Progress in Disaster Science最新文献

This review paper provides a comprehensive analysis of utilizing coastal vegetation as a mitigation strategy against tsunamis. It begins with an introduction to the historical impact of tsunamis on coastal vegetation and explores various types of trees known for their tsunami defense characteristics. The paper examines how vegetation can effectively protect against tsunamis based on past events, supported by both experimental and numerical studies. It also delves into innovative concepts proposed by researchers, including hybrid defense systems and optimized plantation layouts, to enhance the protective capabilities of coastal vegetation. Case studies from Aceh and South Java illustrate practical applications of reforestation efforts aimed at tsunami mitigation. Additionally, the paper discusses the challenges and limitations associated with implementing coastal vegetation strategies, emphasizing crucial factors such as maintenance and long-term sustainability.

Bangladesh, a low-lying deltaic plain formed by the convoluted network of streams within the Ganges-Brahmaputra-Meghna basin, is one of the worst climate change-induced natural hazards sufferers. Among all the riverine and coastal hazards, floods alone have wreaked havoc on the national economy. This study focused on determining the level of potential hazard of different crop stages of Transplanted Aman (T. Aman) rice based on the coincidence of the crop cycle stages with the duration and depth of flood of the Brahmaputra-Jamuna River system. A 2D hydrodynamic model has been developed using TUFLOW for the Brahmaputra-Jamuna River system under this study. The model simulated results for 2008 and 2019, representing bank-full flow conditions (2008) and a recent flood event (2019). It is seen that the vegetative stage for both the flooding scenarios is most affected for all selected monitoring locations, and the effect of flood events of the other two stages (reproductive and ripening stage) varied spatially. The analysis presented in the study can be used to determine the economic damage incurred to the lower-income community, primarily associated with agriculture. Adaptive actions and mitigation measures can be prioritized to depreciate the loss and damage due to these catastrophic flooding events.

The levee effect poses a challenge for flood risk management. While there is research on the consequences of the levee effect in general, a detailed understanding of policies addressing residual risk is lacking. The aim of this research is to understand how coercive and cooperative policy designs are applied in spatial planning provisions dealing with residual flood risk and which context conditions influence planning authorities when deciding on a certain policy design. We applied a qualitative research approach, including expert interviews and examining relevant documents. The results show that coercive planning policies can regulate the use of areas with residual risk either by limiting the extension of building land or by prescribing flood adaptation of buildings. However, the formulation of such regulations is connected to the spatial context, the actors involved, past flood events and risk awareness. Cooperative planning policies address residual risk either as recommendations or by providing local authorities scope for decision-making when it comes to land use planning in residual risk areas. The interview partners also discussed possibilities that go beyond spatial planning, such as emergency management. The research shows the variety of policies that can offer ways of dealing with flooding beyond the expected level.

This study examines the perception of South Korean citizens regarding earthquake risk, their understanding of earthquake management policies, and their evaluation of such policies. The structural relationship between earthquake risk perception, policy efficacy (which is the general audience's understanding of the policy and willingness to participate), and policy support was investigated while exploring the moderating effect of past earthquake experiences. The survey was conducted among 330 South Korean individuals. The responses were analysed using statistical tools such as confirmatory factor analysis, structural equation modelling, and multi-group analysis.

The study revealed that an individual's earthquake risk perception significantly impacts policy efficacy but is unlikely to directly influence policy support. The findings also suggest that individuals who have experienced seismic shockwaves are more likely to perceive earthquake risk and understand earthquake risk mitigation policies. However, an individual's earthquake experience does not significantly impact the relationship between risk perception and policy support.

This study's findings have implications for understanding the relationship between earthquake risk perception, policy efficacy, and support, as well as for developing effective earthquake risk management strategies in South Korea.

Changing rainfall patterns on vulnerable hill slopes are a significant factor in increasing landslide frequency and resulting damages. In the Nilgiris district of the Western Ghats, India, recent shifts in rainfall patterns, including increased overall precipitation and more erratic downpours, have raised concerns about landslide occurrences. This study examines the correlation between the altering rainfall patterns and the occurrence of landslides in a quantitative manner. A thorough analysis of rainfall data from 1992 to 2022 using R (hydroTSM) is conducted to evaluate its impact on landslides. Using the Analytical Hierarchy Process (AHP), a comprehensive Landslide Susceptibility Map (LSM) is generated by incorporating twelve significant landslide causative factors. The results indicate that 1% of the study area is in the very high susceptibility zone and 18% in the high susceptibility zone. These findings are crucial for developing targeted mitigation strategies, effective land use planning, and ensuring the safety of the region's inhabitants and infrastructure.

Drones, unmanned aerial systems, are of growing interest to organizations involved in disaster risk reduction, particularly in post-disaster emergency response. Despite the potential benefits of drones, their use is not well established and practical challenges need to be understood. This study examines the role of drones in disaster management by analyzing various applications of drones in response to the Noto Peninsula earthquake in January 2024. Drones were used on the ground in a variety of new ways, including transport of emergency supplies, restore of cellphone communications, and inspect on damaged facilities. Several issues were identified, including the need to incorporate drone capabilities into disaster management plans, develop appropriate laws and regulations, establish public-private coordination mechanisms, address technological limitations due to advances in technology, and implement training programs specifically for drone operators. Collaboration among government agencies, private organizations, and industry associations in disaster response highlighted the importance of fostering partnerships and mobilizing collective expertise in disaster management. The study concludes by highlighting the important role that drones can play in enhancing emergency response efforts and mitigating the impact of future disasters.

Seismology is among the ancient sciences that concentrate on earthquake disaster management (EQDM), which directly impact human life and infrastructure resilience. Such a pivot has made use of contemporary technologies. Nevertheless, there is a need for more reliable and insightful solutions to tackle the daily challenges and intricacies of the natural sciences that stakeholders must confront. To consolidate the substantial endeavors in this field, we undertake a comprehensive survey of the interconnected contemporary technologies. More particularly, we analyze the data communication networks (DCNs) and the Internet of Things (IoT), which are among the main infrastructures of seismic networks. In accordance, we present conventional and innovative signal-processing techniques in seismology. Then, we shed light on the evolution of EQ sensors including the acoustic sensors based on optical fibers. Furthermore, we address the role of remote sensing (RS), robots, and drones for EQDM. Afterward, we highlight the social media contribution. Subsequently, a comprehensive elucidation of the diverse optimization techniques employed in seismology and for prolonging seismic networks is presented. Besides, the paper analyzes the important functions that artificial intelligence (AI) can fulfill in several areas of seismology. Lastly, we guide stakeholders on how to prevent natural disasters and preserve human lives.

Urban areas are experiencing rapid growth, accompanied by significant disorder in Lima Metropolitan area and many other cities in South America. Due to decades of uncontrolled construction practices, it is imperative to identify and better understand the types of informalities prevalent in these recent urban areas. Addressing this lack of information is crucial for implementing appropriate countermeasures and developing new policies that benefit the communities residing in such areas. It is worth noting that understanding disaster risk aligns with the first priority of the Sendai Framework for Disaster Risk Reduction. In this study, we propose the use of radar satellite imagery recorded by the Sentinel-1 constellation since 2017 to identify clusters of urban growth in Lima Metropolitan area. Then, the informal urban clusters can be depicted by visual inspection of the last recorded high-resolution optical image. With good spatial and temporal resolution, we identified 25 clusters informal areas. Among our findings, we observed that several of these clusters are situated in landfills comprised of construction and other waste, increasing their vulnerability to debris flow, landslides, and earthquakes. Additionally, we noted that some new urban areas mainly consist of temporarily empty houses, highlighting the feasibility of implementing countermeasures, such as relocations, in the early stages of informal occupation. These results underscore the significant contribution of satellite radar imagery in identifying recent informal urban areas.

While research on natural hazards in Nepal has primarily focused on the consequences of individual hazards within an area, it is also essential to analyze the probable occurrence of several types of natural hazards and their interaction, i.e., Multi-hazard assessment. In light of this, the study conducted a Multi-Hazard Risk Assessment of the proposed capital city of Lumbini province, which covers 14 wards from three municipalities. The four prevalent hazards in the area, i.e., flood, landslide, debris flow, and forest fire, have been considered in the study, which includes generating individual susceptibility maps using different geospatial and modeling techniques. The vulnerability and risk assessment was done on a ward level and considered physical, social, economic, and environmental vulnerability indicators. The results on the multi-hazard susceptibility map show that 29.36% of the area was at low susceptibility, while the medium and high zones comprised 46.16% and 24.46% of the total area, respectively. Wards 2, 3, and 7 of Rapti are highly vulnerable, while Ward 8 of Sitganga and Ward 9 of Rapti are the least vulnerable. Moreover, wards 1, 2, and 3 are at high risk to the vulnerability parameters, while ward 8 of Sitganga is at the least risk. The high-risk areas are on the foothills of the Siwalik range, which are prone to landslide, debris flow, and forest fire hazards, as well as are on the bank of West Rapti River, which marks them as potential flood hazard zones. The capital city of Lumbini province is fast developing. Therefore, the results derived from this study assist in identifying potential risk zones to consider while creating a master plan for the area.

In the face of global challenges, ensuring robust health security is paramount for safeguarding populations against emerging threats. Using country-level data on the Global Health Security (GHS) index covering 195 countries, this study employs Bayesian Belief Networks (BBNs) to explore probabilistic dependencies among various indicators that can influence health security outcomes. The findings reveal distinct probabilities of low performance for certain components within main indicators such as ‘prevention’, ‘early detection and reporting’, and ‘sufficient and robust health sector’, significantly shaping overall health security outcomes. Particularly noteworthy is the identification of ‘early detection and reporting’ as the most critical indicator, showing an 87% probability improvement, followed closely by ‘prevention’ at 81%. The latter part of the study delves into the sub-indicators associated with ‘early detection and reporting’. This analysis uncovers varying probabilities of extreme performance states, with ‘laboratory supply chains’ emerging as the most crucial sub-indicator, presenting an 84% probability improvement. Conversely, the ‘epidemiology workforce’ is deemed less influential in impacting overall health security outcomes. Assessing the mutual value of information sheds light on the informative nature of ‘prevention’ and ‘sufficient and robust health sector’ within the main indicators, while in sub-indicators, ‘surveillance data accessibility and transparency’ take precedence.