In recent years, volcanic disasters have occurred repeatedly in Japan. In response, domestic efforts are underway to consider measures for dealing with large-scale eruptions. The Journal of Disaster Research has published several special issues that focus on volcanic disasters, featuring research outcomes related to the observation and investigation of volcanoes and disaster prevention measures.

This special issue features papers that reflect the recent trends in volcanic disaster research. Topics include observational and analytical studies of volcanic ejecta, damage assessments based on volcanic ejecta, research on debris flows triggered by rainfall following ash and tephra deposition, and studies on aviation safety and evacuation planning for residents in the event of a large-scale eruption.

Iguchi and Ishii proposed a forecasting system for ashfall amounts before eruptions around the Sakurajima Volcano by utilizing the statistical properties of ground deformation parameters associated with numerous eruptions. Kumaoka et al. proposed an airport alert system to address volcanic ash risks from large-scale eruptions at Sakurajima and analyzed the capacity of airports to accommodate evacuating aircraft. Shimizu et al. used 10 years of light detection and ranging observation data from Sakurajima to propose a threshold for distinguishing between clouds and volcanic ash. Otsuka et al. investigated small-scale spatial variations in ashfall in urban areas through numerical simulations, highlighting that wind disturbances caused by buildings significantly impact ashfall distribution, depending on the particle size. Nakada et al. demonstrated the utility of a method that automatically generates ashfall distribution contour maps and estimates the ash volume based on ashfall survey results from multiple domestic eruptions. Shimano et al. conducted colorimetric measurements on volcanic ash samples collected daily at Sakurajima and performed principal component analysis, showing that color measurement is a rapid and quantitative method suitable for monitoring volcanic activity. Takebayashi investigated river basins in the southwestern part of Sakurajima, where debris flows occur frequently, and clarified the relationships between permeability differences, gully formation rates, and sediment yield. Tsutsumi et al. examined the generation process of snowmelt-type volcanic mudflows through laboratory experiments. They revealed that when snow and gravel were mixed well, snowmelt accelerated, providing valuable insights into disaster prevention measures against such mudflows. Sugo et al. introduced a collaborative disaster preparedness effort between experts and residents in anticipation of a future large-scale eruption at Sakurajima that may cause heavy pumice and ashfalls in urban areas. They reported behavioral changes in both individual preparedness actions and communication-related activities involving others within the framework of this collaborative effort.

We hope that the results of advanced research presented in this special issue will be utilized to prevent and mitigate volcanic disasters.

The Sakurajima Volcano has experienced repeated Vulcanian eruptions since 1955 for a period of 69 years. We propose a forecasting system for volcanic ashfall prior to the onset of eruptions based on monitoring ground deformation. Inflationary strain changes are detected by strainmeters in an underground tunnel prior to eruptions. Statistical features of the ground deformation are represented by a log-logistic frequency distribution of the duration time from the onset of inflation to the onset of eruption, and the deflation volume ratio to precursory inflation. This indicates that the onset time and scale of eruption can be forecasted probabilistically. In the forecasting system, FALL3D is operated as the simulation engine, with a time interval of six minutes for 20 scenarios (four cases for onset time and five cases for scale) with probabilities given by the log-logistic distribution.

This study proposes a volcanic ash (VA) risk alert system for airports and analyzes the capacity for accommodating evacuation aircraft during a large-scale eruption of Mount Sakurajima. The system classifies airports into four groups (A, B, C, and D) based on factors, such as distance from the erupting volcano and VA spread speed. A crisis response system for VA is developed, which can recommend suitable actions for airports based on their classification. The system is applied to simulate a large-scale eruption of Mount Sakurajima, similar to the An-ei great eruption of 1779. Three scenarios are defined: Case 1, where VA affects all of Kyushu, Shikoku, and Chugoku; Case 2, where VA reaches southern Kyushu and parts of Shikoku and Kansai, while Chugoku remains unaffected; and Case 3, where VA extends to most of Kansai and Chubu, and the southern part of the Capital Region, affecting major airports in Kansai, Chubu, and the Capital Region. The results show that in Cases 1 and 2, the total evacuation capacity exceeds the number of aircraft requiring relocation, indicating no capacity expansion is necessary. However, Case 3 presents a challenge, as a significant number of aircraft cannot be assigned evacuation airports and some airports experience excessive aircraft congestion, leading to capacity constraints in physical airport capacity and air traffic control operations. These findings underscore the need for improvements in these capacity issues and provide policy implications for future preparedness.

Lidar observations of volcanic ash in Sakurajima, Japan, were conducted during 2016–2024 to determine the volcanic impact on the atmosphere. The range from the lidar observatory to the vent was divided into four zones, and the characteristics of the extinction coefficient were then analyzed. The discrimination threshold between cloud and volcanic ash was suggested, and volcanic activity reports by the Japan Meteorological Agency (JMA) were employed to explain the long-term variation of the extinction coefficient coupled with the high depolarization ratio measured by lidar. The correlation between the number of eruptions mentioned in the JMA report and the monthly mean extinction coefficient was low. This result suggests other smaller-scale eruptions affect atmospheric conditions around the volcano.

Micro-spatial behavior of volcanic ashfall at low- and mid-rise building areas in a large city is investigated by numerical ashfall simulations with individual buildings approximately resolved. The effects of the inertial force acting on ash particles are included in the simulations to account for the deviation of ash flow from air flow caused by the large curvatures of air streams around buildings, whereas the inertia force can be neglected in the large-scale atmospheric ash-dispersion processes treated in operational ashfall prediction models. The ashfall rate and the spatial ash concentration in the urban boundary layer are calculated for six particle sizes (from -1 to 4 on the phi scale) under windy conditions. Dependence on the ash-particle size of the distribution of the ashfall rate at the ground, as well as the spatial concentration within the building canopy resulting from the disturbed wind caused by buildings, is shown to be apparent. The results also indicate that the spatial ash concentration can locally exceed 150% of the large-scale values that might be provided by ashfall predictions with a horizontal resolution on the order of kilometers. Understanding small-scale features of ashfall in cities is stressed to be important for developing measures against ashfall events.

Using discrete tephra mass loading/m² data from eruptions, this study attempted to draw their distribution maps using the algorithm developed by Yang and Bursik (2016). In the first approach, we used tephra observation data of the September 2014 Ontake and the October 2021 Aso eruptions to test the reproducibility of this automatically drawing distribution method for the previously reported hand-drawn tephra isopach maps and calculated eruption volumes. As a result, it was possible to reproduce each of the isopach maps and obtain similar total tephra volumes using this automatic drawing method. Therefore, it is possible to automatically obtain a tephra mass loading/m² distribution map without relying on the skills and experience of individual researchers, as was the case in the production of hand-drawn isopach maps. Based on the published tephra data for a series of eruptions at Izu Oshima and Aso Volcanoes over long periods of up to 1,500 and 30,000 years, respectively, the tephra distribution of each eruptive event was automatically drawn using the above method. By superimposing the results (digital data) of these tephra distribution maps for each volcano, it was possible to evaluate the long-term ash fall hazard at any location in each volcano.

We conducted principal component analysis on the colorimetric data of dried bulk ash samples collected daily between 2009 and 2015 at Sakurajima Volcano, southwest Japan. The CIE L*a*b* color system describes the colorimetric values. The analysis was performed for different sets of values: Set 1, average L*a*b* values alone; Set 2, average and ratios of color values; and Set 3, average, ratios, and their standard deviations (Std). The results show that 89% of data in Set 3 consists of five principal components. The first principal component (PC1) reflects Stds rather than averages of color value assigned to the second principal component (PC2). The third to fifth principal components (PC3 to 5) reflect ratios of color values (b/a, L/a). These results show that the major variation in color of the ashfall samples at Sakurajima Volcano is the scattering, or heterogeneity, rather than the average or representing color values. The temporal variation of the PCs synchronizes with some aspects of eruptive phenomena. PC1 (heterogeneity) increases with the frequency of explosions, whereas PC2 (chroma and brightness) decreases with the discharge rate. PC3 and PC4 reflect changes in mixing end components of ash particles, which may indicate the renewal of ascending magma or the shift in vent location or ascent path. As colorimetric measurement is a quick and quantitative method, it can be a candidate technique for monitoring as a proxy of petrological data, although the color dependence on the size distribution requires consideration.

Permeability experiments of the crust layer, channel formation experiments by rainfalls, and numerical simulations focusing on the formation and destruction of crust were conducted to investigate the influence of the formation and destruction of crust on the formation mechanism of gullies. In the Arimura River basin, southwest of Sakurajima in Japan, crusts were formed on volcanic ash deposits. Even within the same watershed area, the degree of crust development differs depending on the intensity of surface disturbance, and the permeability coefficient varies significantly. In the flume experiment considering crusts, the erosion area developed upstream, starting at the location where the crusts were destroyed, and a gully was gradually formed. Compared to the results of the experiment without considering crusts, the channel spacing in the transverse direction was wide and the number of channels was small. A numerical simulation model was developed to reproduce the development process of a gully by changing the angle of repose. In the numerical simulations, the erosion areas developed upstream, and a gully was gradually formed. In a gully with two crust destruction zones in the longitudinal direction, the scour area gradually expanded, and when the two scour holes were connected, the rate of gully development increased rapidly, and the amount of sediment discharged increased.

Volcano eruption during the snow season may lead to a drastic snowmelt owing to eruption heat, resulting in a mudflow. This phenomenon is called “snowmelt-type volcanic mudflow.” A snowmelt-type volcanic mudflow has more water when compared with an ordinary mudflow caused by rainfall such that this type of mudflow can become larger and has the potential to reach more remote areas with greater speed. It triggers tremendous damage in lower reaches in some cases. Therefore, adequate measures should be taken against snowmelt-type volcanic mudflow, and monitoring should be conducted in a volcanic area with snow. However, a snowmelt-type volcanic mudflow rarely occurs and as only a few examples are available, this type of mudflow is less understood. Accordingly, this study examines the generation process of snowmelt-type volcanic mudflow using experiments. The following two types of experiments were conducted. (1) The speed of snow melting is determined by mixing snow and heated gravel. (2) The process in which gravel comes flying and penetrates the snow layer is examined. These experiments have clarified the following points. The speed of melting snow varies depending on the contact condition of snow and heated gravel; the speed of melting snow increases where there is a mixture of snow and heated gravel; under the same condition of the amount of gravel, the smaller the grain size is, the greater is the speed of snow melting; and there is a correlation between the kinetic energy of the gravel flying and the mass of the snow pushed aside by penetration of gravel into snow layer. The findings revealed that 5 cm diameter gravel can melt snow most effectively.

We have been working for about three years on collaborative activities between experts and residents aimed at enhancing disaster preparedness against the risk event of the massive fall of pumice and volcanic ash due to a large-scale eruption in Kagoshima City, which is expected to occur within the next few decades due to a major eruption of Sakurajima Volcano. In this study, we identified the behavioral changes of residents observed through collaborative activities undertaken by experts and residents over a long period, using ethnography and individual interviews, and discussed the mechanisms of these changes based on the framework of the theory of planned behavior. As a result, while the specific behaviors arising from collaborative activities were diverse, the behavioral changes could be broadly categorized into two types: “preparing” behaviors that are self-contained and “speaking” behaviors that involve engaging with others. Furthermore, among the survey participants who experienced changes in both “preparing” and “speaking” behaviors, a higher proportion reflected on experiences that stirred emotions such as “gratitude” and “anxiety” as turning points.

This study investigates the preparedness of public health nurses (PHNs) for nuclear disasters in Kagoshima Prefecture, Japan, following the devastating 2011 Great East Japan Earthquake and subsequent Fukushima Daiichi Nuclear Power Station accident. Focusing on PHNs’ roles in community health management during disasters, we assessed nurses’ knowledge and skills in initial response, including the risk assessment of radiation exposure, health education, and evacuation assistance. We also explored demographic factors, educational background, and participation in disaster training. The findings reveal PHNs’ significant lack of confidence in performing essential duties immediately following a nuclear incident, with only 7% answering that they could perform somewhat adequate post-disaster public health activities. Furthermore, the study highlights deficiencies in practical skills, particularly in administering stable iodine tablets and assisting in evacuations, underscoring the need for improved training programs. The results indicate that, even 12 years after the accident, PHNs’ disaster response capabilities, especially in regions with nuclear facilities, must be urgently enhanced with the cultivation of practical skills, and continuity-in-response capabilities must be assured using systematic training and education. This study underlines the critical need for a comprehensive approach to improving health professionals’ preparedness for nuclear emergencies, with implications for both national and international nuclear disaster policy.

In the event of a disaster, people who are competent to assist the safe evacuation of disabled people are essential. To ensure the availability of such people in the future, it is anticipated that educational programs related to evacuation assistance would be introduced in school education. Evacuation assistance drills involving people with disabilities have been implemented for years at junior high schools within Osaka Prefecture, Japan. This study aims to elucidate the impact of evacuation assistance practices on junior high school students. The research method involved participant observations of evacuation support practices and an evaluation of the actual situation of junior high school students’ learning support methods and their self-evaluation. The results of this study were as follows. (1) The practice of providing evacuation assistance to people with disabilities has an educational impact on students, helping them to learn how to facilitate mobility for people with disabilities and understand the importance of collaboration. (2) Evacuation assistance practice also has an educational impact, as it deepens the understanding of disability through collaborative experience and increased interest in accessible environments. (3) By achieving their goals in training, the students acknowledge their capacity to serve as supporters and exhibit a positive attitude toward assisting people with disabilities.

Some disaster survivors who had previously received support through volunteering participated in volunteer activities for people affected by subsequent disasters. This chain of support, known as “pay-it-forward,” is expected to expand social networks and bring about small-world property (i.e., networks with high clustering and short path length between people). Previous research has focused on the effects of pay-it-forward on individuals (i.e., the psychological perspective), but has insufficiently determined its effects on the whole society or social networks (i.e., the sociological perspective). This study investigates the dynamic effects of pay-it-forward on network properties. We proposed a network formation model considering pay-it-forward during disasters and conducted numerical simulations. The results showed that pay-it-forward led to small-world property and higher social welfare in the long term, because it eliminated the disparity in ties between people (in particular, it reduced the number of people with fewer ties), which accelerated network formation during non-disaster periods. This result was more pronounced in societies with a larger disparity in ties. From a sociological perspective, our findings imply the significance of pay-it-forward volunteering and volunteer organizations that promote such activities.

This study aims to evaluate the performance of various large language models (LLMs) in generating dengue fever epidemic and earthquake intensity maps through the integration of spatial information technology. By combining natural language processing techniques, this paper presents an innovative method to extract real-time data related to dengue fever and earthquake events, which is then used to generate corresponding geographic information maps, thereby improving real-time monitoring and disaster management efficiency. The research designed a series of detailed prompts, including topic descriptions, data sources, analysis objectives, and specific requirements, to test the capabilities of multiple LLMs in the code generation process. The codes generated by these models were further used to map the geographic distribution of dengue fever outbreaks and earthquake intensities in Taiwan. Subsequently, the codes were evaluated on accuracy, operational efficiency, and the clarity of the visualized results. The findings revealed that in addition to ChatGPT, models such as Copilot, Claude, and Nxcode-CQ-7B-orpo also excelled at generating precise and efficient maps. These LLMs are capable of automating the processing of large amounts of data and generating visualized charts with decision support functions, significantly reducing the time and labor costs associated with traditional manual operations. In addition, this innovative approach provides a new technical pathway for real-time geographic disaster monitoring and management. The results underscore the value of integrating LLMs with spatial information technology, offering new research directions for geographic information systems applications and providing robust technical support for disaster response and public health management.