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As confirmed by the extreme tsunami events over the last decade (the 2004 Indian Ocean, 2010 Chile and 2011 Japan tsunami events), mitigation measures and effective evacuation planning are needed to reduce disaster risks. Modeling tsunami evacuations is an alternative means to analyze evacuation plans and possible scenarios of evacuees' behaviors. In this paper, practical applications of an agent-based tsunami evacuation model are presented to demonstrate the contributions that agent-based modeling has added to tsunami evacuation simulations and tsunami mitigation efforts. A brief review of previous agent-based evacuation models in the literature is given to highlight recent progress in agent-based methods. Finally, challenges are noted for bridging gaps between geoscience and social science within the agent-based approach for modeling tsunami evacuations. [ABSTRACT FROM AUTHOR]

On September 8, 2017 (UTC), a normal-fault earthquake occurred 87 km off the southeast coast of Mexico. This earthquake generated a tsunami that was recorded at coastal tide gauge and offshore buoy stations. First, we conducted a numerical tsunami simulation using a single-fault model to understand the tsunami characteristics near the rupture area, focusing on the nearby tide gauge stations. Second, the tsunami source of this event was estimated from inversion of tsunami waveforms recorded at six coastal stations and three buoys located in the deep ocean. Using the aftershock distribution within 1 day following the main shock, the fault plane orientation had a northeast dip direction (strike $$= 320^{\circ }$$ , dip $$= 77^{\circ }$$ , and rake $$=-92^{\circ }$$ ). The results of the tsunami waveform inversion revealed that the fault area was 240 km × 90 km in size with most of the largest slip occurring on the middle and deepest segments of the fault. The maximum slip was 6.03 m from a 30 × 30 km segment that was 64.82 km deep at the center of the fault area. The estimated slip distribution showed that the main asperity was at the center of the fault area. The second asperity with an average slip of 5.5 m was found on the northwest-most segments. The estimated slip distribution yielded a seismic moment of $$2.9 \times 10^{21}$$ Nm (Mw = 8.24), which was calculated assuming an average rigidity of $$7\times 10^{10}$$ N/m. [ABSTRACT FROM AUTHOR]

The tsunami caused by the Tonga submarine volcanic eruption that occurred at 13:15 Japan Time (JST) on January 15, 2022, exposed a blind spot in Japan's tsunami monitoring and warning system, which was established in 1952 for local tsunamis and expanded to distant tsunamis after the 1960 Chile tsunami. This paper summarizes how the warning system responded to the unprecedented tsunami, the actual evacuation process, and the damage it caused in Japan. Initially, the tsunami from the volcanic eruption was expected to arrive at approximately midnight with amplitudes of less than 20 cm. However, a series of short waves arrived at approximately 21:00, a few hours earlier than expected. The early arrival of these sea waves coincided with a rapid increase in atmospheric pressure; then, the short-period component was predominant, and the wave height was amplified while forming wave groups. After a 1.2 m tsunami was observed in Amami City in southern Japan at 23:55 JST, the Japan Meteorological Agency issued a tsunami warning/advisory. The tsunami continued, and all advisories were cleared at 14:00 JST on January 16. Information about this tsunami and the response to it are summarized here, including the characteristics and issues of the actual tsunami evacuation situation in each region. There were no casualties, but the issues that emerged included difficulty evacuating on a winter night and traffic congestion due to evacuation by car and under the conditions of the COVID-19 pandemic. In the coastal area, damage to fishing boats and aquaculture facilities was reported due to the flow of the tsunami. In addition, damage to aquaculture facilities, including those producing oysters, scallops, seaweed and other marine products, decreased the supply of marine products, and the economic impact is likely to increase in the future. [ABSTRACT FROM AUTHOR]

We developed tsunami fragility functions using three sources of damage data from the 2018 Sulawesi tsunami at Palu Bay in Indonesia obtained from (i) field survey data (FS), (ii) a visual interpretation of optical satellite images (VI), and (iii) a machine learning and remote sensing approach utilized on multisensor and multitemporal satellite images (MLRS). Tsunami fragility functions are cumulative distribution functions that express the probability of a structure reaching or exceeding a particular damage state in response to a specific tsunami intensity measure, in this case obtained from the interpolation of multiple surveyed points of tsunami flow depth. We observed that the FS approach led to a more consistent function than that of the VI and MLRS methods. In particular, an initial damage probability observed at zero inundation depth in the latter two methods revealed the effects of misclassifications on tsunami fragility functions derived from VI data; however, it also highlighted the remarkable advantages of MLRS methods. The reasons and insights used to overcome such limitations are discussed together with the pros and cons of each method. The results show that the tsunami damage observed in the 2018 Sulawesi event in Indonesia, expressed in the fragility function developed herein, is similar in shape to the function developed after the 1993 Hokkaido Nansei-oki tsunami, albeit with a slightly lower damage probability between zero-to-five-meter inundation depths. On the other hand, in comparison with the fragility function developed after the 2004 Indian Ocean tsunami in Banda Aceh, the characteristics of Palu structures exhibit higher fragility in response to tsunamis. The two-meter inundation depth exhibited nearly 20% probability of damage in the case of Banda Aceh, while the probability of damage was close to 70% at the same depth in Palu. [ABSTRACT FROM AUTHOR]

In 2011, Japan was hit by a tsunami that was generated by the greatest earthquake in its history. The first tsunami warning was announced 3 min after the earthquake, as is normal, but failed to estimate the actual tsunami height. Most of the structural countermeasures were not designed for the huge tsunami that was generated by the magnitude M = 9.0 earthquake; as a result, many were destroyed and did not stop the tsunami. These structures included breakwaters, seawalls, water gates, and control forests. In this paper we discuss the performance of these countermeasures, and the mechanisms by which they were damaged; we also discuss damage to residential houses, commercial and public buildings, and evacuation buildings. Some topics regarding tsunami awareness and mitigation are discussed. The failures of structural defenses are a reminder that structural (hard) measures alone were not sufficient to protect people and buildings from a major disaster such as this. These defenses might be able to reduce the impact but should be designed so that they can survive even if the tsunami flows over them. Coastal residents should also understand the function and limit of the hard measures. For this purpose, non-structural (soft) measures, for example experience and awareness, are very important for promoting rapid evacuation in the event of a tsunami. An adequate communication system for tsunami warning messages and more evacuation shelters with evacuation routes in good condition might support a safe evacuation process. The combination of both hard and soft measures is very important for reducing the loss caused by a major tsunami. This tsunami has taught us that natural disasters can occur repeatedly and that their scale is sometimes larger than expected. [ABSTRACT FROM AUTHOR]