continual research that will lead to further improvements.
Presenting numerically simulated examples, the paper by Lynett shows that the accurate prediction of tsunami-induced currents are much more difficult to achieve than the prediction of inundation depths. A small difference in an input parameter in the numerical model results in a very large difference in currents, especially the currents associated with the eddy formations. Keon, Yeh, Pancake and Steinberg demonstrate that
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