We are pleased to edit this special issue, National Research Institute for Earth Science and Disaster Resilience (NIED) Frontier Research on Science and Technology for Disaster Risk Reduction and Resilience 2025, at the timing after the Noto Peninsula disasters in 2024 as well as the launch of the Nankai Trough Seafloor Observation Network for Earthquakes and Tsunamis (N-net) in 2025. The Noto Peninsula was seriously damaged not only by the earthquake in January but also by a record-breaking rainfall in September. In addition, Aomori Prefecture was very much damaged by heavy snowfall in the winter of 2024–2025. These events indicated that awareness, preparedness, monitoring, early warning and response are important to improve capacity of societies, which are vulnerable to various natural hazards to reduce disaster risk and enhance resilience. This special issue includes ten articles (eight papers, one survey report, and one review), addressing above-mentioned issues.

Since the 2024 Noto Peninsula earthquake clearly demonstrated that ports are critical lifelines for disaster response and logistics, Dohi et al. assess the seismic uplift risks to ports, focusing on the Nankai Trough earthquake. Fujita et al. explore the feasibility of using multi-sensing data to ensure a rapid response to isolated settlements based on the 2024 Noto earthquake. Chiba et al. investigate societal expectations regarding mechanisms that encourage small and medium enterprises (SMEs) to adopt business continuity measures, as many SMEs have limited awareness and resources. Yamazaki-Honda reviews the land-use regulations in Japan and suggests that it is crucial to establish a spatial disaster risk reduction master plan with a defined timeline to effectively reduce exposure to disaster risks. Nagashima et al. present inversion analyses to improve hypocenter determination and earthquake magnitude assessment in the sea area, using the Japan Trench S-net, which is a part of Monitoring of Waves on Land and Seafloor (MOWLAS) including the N-net. Takaya et al. and Nishi et al. evaluate the damage risks of seismic motion to air conditioning systems and building equipment, using the E-Defense, a world No. 1 large-scale shaking table operated by NIED. Based on the 2016 event in Hokkaido, Akita reveals that riverbank erosion and landslides played major roles in sediment runoff during extreme rainfall. Ishizawa and Danjo propose a method to detect precursory signal of shallow landslides using observations from Typhoon Hagibis in 2019. Tamura examines the temperature changes affecting an increase in snowfall during early winter and rapid snowmelt in early spring.

We believe that these articles will provide valuable insights for readers and contribute to building a resilient society capable of withstanding and responding to catastrophic earthquake and extreme weather disasters.

Advance countermeasures are crucial to address future great earthquakes along the Nankai Trough. Damage caused not only by strong ground motion and tsunami but also by coseismic uplift was reported following previous major earthquakes. If coseismic uplift causes a port to cease to function, there is concern regarding the impact on fisheries and logistics, and whether it can function as a disaster-management base, e.g., for transporting emergency goods and evacuating residents. To understand the characteristics of coseismic uplift on ports, we analyzed coseismic uplift on ports for great earthquakes along the Nankai Trough. Specifically, considering the variety of great earthquake occurrences along the Nankai Trough, we analyzed the amount and likelihood of coseismic uplift for more than 900,000 occurrence patterns and discussed the extent of port functioning as a disaster-management base. This study revealed that, when an M9-class earthquake occurs, some emergency relief ships may not be able to berth at ports positioned as disaster-management hubs. Additionally, when an M8- to M9-class earthquake occurs, some ports may not function to the same extent as before. The results of this study and related discussions, such as ports’ function as disaster-management bases and the impact on fisheries and logistics, are expected to contribute to the advancement of effective preparedness and countermeasures for ports against future great earthquakes along the Nankai Trough.

In the event of a disaster, the occurrence of isolated settlements necessitates prompt responses, including rescue operations, medical transport, and the delivery of essential supplies. However, it is often challenging to quickly identify which areas are isolated. This study developed a method for estimating isolated settlements during earthquake disasters using multi-sensing data. An accuracy evaluation based on data from the 2024 Noto Peninsula earthquake revealed an overlook rate of approximately 60% and a mistaken estimation rate of approximately 20%. By incorporating actual road traffic data, the estimation was refined to extract settlements at high risk of isolation. Moreover, the method successfully identified isolated settlements that were not reported in official damage reports, indicating relatively high estimation accuracy. This capability is expected to assist disaster management headquarters in identifying priority areas for emergency response. Because the data used in the proposed method can be obtained during actual disaster events, the estimation process can be initiated promptly across Japan immediately after an earthquake, thereby enabling the timely provision of valuable information for disaster response. This analysis presents the necessary data and computational approaches for improving estimation accuracy and supporting practical implementation in disaster management. In the future, advancements in various sensing technologies and the development of data-sharing frameworks are expected to facilitate even more accurate estimations.

In Japan, risk of disasters at the national level, such as the Nankai Trough Earthquake, has increased. However, it is unlikely that many small and medium enterprises (SMEs) would proactively take business continuity responses, as they have low recognition of and priority for disaster risk, and their management resources are limited. To improve outcomes in such situations, discovering social expectations of mechanisms and functions needed to urge SMEs to take action for business continuity is essential; this can be incorporated into disaster management technology. This report summarizes the study of social expectations discovered through utilizing the disaster management technology, a simplified disaster risk evaluation tool for earthquakes, developed by the National Research Institute for Earth Science and Disaster Resilience. First, this report describes the background and significance of focusing on SMEs. Thereafter, it reviews previous studies on disaster risk evaluation for businesses, discusses the methodology to construct the disaster risk estimation method, develops an online tool, and discovers social expectations. Finally, it presents the results of the social expectations obtained by applying this methodology.

Land use regulations and controls in Japan have evolved in response to the needs and changes in the social background, as well as experiences of substantial disaster losses and damage. With the unprecedented scenario of an aging and depopulating society, as well as impacts of climate change: Target hazards have been expanded in terms of hazard type, disaster cause, and assumed scale. Target area designation has been expanded to include presumed affected areas, and regulated development and construction have been expanded to reduce exposure to disaster risk. More recently, necessary soft measures such as securing warning and evacuation systems have been additionally integrated. Despite the advancement of risk-informed land use regulations and controls in Japan, their practical implementation has been challenged due to social, institutional, and legal constraints. In practice, area designation has not been fully implemented due to insufficient capacities in terms of technical and financial resources at the local level. Although land use restrictions have promoted relocation and retrofit of buildings, they do not have an immediate effect to change exposure; therefore, a spatial master plan of disaster risk reduction with a timeline is imperative. While the government improves risk information and communication, people and society, as recipients of information, should strengthen their capacity to understand risk at all times and take necessary actions in times of disaster, through a multi-hazard approach in a multi-stakeholder framework. In the long run, systems are required that could transform the entire national land structure into a more resilient, “autonomous, decentralized, and coordinated” structure from a broader perspective.

Since underground structures in the sea area are difficult to observe, they are not well examined. To estimate underground structures beneath Seafloor Observation Network for Earthquakes and Tsunamis along the Japan Trench (S-net), which was installed in the sea area between the Japanese islands and the outer rise of the Japan Trench, horizontal-to-vertical spectral ratios of earthquake motions (EHVRs) recorded at S-net sites were calculated, and the EHVRs were inverted to obtain one-dimensional seismic velocity structures. The effect of reflected waves from sea surface was not found on the observed EHVRs; however, the sharp trough and directional dependency, possibly owing to the seismometers’ installing situation, were found on the observed EHVRs. Inversion analysis of the observed EHVRs based on the diffuse field concept for earthquake was performed within 0.1–3.0 Hz avoiding the sharp trough and the directional dependency. The observed EHVRs were well reproduced by the resultant seismic velocity structures. The travel times for S- and P-waves from the seismic bedrock (S-wave velocity =3100 m/s) to the seafloor were calculated from the identified structures, and it was distributed between 2.8 s and 3.8 s for S-wave velocity and 0.9 s and 1.3 s for P-wave velocity. Comparing the identified structures with previous studies revealed similar depths to seismic bedrock; however, some discrepancies were noted. Such correspondences and discrepancies exhibit the validity and limitation of our inversion models. The possible causes of discrepancies are the difference of the observed data, the target frequency range, and the inversion conditions. Therefore, in the future, more detailed investigations should be performed.

Earthquake damage to building equipment lowers the functionality of the building and makes it difficult to continue its operation. Methods have been proposed to assess the performance of a building via a probabilistic view of the damage or repair costs for its structural and nonstructural components in the event of earthquakes, to assess the functionality of the building against earthquakes. In these methods, damage to the components is expressed by probability distributions (fragility curves) of the damage against the response of the building frame. However, actual damage to building equipment occurs as a result of the response of the equipment, which varies with the vibration characteristics of the building and the input seismic motions. Furthermore, the relation between the equipment response and damage based on dynamic models has not been quantified or sufficiently verified experimentally. In this study, shaking table tests were conducted on three types of air-conditioning units to investigate their dynamic characteristics and assess their damage. Additionally, a dynamic model that reflects the degree of fixation of a hanging-support air-conditioning unit to the support members was analyzed, and its predictions were compared against experimental data to quantitatively evaluate the relation between the initial damage to support members and the response acceleration of units, with the goal of producing fragility curves for building equipment.

To maintain the functionality of a building, it is crucial to understand the seismic behavior of its equipment and evaluate its seismic performance accurately. To enhance the precision of seismic performance evaluations, it is necessary to expand the fragility data for building equipment. This study explores a method for developing a fragility function based on the seismic design force specified in design guidelines. Using risk integrals, the study assesses the relationship between acceleration and damage probability, derived from earthquake damage surveys, to calculate the damage risk for building equipment designed and constructed according to Japanese design standards. The fragility function is then derived by analyzing the damage probability when the response acceleration exceeds the design acceleration. Additionally, through a comparative verification with shake table test results from a full-scale 10-story steel office building, the authors confirm the consistency between the derived fragility functions and experimental results. This approach is expected to improve the accuracy of predicting building equipment seismic behavior and provide more reliable seismic performance evaluations.

This study provides a quantitative assessment of sediment dynamics associated with newly formed landslides and river channels in the Pankenushi River basin (95.8 km²), part of the Saru River system in Hokkaido, Japan. The analysis focuses on the impacts of the torrential rainfalls induced by four typhoons, including Typhoon Lionrock, which occurred between August 17 and 31, 2016. Using satellite imagery and laser profiler (LP) measurements, the study quantifies the spatial extent and volumetric changes in sediment dynamics. The areas affected by newly formed landslides and river channel disturbances were identified by analyzing changes in the normalized difference vegetation index calculated using images from before and after the heavy rainfall events. In the middle and lower reaches of the river, where channel disturbance was pronounced, LP measurements conducted in 2012 and 2019 were used to estimate topographic changes resulting from the rainfall and runoff. Sediment erosion volume was estimated at approximately 880,000 m³, approximately three times greater than the volume of channel deposits (310,000 m³) and about five times greater than the volume supplied by shallow landslides in the upper basin. These findings indicate that riverbank erosion, in addition to landslides, plays a substantial role in sediment runoff during extreme rainfall events, such as that in August 2016.

Shallow landslides caused by heavy rainfall pose significant hazards in mountainous Japan, necessitating improved early warning methodologies. Despite technological advances, the quantitative understanding of failure mechanisms based on comprehensive field observations remains limited. This study presents a multi-parameter monitoring system to detect precursory phenomena and proposes a two-stage estimation methodology based on a shallow landslide triggered by Typhoon Hagibis in 2019. The system combined rainfall gauges, inclinometers, soil moisture sensors, and tensiometers with 10-minute recording intervals. Analysis revealed relationships between groundwater level rise and displacement development, with initial movement occurring at critical groundwater thresholds and a two-phase deformation process corresponding to soil stratification. The proposed approach enables continuous monitoring during normal conditions and quantitative evaluation before failure. The first stage analyzes historical data to estimate instability progression based on hydraulic threshold monitoring, while the second stage applies the inverse velocity method to estimate failure time with excellent statistical reliability (R²>0.9) and ±15-minute accuracy using post-acceleration data. This methodology provides a framework for real-time monitoring, demonstrating that shallow landslides develop through temporally staged deformation processes triggered by groundwater fluctuations.

Global warming has led to significant changes in regional climates, including rising temperatures and altered precipitation patterns. This study investigates regional temperature variations in Japan, focusing on differences between early winter and early spring. An analysis of temperature trends over the past century shows that March exhibits the strongest warming trend, while December shows the weakest. Since the 2000s, the contrast in temperature trends between March and December has become more pronounced. This recent seasonal divergence is associated with changes in large-scale pressure patterns. Despite ongoing global warming, early winter shows no significant changes in surface pressure patterns. In contrast, early spring is marked by a surface pressure pattern that weakens the winter monsoon. Notably, cold early winters may increase snowfall, while warm early springs can accelerate snowmelt—both of which heighten the risk of snow and ice disasters.

The World BOSAI Forum 2025 (WBF2025) was successfully convened from March 7 to 9, 2025. According to the event report of the WBF2025 [1], the forum welcomed 5,434 participants over the three days, including 1,197 pre-registered attendees for the main conference and visitors to the EXPO and side events, ultimately representing 34 countries. The venue featured 46 oral sessions, two workshops, 41 poster presentations, 19 mini-presentations, and 85 exhibition booths. This provided a valuable opportunity for international organizations, governments, academia, industries, NGOs, and citizens to gather in one place, discuss concrete solutions for disaster risk reduction (DRR), and share these insights with the world. The main theme of WBF2025 was climate change, and 13 related sessions were held. One of the forum’s distinctive features was the chance to experience the forefront of global DRR while in Japan, which was facilitated via three sessions hosted by UN-related organizations and five by overseas participants.

The guest editors are pleased to publish this special issue in the Journal of Disaster Research, which comprises five notable articles that share the research advancements presented in the following oral sessions at the WBF2025:

• Toward the Utilization of the Intermediate Function of Local Academic Institutions in the Field of Disaster Risk Reduction in Indonesia

• Towards an Assessment of Loss and Damage Associated With Climate-induced Migration in Indonesia

• Measuring Resilience: Strategy Development and Empirical Analysis

• Utilizing Web GIS to Enhance School Safety for Disaster Risk Reduction—Initiatives in Japan and Taiwan—

We hope that this special issue on the WBF2025 will contribute to the literature on disaster science and further advance DRR and climate change adaptation.

References:

[1] World BOSAI Forum, “Event Report,” 2025 (in Japanese). https://worldbosaiforum.com/media/files/_u/wbf2025/世界防災フォーラム開催報告書_ver1.pdf [Accessed September 14, 2025]

Despite growing recognition of universities’ critical role in building disaster-resilient communities, limited empirical research has examined university lecturers’ actual engagement with disaster risk reduction (DRR) initiatives, particularly in disaster-prone developing regions, where the Sendai Framework for Disaster Risk Reduction 2015–2030 emphasizes educational institutions’ pivotal role in community resilience. This study investigates university lecturers’ experiences, perceptions, and engagement patterns in DRR activities across the western region of Java island, Indonesia, through a cross-sectional survey of 411 lecturers from national and private universities across Banten Province, Jakarta, and West Java Province. The validated questionnaire assessed DRR experiences, knowledge levels, engagement patterns, perceptions, and institutional support using a 5-point Likert scale. Statistical analysis included descriptive statistics, Kruskal–Wallis tests for regional comparisons, and Wilcoxon–Mann–Whitney tests for demographic group differences. Results revealed strong support for academic DRR involvement, with approximately 80% agreeing that academics should engage in research, community outreach, and policy development. However, actual participation levels varied significantly, with Jakarta lecturers demonstrating richer DRR experiences compared with Banten or West Java counterparts. Gender, age, education level, and academic discipline significantly influenced engagement, with humanities majors indicating more positive perceptions than science majors, while duration of DRR involvement emerged as a critical factor affecting both experiences and perceptions across all measured dimensions. This study reveals substantial untapped potential for academic engagement in DRR initiatives, suggesting universities should develop systematic professional development programs, establish clear institutional pathways for lecturer participation, and ensure equitable resource distribution across regions to strengthen disaster resilience building efforts while supporting Sendai Framework implementation goals.

This study investigates the root causes of loss and damage in climate-vulnerable coastal communities, or kampungs, in Greater Jakarta, highlighting how climatic stressors interact with local development pathways. Drawing from in-depth discussions with 64 informants in North Jakarta and Tangerang Regency, representing four and one selected kampungs, respectively, this study analyzes how environmental degradation, urban growth, and relocation pressures have affected kampung residents. The findings reveal spatial contestation, inequality, precarious livelihoods, and injustice, which together intensify vulnerability and lead to unavoidable impacts of climate change. These dynamics are shaped by exclusionary development processes, unequal adaptation impacts, and a lack of inclusive decision-making with communities. Using the conceptual framework of critical vulnerability theory, this research illustrates how governance and power relations influence both urban coastal risk and adaptive capacity. The study provides insights on justice-oriented and equitable approaches to addressing loss and damage in rapidly urbanizing areas in Southeast Asia.

In the context of increasing climate-related disasters, transformative resilience encompassing adaptation, innovation, and sustainability has emerged as a critical concept for strengthening community-level resilience. This systematic literature review (following PRISMA guidelines) synthesizes insights from 39 peer-reviewed studies (2016–2025) to assess how transformative resilience is conceptualized and measured. It aims to inform evidence-based strategies for strengthening community-level resilience to climate change. Findings indicate that adaptation strategies dominate the literature, often focusing on socio-ecological resilience and adaptive capacity indicators. However, recent studies increasingly advocate integrated frameworks that combine adaptation with innovation and sustainability to achieve transformative outcomes. Commonly used indicators include socio-ecological resilience metrics, social capital, and adaptive capacity, although their definitions and measurements vary widely across studies. Key knowledge gaps were identified: notably, standardized measurement tools for transformative resilience are lacking, and insufficient attention has been paid to governance and institutional transformation in resilience efforts. These gaps underscore the need for future research to develop standardized indicators and holistic frameworks that address multi-level governance and institutional change. The findings have implications for both research and policy, suggesting that evidence-based, cross-sectoral strategies are required to bolster community-level resilience in the face of climate change.

This study reviews the evolution of the “disaster resilience” concept and attempts to draw implications for disaster risk reduction from it. First, the concept of disaster resilience was influenced by ecology and brought into disaster management research as a concept of system stability. The irreversible damage caused by Hurricane Katrina in the U.S. has led to disaster resilience being considered not as the ability of a society to “bounce back,” but as the ability of a society to adapt to or transform toward a desirable future. However, the inclusion of transformative capacity in the resilience concept raises several issues in disaster risk reduction practice. Finally, it creates three conflicts: between transformative and maintaining capacity, between the subjects of resilience, and sometimes between transformative capacity and societal values such as justice and equality. This study suggests three conditions that justify transformation under the name of resilience: (1) sustainability, (2) welfare, and (3) dignity.

This study investigates the integration of geographic information systems (GIS) into school disaster risk reduction (DRR) practices, with a specific focus on Taiwan’s School Safety GIS platform. Drawing comparisons with current practices in Japan, this paper highlights the central role of Web-GIS in visualizing hazard risks, enhancing school safety management, and promoting spatial thinking among educators. The case study of Taiwan demonstrates a centralized and systematically updated GIS platform that facilitates comprehensive risk assessments, real-time hazard alerts, and the integration of multi-source governmental data. These findings underscore the importance of geographic literacy, data integration, and inter-agency collaboration for effective DRR in schools. The implications for Japan point to the need for unified GIS adoption and expanded teacher training.

The community-based preparedness approach to disaster risk reduction has gained importance within the field of disaster management. It emphasizes the important roles and responsibilities of community members in creating disaster management programs and systems, ensuring self-confidence, and reducing vulnerability during disasters. A significant portion of this resilience is made up of volunteers. In this study, the experiences of volunteers who went to disaster areas at different times to support search and rescue and humanitarian aid services were examined. Phenomenological design, which is a qualitative research design, was used in this study. The research group consists of volunteers working at Kocaeli University who went to the region after the February 6, 2023 earthquakes and stayed for more than 7 days. The data were obtained through semi-structured interviews. The data were grouped under 2 main themes, Humanitarian Aid and Search and Rescue, and 155 codes were produced. It is observed that the participants who went to the region for humanitarian aid focused on coordination problems, organizational weaknesses, and problems arising from people who were in the region for different purposes. Participants who went to the region for search and rescue reported that there were coordination and security problems after the two major earthquakes affecting 11 provinces, and that heavy traffic in the disaster region made transportation from the crisis coordination center to the field difficult. Suggestions based on participant experiences focused on raising awareness of volunteering, taking psychological first aid into consideration in volunteer training, and strengthening the search and rescue capacities of institutions.

Indonesia, situated at the convergence of four major tectonic plates, has historically been prone to significant seismic activity. In response, the country has adopted Disaster Risk Financing and Insurance (DRFI) as a strategic approach to managing funds, particularly for post-disaster recovery, which poses significant budgeting challenges. This study conducted a detailed seismic risk assessment specifically aiming to enhance the management of funds designated for housing damage recovery after earthquakes. Employing downscaling exposure models and event-based seismic risk assessments, this study estimates the value of earthquake-affected residential properties in Indonesia at the sub-district level to be USD 380.6 billion as of 2022. Subsequent risk analysis employing the event-based seismic risk model produced a hazard map, an exceedance probability curve, and an average annual loss map, indicating an average annual loss ratio of 0.1035% relative to the total exposure. The accuracy of the model was validated using historical event loss data from the 2022 Cianjur earthquake, achieving a mean absolute percentage error of 3.0% at the regency level. This precision level confirms its utility in estimating funds necessary for housing recovery initiatives at this administrative level. The findings support the model’s reliability in assessing the risks associated with funding for earthquake-induced damage up to the regency level and suggest its potential to refine DRFI policies. This model is expected to enhance the effectiveness and inclusiveness of disaster finance strategies in Indonesia.

El Salvador’s seismic design code has remained unchanged for over 28 years, and neither a geophysical nor a soil-column database has been developed. For that sake, the horizontal-to-vertical spectral ratios (HVSR) were computed from 383 microtremor records collected across the western districts of San Salvador City and an adjacent municipality. The results were compared to the theoretical HVSR and transfer functions derived from multichannel analysis of surface waves data provided by the Ministry of Public Works of El Salvador. Subsequently, maps of HVSR amplitude, predominant period, and fundamental (first) period were generated using the Kriging interpolation technique. This approach was selected for its ability to more accurately reflect the spatial variability of geological conditions, particularly those associated with the Plan de la Laguna extinct caldera.

Global environmental change threatens human society and accelerates land degradation by humans’ excessively and inappropriate use of natural resources. The complexity of the human-environmental system and its cascading effects were highlighted by the Intergovernmental Panel on Climate Change’s 2022 report, which pointed to the increasing severity of climate change and its risks to society and ecosystems. However, most disaster management policies are focused on constructing hardware prevention engineering, which lacks the concern to reduce rooted disaster risks incubated by harmonious human-land relationships in local contexts. This study uses a Seediq tribal community that faces compound disaster risks, Alang Tongan, as a case study to demonstrate that effective long-term disaster risk reduction begins with cultivating a holistic and respectful relationship between people and the environment. Participant observation and in-depth interviews are used to collect first-hand data and understand the nexus relationships among ecological restoration, cultural revitalization, economic recovery, and disaster risk reduction. Results show that local knowledge-inherent disaster risk reduction strategies enable communities to respond to and learn from environmental dynamics. These strategies foster a resilient social-ecological system and highlight its capacity for reorganizing into a more robust-but-resilient state. This study concludes that social-ecological resiliency is critical for communities facing disaster risks. Therefore, nature-based solutions that integrate local knowledge, agricultural livelihoods, and sustainable land circulation practices can enhance adaptive capacity in response to environmental threats.

This study advances emergency management research by systematically examining the dynamic evolution of core–periphery structures in disaster response networks using the 2022 Luding earthquake as a case study. Unlike prior work focused on static comparisons of centralized versus decentralized networks, we employ longitudinal social network analysis to reveal how core–periphery configurations shift across disaster phases—a methodological innovation that captures real-time adaptation. Our findings demonstrate that effective emergency networks require phase-specific structures: highly centralized cores dominate rescue operations for rapid coordination while specialized, resource-controlling nodes emerge during recovery. In the case study, only three organizations maintained core status across both stages, highlighting the fluidity of network roles and challenging assumptions about fixed hierarchies. This study identifies an optimal balance between core dominance and peripheral flexibility, with excessive centralization or fragmentation impairing performance. These results provide empirical support for adaptive governance approaches and offer practical strategies for designing flexible emergency systems, including phase-sensitive resource allocation and dynamic role transition protocols. By bridging theoretical gaps in network evolution and delivering actionable insights, this research contributes to more resilient disaster response frameworks.

In the 2011 Great East Japan Earthquake, thermal and nuclear power plants were simultaneously damaged, resulting in a rapid decline in power supply capacity, which necessitated the implementation of planned power outages to forcibly reduce power demand. Subsequently, Japanese power sector administrations established policies for planned power outages following large-scale disasters. Meanwhile, the potential occurrence of the Nankai Trough earthquake raised concerns, as this earthquake may lead to power shortages exceeding those experienced during the Great East Japan Earthquake. This study aims to assess the production impacts and explore countermeasures for the manufacturing industry, which would face significant impacts from long-term planned power outages. Focusing on the Kansai region, which is expected to sustain relatively minor direct damage from the Nankai Trough earthquake, this study establishes scenarios of planned power outages and identifies the impacts on manufacturing industries under such conditions through a questionnaire survey. Based on the findings, the study discusses the directions for countermeasures from the perspectives of both companies and power sector administration to mitigate the impacts of planned power outages.

To meet the growing need for accurate and timely tsunami height predictions, a database comprising 3480 high-precision tsunami simulation scenarios for the Nankai Trough was constructed in this study. The database includes the Dense Oceanfloor Network for Earthquakes and Tsunamis (DONET) seafloor pressure sensor data and the maximum tsunami heights for 19 coastal cities. Gaussian process regression with automatic relevance determination (ARD) was used to quantitatively evaluate the effectiveness of each sensor location. In this framework, the ARD assigns a hyperparameter that functions as an indicator of the contribution of each sensor to the prediction. The proportion of this hyperparameter reflects the effectiveness of each sensor during the prediction process. The results demonstrated that removing the 20 least effective sensors (as identified by the ARD) led to an 11% increase in the estimation error, whereas removing the 10 most effective sensors resulted in a 38% increase. These results demonstrate that the proposed method enables the optimization of the sensor placement process and allows for a prior evaluation of the trade-off between the number of sensors and achieved prediction accuracy. This method offers a robust framework for optimizing observation networks, enhancing the accuracy of tsunami predictions, and supporting future disaster risk reduction.

More than 14 years after the Great East Japan Earthquake, aiding each survivor to reconstruct their lives and recover both physically and mentally still remains a social and political issue. Among the multidimensional elements of post-disaster rebuilding, life recovery feelings are crucial, as they deeply reflect the recovery of victims’ subjective worlds in comparison to their pre-disaster lives. While previous studies have identified neighborhood networks as a key factor shaping these feelings, few have empirically unpacked identifiable mechanisms of how neighborhood networks enhance life recovery feelings. Therefore, this study investigates the effects of neighborhood networks on survivors’ life recovery feelings following the Great East Japan Earthquake from the following perspectives: (a) to formalize the identifiable mechanisms of forming and increasing information and material exchange networks to facilitate life recovery feelings, (b) to use longitudinal survey data that adequately capture post-disaster changes, (c) to correct selection bias via a multiple imputation technique, and (d) to control for time-varying factors and time-invariant unobserved heterogeneity using fixed-effects models. The statistical results reveal that the formation of information exchange networks with neighbors after the disaster enhanced victims’ life recovery feelings, which suggests the importance of ending victims’ social isolation from their communities in disaster recovery processes.