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Abstract Earthquakes that cause extensive damage occur frequently in Japan, the most recent being the Noto Peninsula earthquake on January 1, 2024. To facilitate such a recovery, we introduce a community-based participatory research program implemented through cooperation between universities and local communities after the 2011 Great East Japan Earthquake. In this project, the university and the town of Shichigahama, one of the affected areas, collaborated to hold annual workshops in the target area, which evolved into a climate monitoring survey. Even in Japan, where disaster prevention planning is widespread, various problems arise in the process of emergency response, recovery and reconstruction, and building back better when disasters occur. As is difficult for residents and local governments to solve these problems alone, it is helpful when experts participate in the response process. In this study, we interviewed town hall and university officials as representatives of local residents regarding this project and discussed their mutual concerns. The community-based participatory research framework developed in the Shichigahama project could be used in the recovery from the Noto Peninsula Earthquake as well as in future reconstruction and disaster management projects.

Abstract An earthquake with a moment magnitude of 7.5 (Mw) struck the northern Noto Peninsula, Ishikawa Prefecture, Japan, at 16:10 local time on January 1, 2024. This earthquake triggered a tsunami that propagated along the coastline of Ishikawa, Toyama, and Niigata Prefectures facing the Sea of Japan and significantly damaged coastal communities and infrastructure. Approximately 70 researchers from 23 universities or other institutes throughout Japan formed a joint research group to conduct a post-tsunami survey along a 340 km stretch of the coast. Based on the watermarks and traces of the tsunami, the inundation and run-up heights were surveyed using total stations, automatic optical levels, laser range finders, and a real-time kinematic (RTK) Global Navigation Satellite System (GNSS). The tidal correction was adjusted using astronomical tidal tables. In total, 303 survey records have been compiled, generating the NP2024TS (Noto Peninsula 2024 Tsunami Survey) dataset. This dataset provides comprehensive information on the inundation and run-up heights of the tsunami, which is useful for understanding tsunami characteristics and validating numerical tsunami models.

Abstract A moment magnitude (M w) 7.5 earthquake occurred on January 1, 2024, at the northern tip of the Noto Peninsula, Central Japan, triggering a large tsunami. Seismological and geodetic observations revealed the rupture of mapped submarine active faults. While proximal segment ruptures have been well resolved by previous research, far offshore segments have posed challenges for onshore-based inversions. This emphasizes the necessity for a comprehensive study on the fault through tsunami modeling. Here, we aimed to examine tsunami propagation and inundation using four different fault models to identify the general characteristics of the tsunami source and evaluate the complexities of earthquake- and submarine landslide-induced tsunamis. We identified the simultaneous rupture of two active fault systems as the most suitable model for explaining observed tsunami height and inundation; however, some inconsistencies with observations remained. The propagation process did not follow a concentric pattern but aligned with bathymetric heterogeneity. The findings also suggested potential amplification effects responsible for the devastation of the coast of Iida Bay and indicated a possible submarine landslide in southern Toyama Bay. The findings of the present work could benefit the exploration of a more realistic tsunami source model, considering the differences between observations and simulations. Such efforts, in collaboration with paleotsunami research, can contribute to the improved assessment of hazards from submarine active faults.

Abstract This study explored closed-circuit television (CCTV) networks in northeastern Toyama Prefecture, Japan, as a new data source for tsunami detection following the 2024 Noto Peninsula earthquake. We analyzed CCTV footage and extracted time-series water level fluctuations at Yokoyama, Shimoiino, and Ekko. Spectral analysis of these waveforms revealed several long-period peaks (more than 100 s) in power spectral density (PSD), suggesting the presence of tsunami components. Notably, relatively large PSD peaks at approximately 5–10 min were observed at all CCTV locations in this study and at offshore wave observation points (Tanaka and Toyama). At Yokoyama, a maximum run-up of approximately 3 m was confirmed around 16:28. Although water level fluctuations at Shimoiino and Ekko were detected, identifying tsunami components proved challenging due to their small magnitude compared to other wave components. Despite these challenges, this study demonstrates the potential of CCTV networks for tsunami detection, and further research is needed to achieve real-time detection.

Abstract The scientific evidence based on experiences with past disasters points to the possibility of the occurrence of future mental health issues among those who were affected by the recent Turkey–Syria earthquake. However, post-disaster care information on factors that could give rise to mental health issues among those affected have yet to be provided. In March 2011, Tohoku University compiled and published a booklet with post-disaster healthcare information based on the experiences with the Great East Japan Earthquake. This study aimed to promote the introduction and use of this booklet for post-disaster care in Turkey and Syria by presenting the results of a satisfaction survey conducted with relevant Japanese organizations about the booklet. A total of 505 Japanese organizations participated in the satisfaction survey of, and evaluated, the booklet. The results indicated the need to consider the ease of understanding for the general public when providing information on post-disaster care through booklets. We hope that this study leads to the appropriate provision of easy-to-understand, post-disaster healthcare information to the victims of the Turkey–Syria earthquake and future disasters.

Abstract The massive eruption of the Hunga Tonga-Hunga Ha’apai (HTHH) volcano in Tonga on 15 January 2022 at 04:15 UTC had a global impact and triggered an atmospheric wave and a tsunami. We first analyzed observation data from meteorological stations and tide gauges at 12 locations. Low-frequency trends in the observation data were removed by using a high-pass filter. Fourier and wavelet spectral analyses were applied to determine the frequency characteristics of the filtered data. Modal analysis was developed and used to investigate natural oscillation periods based on bathymetry. The results showed that the Lamb wave generated by the atmospheric pressure wave arrived ~ 7 and ~ 44 h after the eruption. The tsunami arrived ~ 11 and ~ 45 h after the eruption, which corresponded to the arrival time of the Lamb wave. The dominant periods of the Lamb waves were ~ 7.7 and ~ 7.5 min, and for the tsunamis they were ~ 9.9 and ~ 28.7 min. The periods derived from the spectral analysis matched the natural oscillation of the eigenperiod derived from the modal analysis, in eight out of the twelve stations. This study provides valuable insight and information regarding the nonseismic and far-field effects of tsunamis generated by volcanic eruptions.

This study focuses on understanding the historical tsunami events in Eastern Indonesia, specifically the Banda Sea region, by extracting information from the limited and challenging-to-interpret historical records. The oldest detailed account of a tsunami in Indonesia dates back to 1674, documented in the book Waerachtigh Verhael Van de Schlickelijcke Aerdbebinge by Rumphius. The study aims to comprehend the primary source of the tsunami and analyze its characteristics to facilitate future tsunami risk reduction. The methodology includes collecting topography and bathymetry data, conducting landslide scenario analysis, employing a two-layer wave propagation model, and performing spectral analysis. The study utilizes comprehensive datasets, investigates potential landslide scenarios, simulates tsunami propagation, and analyzes frequency characteristics using the fast Fourier transform. The 1674 event yielded a runup height of approximately 50–100 m, whereas this study underestimated the actual runup. To illustrate the tsunami wave along the bay’s coastline, a Hovmöller diagram was employed. By analyzing the Hovmöller diagram, the power spectral density was computed, revealing five prominent period bands: 6.96, 5.16, 4.1, 3.75, and 3.36 min. The integration of these components provides a rigorous approach to understanding tsunami dynamics and enhancing risk assessment and mitigation in the study area.

Abstract Evacuation is a critical life-saving action, especially in devastating natural hazards such as near-field tsunamis. However, the development of effective evacuation measures remains challenging to the extent that a successful example has been referred to as a ‘miracle’. Here we show that urban structures have the potential to reinforce attitudes towards evacuation and significantly influence the success of tsunami evacuation. Agent-based evacuation simulations revealed that a distinctive root-like urban structure formed in ria coasts reinforces positive evacuation attitudes by effectively gathering evacuation flows and leads to higher evacuation rates compared to typical grid-like urban structures, which can explain the regional differences in the number of casualties in the 2011 Tohoku tsunami. Although a grid-like structure reinforces negative attitudes under low evacuation tendencies, with leading evacuees, its dense feature helps to propagate positive attitudes and drastically improve evacuation tendencies. These findings pave the way for making successful evacuation inevitable through harmonised urban and evacuation plannings.

Abstract Tsunami resonance excitation induces tsunami amplification, persistent oscillation, and strong current velocities, which may enlarge coastal hazards in tsunamigenic areas. Historically, the 2006 Pingtung earthquake doublet triggered tsunamis that affected the south Taiwan coast. Studying the resonance features based on past tsunamis is important for assessing tsunami hazards and obtaining critical disaster mitigation information. Here, we elucidate the tsunami resonance oscillation and its impacts along the south Taiwan coast based on synthetic assessment of tsunamis induced by the 2006 Pingtung earthquake doublet. A numerical simulation was performed to replicate the 2006 Pingtung earthquake doublet tsunamis. Then, spatially integrated spectra were obtained via spatiotemporal analysis. The results were compared to tsunami spectra at tide gauges to identify the main oscillation modes, suggesting the main oscillation modes had 13–50 min periods during the 2006 Pingtung earthquake doublet tsunamis. The tsunami resonance oscillations were analyzed based on the main oscillation modes. In the 2006 Pingtung earthquake doublet tsunamis, edge waves occurred along the south Taiwan west coast in most oscillation modes. The Hengchun Peninsula prevents tsunami oscillation transmission, and only part of the oscillation energy at certain periods propagates to the east coast. Furthermore, the spectral amplitude distribution migration across the period domain revealed that energy amplification is a frequency-dependent phenomenon and is responsible for the large tsunami heights and strong tsunami-induced current velocities distributed along the south Taiwan coast during this past tsunami.

Abstract Historical data can determine how adolescents recover from difficult situations such as the Coronavirus disease 2019 (COVID-19) pandemic. This study analysed 3 years of data obtained from high-school students who had been affected by the 2011 Great East Japan Earthquake and consequently evidenced the importance of increasing resilience among affected adolescents. This involved identifying factors contributing to resilience through a model that assessed for each tsunami disaster. This model was determined by assessing the correlation between survivors’ resilience scores and their measured psychological and lifestyle scores. This approach showed that, in all tsunami damage models, resilience was most affected by the depressed emotions. Thus, our approach suggests that interventions for improving the depressed mood may improve resilience in adolescents during the COVID-19 pandemic.

Abstract On 15 January 2022 at 04:15 UTC, the Hunga Tonga-Hunga Ha’apai (HTHH) volcano in Tonga produced a massive eruption that triggered a transoceanic tsunami generated by the coupled ocean and atmospheric shock wave produced during the explosion. The tsunami first reached the coast of Tonga and eventually reached many coasts around the world. This volcano previously underwent a massive eruption in 1100 AD, and an eruption occurs approximately every 1000 years. The 2022 HTHH event provides an opportunity to study a major volcanically generated tsunami that caused substantial damage. In this study, we present a numerical simulation of a tsunami with a state-of-the-art numerical model based on a submarine explosion scenario. We constrain the geometry and magnitude of the explosion energy source based on analyses of pre- and post-event satellite images, which demonstrate that the explosion magnitude varied from 1 to 90 megatons of trinitrotoluene (Mt). Estimated submarine explosion geometries result in a suitable explosion magnitude of approximately 25 Mt, as determined with the waveform from the tide gauge in the time and frequency domains. The tsunami wave first reached the northwestern part of Tonga’s Tongatapu within 10 min, with a maximum runup height of approximately 15 m, and covered the whole of Tongatapu within 30 min. Finally, the numerical simulation provides deep insights into the physical volcanic explosion processes and improves our understanding and forecasting capabilities of frequent and catastrophic tsunamis caused by submarine volcanic explosions.

Rapid and accurate hazard prediction is important for prompt evacuation and casualty reduction during natural disasters. Here, the authors present an AI-enabled tsunami forecasting approach, which provided rapid and accurate early warnings.

When considering a tsunami disaster, many researchers have considered the tsunami's flow depth and velocity as the primary contributors to the building damage. Additionally, the majority of these studies have used the maximum value as the measure of each of these two factors. However, building damage may not occur when the maximum flow depth and the maximum flow velocity of the tsunami are reached. This study addressed two objectives based on the 2011 Great East Japan Earthquake and Tsunami. Firstly, to find out whether the maximum values of the flow depth and flow velocity are the same as their critical values and, secondly, to verify which combination of the parameters is the best predictor of the building damage level. The data from 18,000 buildings in Ishinomaki City, Japan, with the cooperation of the Japanese joint survey team, were analyzed using the decision tree related algorithms. The critical variables were the simulated data at the time when the buildings collapsed. The analysis showed the accuracy of the prediction based on the group of variables. Finally, the findings showed that the combination of the critical flow depth and maximum flow velocity provided the highest accuracy for classifying the level of building damage.

A questionnaire survey was distributed via the Internet to 600 respondents. Preliminary results revealed that most Japanese people regularly washed their hands and had low resistance to wearing masks even before the COVID-19 pandemic. Internet news was the most common source of information. Half of the respondents said they would “stay at home evacuation” if a disaster occurred during the COVID-19 pandemic, reflecting the strategy promoted to reduce crowding in evacuation shelters. If a state of emergency must be reinstated, one-third of respondents said they could bear it for a few months and another one-third for a few weeks.

Self-aid and mutual assistance among victims are critical for resolving difficulties in the immediate aftermath of a disaster, but individual facilitative factors for such resolution processes are poorly understood. To identify such individual factors in the background (i.e., disaster damage and demographic) and personality domains considering different types of difficulty and resolution, we analyzed survey data collected in the 3-year aftermath of the 2011 Great East Japan Earthquake and Tsunami. We first identified major types of difficulty using a cluster analysis of 18 difficulty domains and then explored individual factors that facilitated six types of resolution (self-help, request for help, help from family, help from an acquaintance, help through cooperation, and public assistance) of these difficulty types. We identified general life difficulties and medico-psychological difficulties as two broad types of difficulty; disaster damage contributed to both types, while some personality factors (e.g., neuroticism) exacerbated the latter. Disaster damage hampered self-resolution and forced a reliance on resolution through cooperation or public assistance. On the other hand, some demographic factors, such as being young and living in a three-generation household, facilitated resolution thorough the family. Several personality factors facilitated different types of resolution, primarily of general life difficulties; the problem-solving factor facilitated self-resolution, altruism, or stubbornness resolutions through requests, leadership resolution through acquaintance, and emotion-regulation resolution through public assistance. Our findings are the first to demonstrate the involvement of different individual, particularly personality, factors in survival in the complex social dynamics of this disaster stage. They may contribute to disaster risk mitigation, allowing sophisticated risk evaluation and community resilience building.

The environment surrounding researchers has changed significantly in the face of COVID-19 restrictions. An online self-reported questionnaire was completed by 10,557 participants between June 15 and 19, 2020. The impact on work/research activities and harassments under COVID-19 conditions was higher among researchers (1963) compared to non-researchers (8572). We further examined the effect of COVID-19 restrictions on 300 researchers. Women were significantly more likely to report being harassed than males. The overall “decrease in research motivation” was higher in women. The restrictions on research activities because of COVID-19 restrictions caused future anxiety and a decrease in research motivation.

Understanding the evacuation behaviour in tsunamis offers important knowledge to consider for evacuation, countermeasures and preparedness for future tsunamis. With this background, various aspects of evacuation behaviour have been investigated in past earthquake and tsunami events, but have not been organised to provide an overview of the general tsunami evacuation process. In this paper, we reviewed 39 reports and articles that surveyed actual human responses in past 22 tsunami-related events and organised the existing findings on human behaviour during tsunamis into a theoretical framework: a tsunami evacuation process that describes general human behavioural components and notifications during tsunami events. The framework illustrates the continuous psychological and physical process in tsunami evacuation and the dynamical transition of notifications during tsunamis. Since the tsunami evacuation process provides a clear overview of the components of the tsunami evacuation process, it enables researchers design survey questions for comprehensive investigations of tsunami evacuations and leads a deeper and more comprehensive understanding of human behaviour in tsunamis that will contribute to consider more appropriate evacuation preparedness for future tsunamis.

Mutual help is common in human society, particularly during a disaster. The psychological processes underlying such social support are of interest in social and evolutionary psychology, as well as in the promotion of community resilience. However, research in terms of personality factors or support types is sporadic and has yet to address actual emergency situations. In this study, we analyzed survey data from survivors of the 2011 Tohoku earthquake and tsunami. The data included five types of social support occurring during the evacuation from a potential tsunami area: providing and receiving actual help and oral encouragement, as well as perceived support. The personality factor items included the Big Five dimensions and eight "power to live" factors, which were identified as advantageous for survival during this disaster. While none of the Big Five dimensions were associated with social support, six of the power to live factors were. Altruism, problem solving, etiquette, and self-transcendence contributed to the provision of actual help. Leadership and active well-being contributed to oral encouragement with the latter contributing also to perceived support. The findings were largely consistent with the literature in a non-emergency context. The relevance of the majority of these pro-survival personality factors to social support appeared to support the view that the propensity to cooperate in service of human survival in a disaster situation is primarily a social, rather than an individual, phenomenon, and encourages research on the mechanisms underlying how personality factors provide a benefit to both the individual and their community.

With a total of 251,770 casualties and US$280 billion in damages, the loss inflicted by tsunamis between 1998 and 2017 was one hundred times higher than that experienced during the previous decade (1978–1997). The processes of disasters following tsunamis have also become more complex with global impacts. The broad economic and political consequences of the 2011 Tohoku earthquake and tsunami encouraged the global community to consider the problem of “cascading disasters”. We can categorized the cause and damage due to the 2011 tsunami with incentive and predisposing factors, impact as compound disaster. We also proposed and developed various tsunami fragility functions as essential tools to assess and mitigate damage such as casualties, house/building, marine vessels, pedestrian bridges, road bridges and aquaculture rafts. The process of cascading disasters still remains as major issue and should be studied together with the factors of interdependencies, vulnerabilities, amplification, secondary disasters and critical infrastructure and spin-off effects. Another important issue concerns non-seismic tsunamis, such as those that impacted Palu and Sunda Straight in Indonesia in 2018. These events demonstrated the difficulties and remaining problems regarding tsunami warning and evacuation and the difficulties of real time monitoring and detection. Since tsunamis are low-frequency, high-impact natural hazards, interdisciplinary research on risk perception, awareness, memory and lessons becomes critically important. The process of sharing tsunami experiences underwent a transformation in the form of digital archives and new media in response to the needs and opportunities for disaster risk reduction (DRR) in the 21st century. Last but not least, this paper highlights the roles of museum and memorial halls in order to share the experiences of natural hazard-related disasters necessary to inform disaster mitigation. Keywords: Tsunamis, Disaster science, Process of transformation

A probabilistic hazard analysis of a tsunami generated by a subaqueous volcanic explosion was performed for Taal Lake in the Philippines. The Taal volcano at Taal Lake is an active volcano on Luzon Island in the Philippines, and its eruption would potentially generate tsunamis in the lake. This study aimed to analyze a probabilistic tsunami hazard of inundated buildings for tsunami mitigation in future scenarios. To determine the probabilistic tsunami hazard, different explosion diameters were used to generate tsunamis of different magnitudes in the TUNAMI-N2 model. The initial water level in the tsunami model was estimated based on the explosion energy. The tsunami-induced inundation from the TUNAMI-N2 model was overlaid on the distribution of buildings. The tsunami hazard analysis of inundated buildings was performed by using the maximum inundation depth in each explosion case. These products were used to calculate the probability of the inundated building given the occurrence of a subaqueous explosion. The results from this study can be used for future tsunami mitigation if a tsunami is generated by a subaqueous volcanic explosion.

A hypothetical landslide tsunami at the Nile Delta in the Eastern Mediterranean Sea is modeled in order to study hazards it would pose to the region. The methodology used is based on numerical simulation of the generation and propagation of a realistic landslide scenario. The volume of the landslide source is 41 km3, located offshore northern Egypt. The maximum simulated wave heights along the northern, southern, and eastern coasts in the region are in the range of 1–12, 1–6.5, and 0.5–3 m, respectively. The maximum tsunami current velocity along the coasts reaches ~ 2–5 m s–1. Simulations show that bathymetric features in the region and the coastal morphology focus the maximum tsunami waves into some specific paths along which the largest tsunami runup heights occur. The semi-enclosed nature of the eastern Mediterranean causes wave reflections, which result in several wave trains arriving at every coastal site. In some coastal sites, the largest simulated wave belongs to the second wave train, indicating that wave reflection is responsible for this delayed large wave. Based on the results, deployment of a network of deepwater pressure gauges may help in detection and early warning of possible landslide-generated tsunamis in the Eastern Mediterranean.

Understanding the impacts of tsunamis, especially in terms of damage and losses, is important for disaster mitigation and management. The aim of this study is to present our estimations of the potential losses from tsunami damage on Okinawa Island. We combine the use of a tsunami hazard map and our proposed economic loss model to estimate the potential losses that would be sustained by Okinawa Island in the event of a tsunami. First, to produce the tsunami hazard map, we calculated tsunami flow characteristics using the mathematical model TUNAMI-N2 and incorporating 6 earthquake fault scenarios around the study area. The earthquake scenarios are based on historical records along the Ryukyu Trench and the Okinawa. The resulting inundation map is overlaid with economic land use type and topography maps to identify vulnerable regions, which are then employed to compute potential economic losses. Second, we used our proposed economic model for this study area to calculate the potential losses that would be sustained in these vulnerable regions. Our economic model extends the multi-regional-input-output (MRIO) model, where the economic values of industrial sectors are scaled to correlate with land use and topography types (coastal and inland areas) to calculate losses through the Chenery−Moses estimation method. Direct losses can be estimated from the total input of the MRIO table, while indirect losses are computed from the direct losses and interaction parameter of the MRIO table. The interaction parameter is formed by linear programming and calculated using the Leontief methodology. Our results show that the maximum total damaged area under the 6 earthquake scenarios is approximately 30 km2. Inundation ranging from 2.0 to 5.0 m in depth covers the largest area of approximately 10 km2 and is followed by areas with inundation depths of 1.0−2.0 m and >5.0 m. Our findings show that direct losses will occur, while indirect losses are only approximately 56% that of direct losses. This approach could be applied to other areas and tsunami scenarios, which will aid disaster management and adaptation policies.

Although various factors related to the environment (perception of earthquake and warning) and knowledge (oral history and scientific knowledge) affect individual differences in evacuation behavior before a tsunami, the roles of psychological processes and personality factors in such relationships are poorly understood. We addressed this research gap by applying hierarchical regression analyses to survey data from survivors of the 2011 Tohoku earthquake and tsunami disaster. Previously-known contributions of environmental and knowledge factors were mostly replaced by the perception of a tsunami risk and threat, and these background factors were shown to facilitate these psychological processes. Several personality factors directly contributed to voluntary evacuation, particularly leadership and active well-being in the Power to Live scale, and extraversion in the Big Five scale. Overall, these results seem to indicate the need for formulating two independent targets when developing measures to enhance appropriate tsunami evacuation. Facilitation of the perception of a tsunami risk and threat may basically be pursued by developing existing approaches. Addressing the relevant personality factors may be done in a broader context of disaster or general education and sociocultural activities.

The aim of this study is to assess the performances of different infrastructures as structural tsunami countermeasures in Sendai City, based on the lessons from the 11 March 2011, Great East Japan Tsunami, which is an example of a worst-case scenario. The tsunami source model Ver. 1.2 proposed by Tohoku University uses 10 subfaults, determined based on the tsunami height and the run-up heights measured for all tsunami affected areas. The TUNAMI-N2 model is used to simulate 24 cases of tsunami defense in Sendai City based on a combination of 5 scenarios of structural measures, namely, a seawall (existing and new seawall), a greenbelt, an elevated road and a highway. The results of a 2D tsunami numerical analysis show a significant difference in the tsunami inundations in the areas protected by several combinations of structures. The elevated road provides the highest performance of the single schemes, whereas the highest performance of the 2-layer schemes is the combination of an existing seawall and an elevated road. For the 3-layer scenarios, the highest performance is achieved by the grouping of an existing seawall, a new seawall, and an elevated road. The combination of an existing seawall, a new seawall, a greenbelt and an elevated road is the highest performing 4-layer scenario. The Sendai City plan, with a 5-layer scenario, reduces the tsunami inundation area by 20 sq. km with existing structural conditions. We found that the combination of an existing seawall, a greenbelt, an elevated road and a highway (a 4-layer scheme) is the optimum case to protect the city against a tsunami similar to the 2011 Great East Japan Tsunami. The proposed approach can be a guideline for future tsunami protection and the evaluation of countermeasure schemes.

Based on the definition of tsunami risk, we quantitatively evaluated the annual expected tsunami loss ratio (Tsunami Risk Index) and clarified the quantitative effects of epistemic uncertainties in tsunami hazard assessments on the tsunami risk of buildings by combining probabilistic information regarding tsunami inundation depths at target points and tsunami fragility assessments of buildings. For the risk assessment, we targeted buildings with four different structures (reinforced concrete, steel, brick, wood) located in three different areas (Soma, Sendai, Kesennuma). In conclusion, we demonstrated that the expected tsunami risk could vary by approximately two orders of magnitude when considering tsunami hazard uncertainties between the 95th percentile and the 5th percentile. In addition, we quantitatively clarified the fact that we cannot properly understand the tsunami risk by evaluating the tsunami fragility alone. For example, the analysis results indicate that the tsunami risk of a wood building located in Kesennuma is lower than that of a reinforced concrete building located in either Soma or Sendai.

People perceive, judge, and behave differently in disasters and in a wide range of other difficult situations depending on their personal characteristics. The power to live, as captured by characteristics that are advantageous for survival in such situations, has thus far been modeled in arbitrary ways. Conceptualizing such characteristics in more objective ways may be helpful for systematic preparations for future disasters and life difficulties. Here, we attempted to identify the major factors of the power to live by summarizing the opinions of survivors of the 2011 Great East Japan Earthquake disaster. We conducted personal interviews with 78 survivors about their survival experiences and elicited their opinions about the power to live as relevant to those experiences. We then incorporated these opinions into a questionnaire that was completed by 1400 survivors. Factor analysis identified eight factors related to the power to live: leadership, problem solving, altruism, stubbornness, etiquette, emotional regulation, self-transcendence, and active well-being. All factors had sufficient internal construct validity, and six of them showed significant associations with one or more measures of survival success in the disaster, including immediate tsunami evacuation, problem solving in refugee situations, recovery during reconstruction, physical health, and mental health. Overall, the personal characteristics described by the eight factors largely overlap with those described in previous arbitrary models. Further research should investigate the domains, phases, and contexts in which each factor contributes to survival, address whether the factors are rooted in nature or in nurture, and explore their psychological or physiological bases.

Excessive car evacuation can cause severe traffic jams that can lead to large numbers of casualties during tsunami disasters. Investigating the possible factors that lead to unnecessary car evacuation can ensure smoother tsunami evacuations and mitigate casualty damages in future tsunami events. In this study, we quantitatively investigated the possible factors that promote car evacuation, including both necessary and unnecessary usages, by statistically analysing a large amount of data on actual tsunami evacuation behaviours surveyed in Kesennuma, where devastating damage occurred during the 2011 Tohoku Tsunami. A straightforward statistical analysis revealed a high percentage of car evacuations (approx. 50%); however, this fraction includes a high number of unnecessary usage events that were distinguished based on mode choice reasons. In addition, a binary logistic regression was conducted to quantitatively evaluate the effects of several factors and to identify the dominant factor that affected evacuation mode choice. The regression results suggested that the evacuation distance was the dominant factor for choosing car evacuation relative to other factors, such as age and sex. The cross-validation test of the regression model demonstrated that the considered factors were useful for decision making and the prediction of evacuation mode choice in the target area.