The accuracy of numerical simulations of a landslide-induced tsunami depends on the landslide characteristics, such as landslide geometry and geotechnical parameters. However, owing to the difficulty in sampling and measuring submarine landslides, rough assumptions of landslide parameters typically lead to significant uncertainties. In the 2018 Palu event, the earthquake was followed by immediate cascading disasters of coastal subsidence, both land and submarine landslides and a tsunami. This scenario provides opportunities to analyze landslide phenomena on land to characterize the submarine landslide causing the tsunami. This study proposes a new approach of using shear-stress parameters obtained from liquefaction analyses as input for landslide-induced tsunami simulation. To obtain the submarine landslide parameter, using the finite element method we modeled the liquefaction happened in Jono-Oge located near Palu Valley area. The shear-stress in this area was quite small with the range 1.5–3.5 kPa. We found that tsunami simulation yielded better accuracy by applying the stress value range obtained from the liquefaction analysis on land (1.5 kPa) rather than the typically adopted stress value for general cases (20 kPa). The result from the tsunami simulation using two-layer method with identical landslide location and geometry showed that shear-stress value of landslide mass gave quite a significant effect to the tsunami height.

This study examined the impact of coronavirus disease 2019 (COVID-19) on Japanese expatriates living in China. The survey period was from March 30 to July 31, 2021; responses were received via an online survey. An online survey gathered responses from 236 participants about the impact of COVID-19 on their work and life. While 80% of the participants responded that COVID-19 had impacted their work and life, 60% said that it had a physical or mental impact. Kruskal–Wallis test and Mann–Whitney U test were conducted to compare the effects of COVID-19 on job performance, including personal attributes. The impact of COVID-19 was associated with gender (p = .007), age (p = .010), occupation (p = .005), job title (p = .009), and living arrangements with or without a partner (p = .005). The impact was also correlated with age (p = .030), job position (p = .014), number of times the respondent had lived in Japan (p = .003), and number of years in Japan (p = .015). The most significant effect on mental and physical health was correlated with job position (p = .016). Thus, Japanese expatriates living in China were substantially affected by the COVID-19 epidemic; although, 60% of them said their region was easy to live in. Further, despite the Chinese government’s strict isolation orders, they found the thorough testing and use of the coronavirus tracking app reassuring. This suggests the importance of providing not only mental care for expatriates during the COVID-19 epidemic but also prompt decision-making based on an accurate understanding of the local situation.

The occurrence rate of a subsequent earthquake is estimated to become a hundred times more than that at ordinary times when a case of partial rupture of the Nankai Trough Earthquake occurs. Companies and organizations that play a key role in social activities should take practicable actions positively in cooperation with relevant actors. Their recommended correspondences would be different by area according to the influence level by the subsequent partial rupture earthquake. Areas would be classified into three types: 1) strong earthquakes and tsunami are anticipated, 2) strong earthquakes without tsunami are anticipated, and 3) neither strong earthquakes nor tsunami is anticipated (this area should contribute as a supporter). There is also difference depending on business character and industry type. Therefore, it would be effective to examine the responses in the case of partial rupture, counting these differences in, and based on their business continuity plans (BCP). The authors will propose a recommended correspondence method (“recipe”) as an example of this means. In addition, there should be recommended actions of companies and organizations such as their operations not preventing evacuation and stockpiling in the local communities.

As a countermeasure against M8–9 class Nankai Trough earthquakes, the Japan Meteorological Agency started a service to release “Nankai Trough Earthquake Extra Information (Megathrust Earthquake Alert).” This alert is released after an M8.0 or higher earthquake occurs and the possibility of a subsequent earthquake is evaluated to be higher than usual. This is an innovative attempt at disaster mitigation in Japan as it encourages residents in the predefined area to pre-evacuate for one week when tsunami risk is higher. However, the factors influencing the evacuation behavior of residents are unknown. In this study, we investigated factors contributing to residents’ pre-event evacuation intentions using the hierarchical multiple regression analysis. We focused on the extent to which the recognition of the hazards and risks of the Nankai Trough earthquake and the response to the Extra Information, which are changeable by the local governments’ public relations activities, contributed to pre-event evacuation intentions after controlling for disaster-related general attitude and sociodemographic factors. Further, we paid special attention to residents’ degree of recognition of this information by checking the accuracy of their understanding of whether they lived within the pre-event evacuation area. The results showed that the recognition factors were relevant but less so than the general attitude toward disaster and more so than the sociodemographic factors. In addition, residents’ recognition accuracy was low. Our results suggest that it is important for local governments to make adequate efforts to encourage residents to evacuate.

To understand the workload of house cleanup and related workforce shortage after a disaster, the actual work situation in disaster-stricken areas is accounted for by disaster volunteer work management data created by the Disaster Volunteer Center of Joso City in Ibaraki Prefecture at the time of the Kanto–Tohoku Heavy Rain Disaster in September 2015. Using the classification of inundation depth, judged from ground elevation, the weekly workload of house cleanup according to the work content is recorded to clarify the characteristics of each area. Comparing this with the inundated areas without destructions by water flow, near the bank break with house destructions, in the urban area, and around the farmland along the old road, a model to estimate the workload is constructed. It was observed that indoor work to recommence living in urban areas continued for a long time, while the work was completed in a relatively short time in the area along the old road. The area near the bank break, with a small number of houses, witnessed very few house destructions. Hence, it is not necessary to separately calculate the workload caused by house destructions. The appropriateness of the estimated results was verified by using a method to estimate the workload based on the amount of disaster waste. As a result, the total workload estimated by disaster volunteers and victims for the busy period of two months was a million people. In the case of the Joso City flood, very few houses were completely destroyed, therefore, regular living could be resumed swiftly and people settled there after the disaster due to its proximity to the metropolitan area. Hence, the population decreased by the flood was recovered in two years.

Learning from the Great East Japan Earthquake, the Japanese government enacted the “Tsunami Disaster Prevention Community Development Law.” Following the law’s enactment, local prefectures could designate areas that required special preparation for tsunami disasters as “tsunami disaster alert areas.” However, more than 10 years after the law’s enactment, only about half of the prefectures with estimated tsunami inundation have designated disaster alert areas. One reason for this lack of progress is that it is difficult to reach a consensus owing to concerns regarding falling land prices caused by rumors. Thus, this study presents an empirical analysis of the impact of designating tsunami disaster alert areas on land prices. The difference in land prices between designated tsunami disaster alert areas and other areas is analyzed using the difference-in-difference and propensity score matching methods, using data on 26 prefectures. The eight prefectures in the “treatment group” were designated as tsunami disaster alert areas before 2018. The other prefectures are assigned to the “control group.” The results show a significant difference between designated tsunami disaster alert areas and other locations. The results are confirmed in kernel matching bandwidths of 0.06 for the entire sample, sample of only residential use, and sample of an estimated tsunami inundation depth below 2 m. Thus, this study concludes that before designating tsunami alert areas, local prefectures must carefully consider the impact of such designation on land prices.

Hydraulic fracturing (HF) in a dam is the phenomenon of crack propagation after water pressure enters and expands an existing crack. An HF numerical model was tested on an existing dam on a complex foliated rock foundations. The locations and areas of HF could be identified, leading to the development of the hydraulic fracturing index (HFI). The results revealed that the HF area mainly occurred in syncline concave areas on rock foundations. The expansion of HF significantly affected the seepage and the stability of the dam. The HF area on a studied dam mainly started to occur when the reservoir water level (RWL) reached 146.00–156.00 m mean sea level (MSL). These results agreed well with the piezometric monitoring data recorded as 148.00–149.00 m MSL. The findings supported the formulation of the HFI based on the influencing factors of the cross-valley geometry, RWL, dam height, and elastic modulus of the rock foundation. The probability of HF occurrence could be evaluated and categorized for safety evaluation into five conditions: ≤0.14 (very unlikely), 0.15–0.74 (unlikely), 0.75–1.86 (neutral), 1.87–3.10 (likely), and ≥3.10 (very likely). The HFI can be used to predict the likelihood of seepage problems due to HF in an existing earth dam.

Energy-generating and storage systems, such as photovoltaic (PV) panels and energy storage batteries in homes, are becoming increasingly popular in the context of decarbonization. The systems are also expected to increase household resilience to natural hazard-triggered blackouts. However, how these systems contribute to the use of electrical appliances in households in actual cases is not sufficiently known. Therefore, this report aims to describe the activities that a household with an energy-generating and storage system could undertake during a natural hazard-triggered blackout. We focused on the blackout triggered by the 2018 Hokkaido Eastern Iburi Earthquake (approximately 2.95 million households lost power) and conducted an interview with a household living in a detached all-electric house with a PV and battery system. The results showed that the household lived without inconveniences during the blackout due to the power supply from the installed system, despite the weather. They charged cell phones and used a television, refrigerator, microwave oven, cooking heater, and bath. Moreover, the household’s electricity was also supplied to other households. These results clarified the actual benefit of enhancing household and community resilience of the systems. The results will aid household decision-making for the installation and governmental consideration of subsidies.