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This study proposes a framework for utilizing results obtained from advanced numerical simulations and performing probabilistic tsunami hazard assessment for investigating optimal facility placement. A set of numerical simulations of the tsunami off the Pacific coast caused by the 2011 Tohoku earthquake are performed considering uncertainties in fault parameters. Both inundation depths and tsunami forces acting on buildings are numerically simulated and defined as tsunami hazard indices. Proper orthogonal decomposition is then applied to numerical results for extracting characteristic spatial modes, which can be used to construct surrogate models. Monte Carlo simulations (MCSs) were performed at a low computational cost using surrogate models. The optimal placement of facilities was probabilistically investigated with the help of genetic algorithms using the MCS results along with the concept of system failure probability. The results indicate that the proposed framework allows determining the optimal placement of facilities by applying different strategies at low computational costs while effectively reflecting the results of advanced tsunami simulations.

Consecutive ML 7.0 submarine earthquakes occurred offshore of the Hengchun Peninsula, Taiwan, on 26 December 2006. A small tsunami was generated and recorded at tide gauge stations. This important event attracted public interest, as it was generated by an earthquake doublet and produced a tsunami risk for Taiwan. This study analyzed tide gauge tsunami waveforms and numerical simulations to understand the source characteristics and resulting behaviors of tsunamis. The maximum wave heights at the three nearest stations were 0.08 m (Kaohsiung), 0.12 m (Dongkung), and 0.3 m (Houbihu), and only Houbihu recorded the first wave crest as the largest. The tsunami duration was 3.9 h at Dongkung and over 6 h at Kaohsiung and Houbihu. Spectral analyses detected dominant periodic components of spectral peaks on the tsunami waveforms. The period band from 13.6–23.1 min was identified as the tsunami source spectrum, and the approximate fault area for the consecutive tsunamis was estimated to be 800 km2, with central fault depths of 20 km (first earthquake, Mw 7.0) and 33 km (second earthquake, Mw 6.9). The focal mechanisms of the first earthquake, with a strike of 319∘, dip of 69∘, and rake of −102∘, and the second earthquake, with a strike of 151∘, dip of 48∘, and rake of 0∘, could successfully reproduce the observed tsunami waveforms. Numerical simulations suggested that the tsunami waves were coastally trapped on the south coast of Taiwan during the tsunami's passage. The trapped waves propagated along the coast as edge waves, which repeatedly reflected and refracted among the shelves, interfered with incoming incident wave, and resonated with the fundamental modes of the shelves, amplifying and continuing the tsunami wave oscillation. These results elucidated the generation and consequential behaviors of the 2006 tsunami in southern Taiwan, contributing essential information for tsunami warning and coastal emergency response in Taiwan to reduce disaster risk.

Studies have indicated that submarine landslides played an important role in the 2018 Sulawesi tsunami event, damaging the coast of Palu Bay in addition to the earthquake source. Most of these studies relied on observed coastal subaerial landslides to reproduce tsunamis but could still not fully explain the observational data. Recently, several numerical models included hypothesized submarine landslides that were taken into account to obtain a better explanation of the event. In this study, for the first time, submarine landslides were simulated by applying a numerical model based on Hovland's 3D slope stability analysis for cohesive–frictional soils. To specify landslide volume and location, the model assumed an elliptical slip surface on a vertical slope of 27 m of mesh-divided terrain and evaluated the minimum safety factor in each mesh area based on the surveyed soil property data extracted from the literature. The soil data were assumed as seabed conditions. The landslide output was then substituted into a two-layer numerical model based on a shallow-water equation to simulate tsunami propagation. The tsunamis induced by the submarine landslide that were modeled in this study were combined with the other tsunami components, i.e., coseismal deformation and tsunamis induced by previous literature's observed subaerial coastal collapse, and validated with various post-event field observational data, including tsunami run-up heights and flow depths around the bay, the inundation area around Palu city, waveforms recorded by the Pantoloan tide gauge, and video-inferred waveforms. The model generated several submarine landslides, with lengths of 0.2–2.0 km throughout Palu Bay. The results confirmed the existence of submarine landslide sources in the southern part of the bay and showed agreement with the observed tsunami data, including run-ups and flow depths. Furthermore, the simulated landslides also reproduced the video-inferred waveforms in three out of six locations. Although these calculated submarine landslides still cannot fully explain some of the observed tsunami data, they emphasize the possible submarine landslide locations in southern Palu Bay that should be studied and surveyed in the future.

Indonesia has experienced several tsunamis triggered by seismic and non-seismic (i.e., landslides) sources. These events damaged or destroyed coastal buildings and infrastructure and caused considerable loss of life. Based on the Global Earthquake Model (GEM) guidelines, this study assesses the empirical tsunami fragility to the buildings inventory of the 2018 Sunda Strait, 2018 Sulawesi–Palu, and 2004 Indian Ocean (Khao Lak–Phuket, Thailand) tsunamis. Fragility curves represent the impact of tsunami characteristics on structural components and express the likelihood of a structure reaching or exceeding a damage state in response to a tsunami intensity measure. The Sunda Strait and Sulawesi–Palu tsunamis are uncommon events still poorly understood compared to the Indian Ocean tsunami (IOT), and their post-tsunami databases include only flow depth values. Using the TUNAMI two-layer model, we thus reproduce the flow depth, the flow velocity, and the hydrodynamic force of these two tsunamis for the first time. The flow depth is found to be the best descriptor of tsunami damage for both events. Accordingly, the building fragility curves for complete damage reveal that (i) in Khao Lak–Phuket, the buildings affected by the IOT sustained more damage than the Sunda Strait tsunami, characterized by shorter wave periods, and (ii) the buildings performed better in Khao Lak–Phuket than in Banda Aceh (Indonesia). Although the IOT affected both locations, ground motions were recorded in the city of Banda Aceh, and buildings could have been seismically damaged prior to the tsunami's arrival, and (iii) the buildings of Palu City exposed to the Sulawesi–Palu tsunami were more susceptible to complete damage than the ones affected by the IOT, in Banda Aceh, between 0 and 2 m flow depth. Similar to the Banda Aceh case, the Sulawesi–Palu tsunami load may not be the only cause of structural destruction. The buildings' susceptibility to tsunami damage in the waterfront of Palu City could have been enhanced by liquefaction events triggered by the 2018 Sulawesi earthquake.

Modern tsunami events have highlighted the vulnerability of port structures to these high-impact but infrequent occurrences. However, port planning rarely includes adaptation measures to address tsunami hazards. The 2011 Tohoku tsunami presented us with an opportunity to characterise the vulnerability of port industries to tsunami impacts. Here, we provide a spatial assessment and photographic interpretation of freely available data sources. Approximately 5000 port structures were assessed for damage and stored in a database. Using the newly developed damage database, tsunami damage is quantified statistically for the first time, through the development of damage fragility functions for eight common port industries. In contrast to tsunami damage fragility functions produced for buildings from an existing damage database, our fragility functions showed higher prediction accuracies (up to 75 % accuracy). Pre-tsunami earthquake damage was also assessed in this study and was found to influence overall damage assessment. The damage database and fragility functions for port industries can inform structural improvements and mitigation plans for ports against future events.

Abstract Following the eruption of Mount Anak Krakatau, a considerable landslide occurred on the southwestern part of the volcano and, upon entering the sea, generated a large tsunami within the Sunda Strait, Indonesia, on December 22, 2018. This tsunami traveled ~ 5 km across the strait basin and inundated the shorelines of Sumatra and Java with a vertical runup reaching 13 m. Following the event, observed field data, GPS measurements of the inundation, and multibeam echo soundings of the bathymetry within the strait were collected and publicly provided. Using this dataset, numerical modeling of the tsunami was conducted using the two-layer (soil and water) TUNAMI-N2 model based on a combination of landslide sources and bathymetry data. The two-layer model was implemented to nest the grid system using the finest grid size of 20 m. To constrain the unknown landslide parameters, the differential evolution (DE) global optimization algorithm was applied, which resulted in a parameter set that minimized the deviation from the measured bathymetry after the event. The DE global optimization procedure was effective at determining the landslide parameters for the model with the minimum deviation from the measured seafloor. The lowest deviation from the measured bathymetry was obtained for the best-fitting parameters: a maximum landslide thickness of 301.2 m and a landslide time of 10.8 min. The landslide volume of 0.182 km3 estimated by the best-fitting parameters shows that the tsunami flow depth could have reached 3–10 m along the shore with a K value of 0.89, although the simulated flow depths were underestimated in comparison with the observation data. According to the waveforms, the general wave pattern was well reproduced at tide gauges during the event. A large number of objective function evaluations were necessary to locate the minimum with the DE procedure to fix the grid cell size to 20 m; this limited the accuracy of the obtained parameter values for the two-layer model. Moreover, considering the generalizations in the modeling of landslide movements, the impact landslide time and thickness must be carefully calculated to obtain a suitable accuracy.

The 2004 Indian Ocean tsunami and the 2011 Tōhoku earthquake and tsunami caused large-scale topographic changes in coastal areas. Whereas much research has focused on coastlines that have or had large human populations, little focus has been paid to coastlines that have little or no infrastructure. The importance of examining erosional and depositional mechanisms of tsunami events lies in the rapid reorganization that coastlines must undertake immediately after an event. A thorough understanding of the pre-event conditions is paramount to understanding the natural reconstruction of the coastal environment. This study examines the location of sediment erosion and deposition during the 2004 Indian Ocean tsunami event on the relatively pristine Phra Thong Island, Thailand. Coupled with satellite imagery, we use numerical simulations and sediment transportation models to determine the locations of significant erosion and the areas where much of that sediment was redeposited during the tsunami inundation and backwash processes. Our modeling approach suggests that beaches located in two regions on Phra Thong Island were significantly eroded by the 2004 tsunami, predominantly during the backwash phase of the first and largest wave to strike the island. Although 2004 tsunami deposits are found on the island, we demonstrate that most of the sediment was deposited in the shallow coastal area, facilitating quick recovery of the beach when normal coastal processes resumed.

On 22 December 2018, a tsunami was generated from the Mount Anak Krakatau area that was caused by volcanic flank failures. The tsunami had severe impacts on the western coast of Banten and the southern coasts of Lampung in Indonesia. A series of surveys to measure the impacts of the tsunami was started 3 d after the tsunami and lasted for 10 d. Immediate investigations allowed the collection of relatively authentic images of the tsunami impacts before the clearing process started. This article investigates the impacts of the 2018 Sunda Strait tsunami on the affected areas and presents an analysis of the impacts of pure hydrodynamic tsunami forces on buildings. Impacts of the tsunami were expected to exhibit different characteristics than those found following the 2004 Indian Ocean tsunami in Aceh. Data were collected from 117 flow depths along the Banten and Lampung coasts. Furthermore, 98 buildings or houses were assessed for damage. Results of this study revealed that the flow depths were higher in Banten than in Lampung. Directions of the tsunami arrays created by the complex bathymetry around the strait caused these differences. Tsunami-induced damage to buildings was mostly the result of impact forces and drag forces. Damping forces could not be associated with the damage. The tsunami warning system in Indonesia should be extended to anticipate non-seismic tsunamis, such as landslides and volcanic processes driven by tsunamis. The lack of a tsunami warning during the first few minutes after the generation of the first wave led to a significant number of human casualties in both of the affected areas.

Tsunami fragility functions describe the probability of structural damage due to tsunami flow characteristics. Fragility functions developed from past tsunami events (e.g., the 2004 Indian Ocean tsunami) are often applied directly, without modification, to other areas at risk of tsunami for the purpose of damage and loss estimations. Consequentially, estimates carry uncertainty due to disparities in construction standards and coastal morphology between the specific region for which the fragility functions were originally derived and the region where they are being used. The main objective of this study is to provide an alternative approach to assessing tsunami damage, especially for buildings in regions where previously developed fragility functions do not exist. A damage assessment model is proposed in this study, where load-resistance analysis is performed for each building by evaluating hydrodynamic forces, buoyancies and debris impacts and comparing them to the resistance forces of each building. Numerical simulation was performed in this study to reproduce the 2011 Great East Japan tsunami in Ishinomaki, which is chosen as a study site. Flow depths and velocities were calculated for approximately 20 000 wooden buildings in Ishinomaki. Similarly, resistance forces (lateral and vertical) are estimated for each of these buildings. The buildings are then evaluated for their potential of collapsing. Results from this study reflect a higher accuracy in predicting building collapse when using the proposed load-resistance analysis, as compared to previously developed fragility functions in the same study area. Damage is also observed to have likely occurred before flow depth and velocity reach maximum values. With the above considerations, the proposed damage model might well be an alternative for building damage assessments in areas that have yet to be affected by modern tsunami events.

This research aimed to assess the tsunami flow velocity and height reduction produced by a planned elevated road parallel to the coast of Banda Aceh, called the Banda Aceh Outer Ring Road (BORR). The road will transect several lagoons, settlements, and bare land around the coast of Banda Aceh. Beside its main function to reduce traffic congestion in the city, the BORR is also proposed to reduce the impacts of future tsunamis. The Cornell Multi-grid Coupled Tsunami Model (COMCOT) was used to simulate eight scenarios of the tsunami. One of them was based on the 2004 Indian Ocean tsunami. Two magnitudes of earthquake were used, that is, 8.5 and 9.15 Mw. Both the earthquakes were generated from the same source location as in the 2004 case, around the Andaman Sea. Land use data of the innermost layer of the simulation area were adopted based on the 2004 condition and the land use planning of the city for 2029. The results of this study reveal that the tsunami inundation area can be reduced by about 9 % by using the elevated road for the earthquake of magnitude 9.15 Mw and about 22 % for the earthquake of magnitude 8.5 Mw. Combined with the land use planning 2029, the elevated road could reduce the maximum flow velocities behind the road by about 72 %. Notably, the proposed land use for 2029 will not be sufficient to deliver any effects on the tsunami mitigation without the elevated road structures. We recommend the city to construct the elevated road as this could be part of the co-benefit structures for tsunami mitigation. The proposed BORR appears to deliver a significant reduction of impacts of the smaller intensity tsunamis compared to the 2004 Indian Ocean tsunami.

Since the two devastating tsunamis in 2004 (Indian Ocean) and 2011 (Great East Japan), new findings have emerged on the relationship between tsunami characteristics and damage in terms of fragility functions. Human loss and damage to buildings and infrastructures are the primary target of recovery and reconstruction; thus, such relationships for offshore properties and marine ecosystems remain unclear. To overcome this lack of knowledge, this study used the available data from two possible target areas (Mangokuura Lake and Matsushima Bay) from the 2011 Japan tsunami. This study has three main components: (1) reproduction of the 2011 tsunami, (2) damage investigation, and (3) fragility function development. First, the source models of the 2011 tsunami were verified and adjusted to reproduce the tsunami characteristics in the target areas. Second, the damage ratio (complete damage) of the aquaculture raft and eelgrass was investigated using satellite images taken before and after the 2011 tsunami through visual inspection and binarization. Third, the tsunami fragility functions were developed using the relationship between the simulated tsunami characteristics and the estimated damage ratio. Based on the statistical analysis results, fragility functions were developed for Mangokuura Lake, and the flow velocity was the main contributor to the damage instead of the wave amplitude. For example, the damage ratio above 0.9 was found to be equal to the maximum flow velocities of 1.3 m s−1 (aquaculture raft) and 3.0 m s−1 (eelgrass). This finding is consistent with the previously proposed damage criterion of 1 m s−1 for the aquaculture raft. This study is the first step in the development of damage assessment and planning for marine products and environmental factors to mitigate the effects of future tsunamis.

Three weeks after the deadly Bohol earthquake of Mw 7.2, which claimed at least 222 victims, another disaster struck the Philippines. This time, Super Typhoon Haiyan, also known as Typhoon Yolanda in the Philippines, devastated the Eastern Visayas islands on 8 November 2013. Its classification as a super typhoon was based on its maximum sustained 1 min surface wind speed of 315 km h−1, which is equivalent to a strong Category 5 hurricane on the Saffir–Simpson scale. This was one of the deadliest typhoon events in the Philippines' history, after the 1897 and 1912 tropical cyclones. At least 6268 individuals have been reported dead and 1061 people are missing. In addition, a wide area of destruction was observed in the Eastern Visayas, on Samar and Leyte islands. The International Research Institute of Disaster Science (IRIDeS) at Tohoku University in Sendai, Japan, has deployed several teams for damage recognition, relief support and collaboration with regard to this disaster event. One of the teams, the hazard and damage evaluation team, visited the affected areas in the Eastern Visayas in mid-January 2014. In this paper, we summarize the rapid damage assessment from satellite imagery conducted days after the event and report on the inundation measurements and the damage surveyed in the field. Damage interpretation results by satellite images were qualitatively confirmed for the Tacloban city area on Leyte Island, the most populated city in the Eastern Visayas. During the survey, significant damage was observed from wind and storm surges on poorly designed housing on the east coast of Leyte Island. Damage, mainly from surface waves and winds, was observed on the east coast of Samar Island.

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 Coastal communities in various regions of the world are exposed to risk from tsunami inundation, requiring reliable modeling tools for implementing effective disaster preparedness and management strategies. This study advocates for comprehensive multi-variable models and emphasizes the limitations of traditional univariate fragility functions by leveraging a large, detailed dataset of ex-post damage surveys for the 2011 Great East Japan tsunami, hydrodynamic modeling of the event, and advanced machine learning techniques. It investigates the complex interplay of factors influencing building vulnerability to tsunami, with a specific focus on the hydrodynamic effects associated to tsunami propagation on land. Novel synthetic variables representing shielding and debris impact mechanisms prove to be suitable proxies for water velocity, offering a practical solution for rapid damage assessments, especially in post-event scenarios or large-scale analyses. Machine learning then emerges as a promising approach to tackle the complexities of vulnerability assessment, while providing valuable and interpretable insights.

On 27 February 2010, a megathrust earthquake of Mw = 8.8 generated a destructive tsunami in Chile. It struck not only Chilean coast but propagated all the way to Japan. After the event occurred, the post-tsunami survey team was assembled, funded by the Japan Science and Technology Agency (JST), to survey the area severely affected by the tsunami. The tsunami damaged and destroyed numerous houses, especially in the town of Dichato. In order to estimate the structural fragility against tsunami hazard in this area, tsunami fragility curves were developed. Surveyed data of inundation depth and visual inspection of satellite images of Dichato were used to classify the damage to housing. A practical method suitable when there are limitations on available data for numerical simulation or damage evaluation from surveys is presented here. This study is the first application of tsunami fragility curves on the South American Pacific coast and it might be of practical use for communities with similar characteristics along the west Pacific coast. The proposed curve suggests that structures in Dichato will be severely damaged – with a 68% probability – already at 2 m tsunami inundation depth.

The Pacific Ocean is the location where two-thirds of tsunamis have occurred, resulting in a great number of casualties. Once information on an earthquake has been issued, it is important to understand if there is a tsunami generation risk in relation with a specific earthquake magnitude or focal depth. This study proposes a Tsunamigenic Ratio (TR) that is defined as the ratio between the number of earthquake-generated tsunamis and the total number of earthquakes. Earthquake and tsunami data used in this study were selected from a database containing tsunamigenic earthquakes from prior 1900 to 2011. The TR is calculated from earthquake events with a magnitude greater than 5.0, a focal depth shallower than 200 km and a sea depth less than 7 km. The results suggest that a great earthquake magnitude and a shallow focal depth have a high potential to generate tsunamis with a large tsunami height. The average TR in the Pacific Ocean is 0.4, whereas the TR for specific regions of the Pacific Ocean varies from 0.3 to 0.7. The TR calculated for each region shows the relationship between three influential parameters: earthquake magnitude, focal depth and sea depth. The three parameters were combined and proposed as a dimensionless parameter called the Tsunami Index (TI). TI can express better relationship with the TR and with maximum tsunami height, while the three parameters mentioned above cannot. The results show that recent submarine earthquakes had a higher potential to generate a tsunami with a larger tsunami height than during the last century. A tsunami is definitely generated if the TI is larger than 7.0. The proposed TR and TI will help ascertain the tsunami generation risk of each earthquake event based on a statistical analysis of the historical data and could be an important decision support tool during the early tsunami warning stage.

The 2004 Indian Ocean tsunami damaged and destroyed numerous buildings and houses in Thailand. Estimation of tsunami impact to buildings from this event and evaluation of the potential risks are important but still in progress. The tsunami fragility curve is a function used to estimate the structural fragility against tsunami hazards. This study was undertaken to develop fragility curves using visual inspection of high-resolution satellite images (IKONOS) taken before and after tsunami events to classify whether the buildings were destroyed or not based on the remaining roof. Then, a tsunami inundation model is created to reconstruct the tsunami features such as inundation depth, current velocity, and hydrodynamic force of the event. It is assumed that the fragility curves are expressed as normal or lognormal distribution functions and the estimation of the median and log-standard deviation is performed using least square fitting. From the results, the developed fragility curves for different types of building materials (mixed type, reinforced concrete and wood) show consistent performance in damage probability and when compared to the existing curves for other locations.

Disaster risk in the 21st century differs from the experience of past generations and is defined by its evolving systemic nature. The increased role of technological networks, societal interdependencies and climate change dynamics make crises more complex and unpredictable. Cascading and compounding dynamics are becoming the new “business as usual”, challenging emergency management to maintain operations in face of complex disruptions while requiring the development of good practices and strategy for facilitate the recovery process. Our special issue aimed to support the development of a paradigm shift in the understanding of complex events, utilizing a network-based, cross-disciplinary approach to resilience. This editorial introduces and summarizes 18 papers across four thematic areas: 1) Resilience Challenges; 2) Area Studies and the Sendai Framework for Disaster Risk Reduction; 3) Community and Health; 4) Enhancing New Methodologies. The conclusions highlight open research challenges for future exploration.

On January 1 2024, at 16:10 JST, an earthquake of Mw 7.5 occurred underneath the Noto Peninsula of Ishikawa Prefecture, Japan. This event caused a cascading disaster impact on cities in the Noto Peninsula through a series of strong earthquake shakes, strong ground motions, slope failures, liquefaction, fire, and tsunamis. The tsunami first reached Suzu City a few minutes after the earthquake, eventually affecting approximately 340 km of the coast from the Ishikawa to Niigata Prefectures. The Coastal Engineering Committee of the Japan Society of Civil Engineers conducted an organized post-event field survey to understand the impact of tsunamis on land. This study summarizes the post-event field survey results and provides a general understanding of tsunami behavior and damage using measured tsunami inundation and run-up heights. [ABSTRACT FROM AUTHOR]

Building a resilient society is key to preparing for disasters beyond the planned scale. To achieve this, it is necessary to create a clear common understanding of what "resilient" disaster management means and to consider concrete methods to accelerate its social implementation. However, few opportunities have occurred to have these discussions with diverse stakeholders. Therefore, a panel discussion was held to consider the type of cooperation required to build a resilient society. Each speaker provided information from various perspectives, including emergency information, disaster prevention education, and scientific knowledge on the mechanism of tsunamis, and their impact on ecosystems. Based on the above, the panel discussion confirmed the need for various elements such as infrastructure, information, rules, and social structure. In particular, it is necessary to develop consistency with existing safety standards for disaster prevention using ecosystems. It was suggested that, in addition to the practice of education, cooperation with the media, which keeps up-to-date information on a long-term basis, is indispensable for raising awareness of disaster prevention. This panel discussion emphasized that disaster reduction is a difficult field for companies to enter and commercialize, however, it was emphasized that it is indispensable worldwide. [ABSTRACT FROM AUTHOR]