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Background: The Mediterranean Sea is a region characterized by high seismic activity, with at least 200 tsunami events recorded from the fourth century to the present twenty-first century. Numerous studies have been conducted to understand past tsunami events, earthquake–tsunami generation, tsunami recurrence periods, tsunami vulnerability zones, and tsunami hazard mitigation strategies. Therefore, gaining insights into future trends and opportunities in Mediterranean Sea tsunami research is crucial for significantly contributing to all relevant aspects. This study aims to assess such trends and opportunities through a scientometric analysis of publications indexed by Web of Science from 2000 to 2023. Results: Based on a selection of 329 publications, including research articles, review articles, book chapters, and conference papers, published between 2000 and 2023, Italy has the highest number of publications and citations in this field. The number of publications has increased significantly, especially after the 2004 Indian Ocean, 2011 Tohoku, and 2018 Palu tsunamis. According to the keyword analysis, the terms "tsunami", "earthquake", "hazard", "wave", "Mediterranean", "coast", and "tectonic" were the most frequently used in these publications. Research themes consist of four classifications: motor themes, such as seismic hazard; specific but well-developed themes, like tsunamiite; emerging or disappearing themes, for example, climate change; and general or basic themes, such as equations and megaturbidite. The number of publications related to the motor theme classification continued to grow throughout 2000–2023. Topics from 2011–2023 are more complex compared to 2000–2010, characterized by the emergence of new keywords such as evacuation planning, risk reduction, risk mitigation, building vulnerability, coastal vulnerability, climate change, probabilistic tsunami hazard assessment (PTVA-3 and PTVA-4). However, topics that were popular in the 2000–2010 period (e.g., paleotsunami deposits, earthquake, and tsunami propagation analysis) also increased in 2011–2023. Conclusions: Research topics with high centrality and density such as seismic hazard will continue to develop and prospect. The cluster network of this topic includes seismoturbidites, sedimentary features, tsunami modeling, active faults, catalog, and historical earthquakes. [ABSTRACT FROM AUTHOR]

This document is an editorial from the journal Frontiers in Earth Science titled "Prevention, Mitigation, and Relief of Compound and Chained Natural Hazards." It discusses the increasing frequency of extreme natural disasters due to global climate warming and frequent earthquakes, which pose significant threats to human life and property. The editorial highlights the importance of preventing, mitigating, and relieving compound and chained natural hazards, and the role of technological advancements in addressing these hazards. The document provides an overview of nine published papers that focus on earthquakes, geological hazards, earthquake-triggered landslides, and landslide susceptibility. It concludes by emphasizing the need for continued research on comprehensive natural hazards and disaster chains, beyond earthquakes and geological disasters, such as meteorological events, floods, droughts, wildfires, and tsunamis. [Extracted from the article]

The mountainous areas of the Loess Plateau in China are crisscrossed with ravines, fragile ecological environment, and frequent landslide hazards. Landslides often cause building collapses and casualties, seriously affecting the sustainability of economic and social development in the region. In order to study the damage of loess landslides to village and town buildings, the paper takes the Xingwang landslide in Fugu County, Shaanxi Province, China as an example, and uses discrete element method and finite element method to study the dynamic process of landslide and its damage to houses. Firstly, the geological characteristics of the landslide were identified by means of investigation, surveying, engineering exploration and geotechnical testing. Secondly, a threedimensional numerical model of the landslide area was established by using the particle flow code system (PFC[sup 3D]). Finally, the entire movement process of the landslide was simulated, and the impact damage to houses induced from landslide was analyzed and predicted. The results show that the whole movement of the landslide lasted a total of 180 s, with a maximum average velocity of 2.01 m/s and a maximum average displacement of 73.7 m. The first and second rows of houses located at the foot of the landslide will suffer serious damage, with most bricks displacement ranging from 0.1 to 2.5 m and a maximum displacement of 10.3 m, posing a serious safety risk to the houses. Only a portion of the third row houses will be damaged, and the fourth row houses will not be threatened by landslide. By comparing with the prediction results of other methods and the current situation of buildings deformation, the results of this paper have a certain credibility. This study provides a numerical method for quantitative assessment of the risk and building damage for loess landslide, which can be used as a reference. It also provides technical support for formulating hazard prevention and reduction plans for the Xingwang landslide. [ABSTRACT FROM AUTHOR]

The present paper argues that the standardised treatment of disaster research and practice perpetuates the production of systematic epistemic injustices against victims of disasters. On the one hand, disaster victims are often prevented from contributing with their opinions and knowledge to the processes of disaster mitigation and disaster conceptualisation. On the other hand, disaster victims tend to lack the hermeneutical resources to make sense of their experiences intelligibly, due to the existence of significant hermeneutical gaps in the hegemonic terminology on the matter. I argue that both forms of epistemic injustice, the testimonial and the hermeneutical, are sustained by an epistemic privilege between the Global North and the Global South in matters of disasters. The second group comprises what I categorise generally as 'disaster victims'. I identify two forms of structural prejudice that operate against disaster victims: one is the 'non-expert' prejudice, and the other is the colonial prejudice. Finally, because of the intercultural nature of disaster environments, I discuss the field of 'multicultural competencies' as a useful form of unveiling and counteracting the epistemic injustices contained in both disaster theory and practice. [ABSTRACT FROM AUTHOR]

Sichuan-Tibet Railway spans several watersheds such as Jinsha River and Yalong River, and Potential landslides are frequent along the route, which poses serious hazards to the normal construction and operation of the railroad. The traditional time-series InSAR technology is limited by the number of images and other restrictions, and has a long solution time, making it difficult to obtain information on short-term occurrence of deformation and unable to perform wide-area potential landslides monitor quickly. In this paper, taking a geological hazard-prone area in the Jinsha River basin (or a section of the Sichuan-Tibet line) as an example, based on the Sentinel-1 satellite SAR data provided by the Copernicus program of ESA, the model corrects the interferometric superposition deformation results obtained from a small number of SAR images (less than 7), decodes the corrected rate results, and identifies a total of 13 areas where deformation obviously occurs A total of 13 typical areas with significant deformation were identified. The identified typical areas were time-series solved and their deformation was traced. The method provides a new idea for identification and monitor of Potential landslides in a wide area and further promotes the development of disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

In the context of natural hazard risk quantification and modeling of hazard interactions, some literature separates "Level I" (or occurrence) interactions from "Level II" (or consequence) interactions. The Level I interactions occur inherently due to the nature of the hazards, independently of the presence of physical assets. In such cases, one hazard event triggers or modifies the occurrence of another (e.g., flooding due to heavy rain, liquefaction and landslides triggered by an earthquake), thus creating a dependency between the features characterizing such hazard events. They differ from Level II interactions, which instead occur through impacts/consequences on physical assets/components and systems (e.g., accumulation of physical damage or social impacts due to earthquake sequences, landslides due to the earthquake-induced collapse of a retaining structure). Multi-hazard life cycle consequence (LCCon) analysis aims to quantify the consequences (e.g., repair costs, downtime, casualty rates) throughout a system's service life and should account for both Level I and II interactions. The available literature generally considers Level I interactions – the focus of this study – mainly defining relevant taxonomies, often qualitatively, without providing a computational framework to simulate a sequence of hazard events incorporating the identified interrelations among them. This paper addresses this gap, proposing modeling approaches associated with different types of Level I interactions. It describes a simulation-based method for generating multi-hazard event sets (i.e., a sequence of hazard events and associated features throughout the system's life cycle) based on the theory of competing Poisson processes. The proposed approach incorporates the different types of interactions in a sequential Monte Carlo sampling method. The method outputs multi-hazard event sets that can be integrated into LCCon frameworks to quantify interacting hazard consequences. An application incorporating several hazard interactions is presented to illustrate the potential of the proposed method. [ABSTRACT FROM AUTHOR]

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Translation of geoscience research into tangible changes, such as modified decisions, processes, or policy, in the wider world is an important yet notably difficult process. Illustratively, university-based scientists and professionals work on different timescales, seek different insights, and may have a substantial cognitive distance between them. The work on Co-RISK reported in this paper is motivated by an ongoing need for mechanisms to aid this translation process. Co-RISK is an accessible (i.e. open access, paper based, zero cost) toolkit for use by stakeholder groups within workshops. Co-RISK has been developed to aid the co-creation of collaborative inter-organisational projects to translate risk-related science into modified actions. It is shaped to avoid adding to a proliferation in increasingly complex frameworks for assessing natural hazard risk and is given a robust basis by incorporating paradox theory from organisation studies, which deal with navigating the genuine tensions between industry and research organisations that stem from their differing roles. Specifically designed to ameliorate the organisational paradox, a Co-RISK workshop draws up "maps" including key stakeholders (e.g. regulator, insurer, university) and their positionality (e.g. barriers, concerns, motivations) and identifies exactly the points where science might modify actions. Ultimately a Co-RISK workshop drafts simple and tailored project-specific frameworks that span from climate to hazard, to risk, to implications of that risk (e.g. solvency). The action research approach used to design Co-RISK, its implementation in a trial session for the insurance sector, and its intellectual contribution are described and evaluated. The initial Co-RISK workshop was well received so it is envisaged to be applicable to other sectors (i.e. transport infrastructure, utilities, government). Joint endeavours enabled by Co-RISK could fulfil the genuine need to quickly convert the latest insights from environmental research into real-world climate change adaptation strategies. [ABSTRACT FROM AUTHOR]

Earthquake-induced rock landslides in the eastern mountains of the Tibetan Plateau, especially landslides with weak interlayers pose a significant threat to major construction projects. Prestressed anchor cable is one of the main reinforcement methods of rock slopes. This paper combines shaking table model tests and numerical simulation to study the reinforcement effect and dynamic response characteristics of prestressed anchor cables applied to rock slopes with weak interlayers under strong earthquakes. The research results show that prestressed anchor cables can effectively reinforce slopes with weak interlayers. A small cable inclination, a small spacing and a high prestress are recommended in the seismic reinforcement design of prestressed anchor cable. In addition, the characteristics of slope progressive damage and prestress loss under the earthquake are found by the shaking table test. The results have been applied in hazard prevention and control of rock slopes on the Chengdu-Lanzhou Railway at the eastern Qinghai-Tibet Plateau. [ABSTRACT FROM AUTHOR]

The co-occurrence of multiple hazards can either exacerbate or mitigate risks. The interrelationships between multiple hazards greatly depend on the spatiotemporal scale and can be difficult to detect from large to local scales. In this paper, we identified coastal regions worldwide where the leading tropical (El Niño-Southern Oscillation, ENSO) and polar (Arctic Oscillation, AO; Southern Annular Mode, SAM) modes of climate variability simultaneously modify the seasonal conditions of multiple hazards, including the near-surface wind speed and swell and wind-sea wave powers. We classified the results at the national and municipal levels, with a focus on multiple hazards simultaneously occurring in space and time. The results revealed that the ENSO modulates multiple hazards, affecting approximately 40% of coastal countries, while the polar annular modes affect approximately 30% of coastal countries. The ENSO induced a greater diversity of multiple hazards, with Asian countries (e.g., Indonesia experienced increases of + 2% in wind and + 7% in swell) and countries in the Americas (e.g., Peru exhibited increases of + 1.5% in wind and + 6% in wind-sea) the most notably affected. The SAM imposed a greater influence on swells in the eastern countries of ocean basins (+ 2.5% in Chile) than in other countries, while the influence of the AO was greater in Norway and the UK (+ 12% for wind-sea and 8% for swell). Low-lying islands exhibited notable variations in pairwise hazards between phases and seasons. Our results could facilitate the interpretation of multihazard interactions and pave the way for a wide range of potential implementations of different coastal industries. [ABSTRACT FROM AUTHOR]

The utilization of baffle structures as a highly effective strategy for mitigating debris flow has attracted significant scholarly attention in recent years. Although the predominant focus of existing research has been on augmenting the energy dissipation capabilities of baffle structures, their deformation behavior under impact load has not been extensively investigated. Addressing this research gap, the current study systematically designs a series of physical model experiments, incorporating variables such as baffle height, shape, and various combinations of baffle types to comprehensively analyze the deformation characteristics of baffles subjected to debris flow impact. The experimental results reveal that the deformation of baffle group structures demonstrates a marked non-uniform spatial distribution and exhibits a latency effect. Additionally, distinct baffle configurations show considerable variations in peak strain, suggesting that combining different baffle shapes can not only optimize energy dissipation but also enhance resistance to deformation. Moreover, the relationship between baffle height and the development of deformation in relation to energy dissipation capacity is inconsistent, indicating that deformation must be a key consideration in the design of baffle structures. Consequently, this paper advocates for the formulation of a deformation-based design strategy for baffle structures, with the findings presented herein providing a foundational reference for future studies. [ABSTRACT FROM AUTHOR]

With the development of earthquake disaster reduction efforts in China, the content of earthquake disaster reduction policies has become increasingly enriched and improved. Particularly, multiple provincial governments have proposed earthquake disaster reduction planning policies. It is important to explore whether these policies can affect disaster mitigation. Therefore, this paper summarizes the earthquake disaster reduction plans and factors influencing seismic resilience. Panel data from 24 provinces between 2012 and 2021 were collected, and a difference-in-differences approach was used to construct an econometric model to evaluate the policy effects and analyze the enhancement of seismic resilience. The results show that the implementation of earthquake disaster reduction policies has a positive impact on earthquake monitoring, evacuation, and emergency relief capabilities, and the estimated policy effects are statistically significant. Moreover, a series of tests were conducted. The conclusions are as follows: (1) Earthquake disaster reduction policies have a positive impact on the improvement of seismic resilience in provinces. (2) Provinces with a higher number of earthquakes experience more significant effects from earthquake disaster reduction policies. (3) Provinces with higher seismic peak ground acceleration values exhibit more pronounced improvements in seismic resilience. [ABSTRACT FROM AUTHOR]

The western region of Sichuan Province, located in the Hengduan Mountains, is one of China's most seismically active zones. Due to limited land resources, many villages in western Sichuan Province are situated in mountainous and valley areas, facing harsh climatic conditions, lagging economic development, and insufficient infrastructure. After experiencing seismic disasters, these villages often encounter challenges, such as cut-off mountain roads, difficulties in delivering relief supplies, and sharply a significant drop in nighttime temperatures due to the high-altitude climate. Consequently, in the case of the economic underdevelopment and limited resources, how to repurpose existing buildings for disaster relief has become a crucial issue for disaster prevention and mitigation in these villages. This paper takes Ganbao Tibetan Village, located in the alpine gorge regions of western Sichuan Province, as a case study. It evaluates the interior space utilization status of different types of existing public buildings during disasters, calculates the effective utilization rate of interior space disaster reduction conversion based on the spatial layout model, and extracts the typical interior space dimensions that are conducive to disaster relief and conversion of public buildings based on the interior space utilization characteristics of disaster relief. This study provides a reference for the design of public service buildings considering the requirements of disaster resilience transformation. [ABSTRACT FROM AUTHOR]

High-voltage transmission lines are susceptible targets for lightning strikes. It is an interesting topic how the trip event of transmission line is related to the area, location, and intensity of thunderstorms occurring at that time and that place. Based on total lightning observation containing intra-cloud and cloud-to-ground lightning, and transmission line trip information from relaying system of power system, 8 thunderstorms associated with the lightning strike trip of local transmission lines were selected in the Pearl River Delta (PRD) region. Analysis was conducted on the total lightning activity of each thunderstorm process, including the characteristics of total lightning counts and density, followed by the variations in total lightning activity before and after lightning strike trips. Further, our investigation encompassed the spatial and temporal evolution, charge structure, and kinematic parameters of thunderstorms. It was revealed that almost all lightning trips in this area emerged in close proximity to bodies of water, accompanied by a discernible reduction in thunderstorm cloud altitude during line trip occurrences. This paper aims to enhance the understanding of total lightning and thunderstorm activity behavior, thereby providing valuable insights for lightning disaster prevention and mitigation in the meteorological bureau and power system. [ABSTRACT FROM AUTHOR]

Extreme precipitation of a minimum daily value of >30 mm often initiates natural hazards such as floods, which in turn may not only lead to property damage but also present a danger to people's health and lives. This paper mainly focuses on examining the trends and frequency of extreme daily precipitation (EDPr) in Poland. Also, it determines natural risk zones caused by EDPr of >30 mm, >50 mm, >70 mm, and >100 mm. In Poland, a significant positive trend was found for EDPr > 30 mm, >50 mm, and >70 mm in September, and for EDPr >100 mm in May. The most frequently recorded EDPr in Poland was >30 mm, the frequency of which ranged from 0.04% in February to nearly 3% in July. EDPr of >100 mm was recorded in 4 months, from May to August. An increase in the frequency of monthly EDPr in Poland occurred mainly in the southwestern and western parts. In Poland, three hazard zones of various frequencies of EDPr events were determined. In Zone III, which is in the southwestern and southern parts of the country, EDPr events occurred far more often than in Zone I; on average, four times more in the spring–summer season and slightly more than five times more in the autumn–winter season. The obtained results may help in the building of modern management and monitoring systems for the prevention of natural hazards caused by extreme precipitation. [ABSTRACT FROM AUTHOR]

The earthquake landslide hazard assessment method is mainly based on the traditional Newmark model. However, when the landslide hazard assessment is carried out along the fault zone, the calculated results are often different from the actual situation because the influence of fault effect is not fully considered. Therefore, how to construct a landslide hazard assessment model suitable for the fault zone is a technical problem to be solved by researchers. Taking the Lixian-Luojiabu fault zone in Gansu Province in China as the study area, this paper put forward the concept of fault effect correction coefficient exploringly, systematically studied the relative distance relationship between the landslide and fault zone, and the relative position relationship between landslide and upper and lower sides of the fault zone. The value table of the fault effect correction coefficient along the Lixian-Luojiabu fault zone was established, and the corresponding distribution map of the fault effect correction coefficient was drawn. Based on this, an improved Newmark model for the landslide hazard assessment along the fault zone was constructed. On the basis of systematic analysis of the slope and engineering geological rock group in the study area, the traditional Newmark model and improved Newmark model considering fault effects were used, respectively, to carry out the earthquake landslide hazard assessment under the condition of 10% exceeding probability in 50 years, and the ROC curve and Kappa coefficient methods were used to compare and analyze the evaluation results. The results showed that the AUC value and Kappa coefficient of the danger area obtained by the improved model with the Newmark model were 0.841 and 0.822, respectively, which were significantly higher than the calculated values of the traditional Newmark model, indicating that the model had a good improvement effect. The Newmark improved model, considering the fault effect, fully considered the influence of distance from the fault zone and fault upper and lower side effects, and the research results can provide a new reference for the landslide hazard assessment along the fault zone. [ABSTRACT FROM AUTHOR]

Flood hazard mapping is currently in a transitional phase involving the use of data and methods that were traditionally in the domain of local studies in a regional or nationwide context. Challenges include the representation of local information such as hydrological particularities and small hydraulic structures, as well as computational and labour costs. This paper proposes a methodology of flood hazard mapping that merges the best of the two worlds (local and regional studies) based on experiences in Austria. The analysis steps include (a) quality control and correction of river network and catchment boundary data; (b) estimation of flood discharge peaks and volumes on the entire river network; (c) creation of a digital elevation model (DEM) that is consistent with all relevant flood information, including riverbed geometry; and (d) simulation of inundation patterns and velocities associated with a consistent flood return period across the entire river network. In each step, automatic methods are combined with manual interventions in order to maximise the efficiency and at the same time ensure estimation accuracy similar to that of local studies. The accuracy of the estimates is evaluated in each step. The study uses flood discharge records from 781 stations to estimate flood hazard patterns of a given return period at a resolution of 2 m over a total stream length of 38 000 km. It is argued that a combined local–regional methodology will advance flood mapping, making it even more useful in nationwide or global contexts. [ABSTRACT FROM AUTHOR]

To address the issue of poor accuracy in typhoon wind data, this paper presents a methodology for the calibration of typhoon wind data while conducting an analysis and evaluation of the associated uncertainties. The approach commences with the introduction of two wind field data calculation models. The first model facilitates the correction of buoy attitude, thereby transforming inaccurate buoy wind speed data into real-speed data. In parallel, the second model enables the conversion of buoy-observed true velocity into neutral stable stratified wind parameters, leveraging satellite-derived data for precise calculations. Subsequently, the paper undertakes the task of spatio-temporal alignment between buoy data and satellite observations. Ultimately, a comprehensive comparative analysis is conducted by juxtaposing the ERA5 database with data collected from a moored buoy equipped with the R.M. YOUNG wind monitor. A new simulation method for satellite wind speed data inversion is proposed, and the experimental results demonstrate the effectiveness of the proposed calibration method in enhancing the accuracy of typhoon wind field data. In particular, the maximum wind speeds recorded were 20.15 m s−1 and 13.22 m s−1 during Typhoon "Jangmi (202005)" and "Maysak (202009)," respectively. Furthermore, the mean square errors (MSE) for our method were measured at 0.31 m s−1 and 0.28 m s−1, outperforming the satellite-derived indicators. The expanded uncertainty of measurement results for the two typhoons was calculated at 0.39 m s−1 and 0.34 m s−1, closely aligning with the MSE values. These computational models present a valuable means of enhancing the precision and reducing uncertainty in satellite-derived data. The findings presented in this paper hold great promise for applications in typhoon forecasting, investigations of air-sea interactions, and disaster prevention and mitigation efforts. [ABSTRACT FROM AUTHOR]

In highway reconstruction and expansion projects, the impact of the abandoned dreg body produced by the original highway on the new bridge project cannot be ignored. If the abandoned dregs are not handled properly, they will cause great threat to the operation of the new highway as well as to the safety of the surrounding environment and personnel. In this paper, based on a South China highway reconstruction and expansion project, a model of the abandoned dreg body, bridge pile and anti-slide pile is established with the help of finite difference software FLAC3D 5.0. The calculation results show that compared with burying the anti-slide pile, slope cutting is more effective for improving the stability of the abandoned dreg body. Under the action of vertical force intensity, the displacement of the top of the pile increases continuously, and the maximum bending moment of the pile body increases firstly and then decreases. The pile displacement and bending moment of the bridge pile increase significantly in the storm condition compared with the normal condition. In addition, the abandoned dreg body hazard prevention and control technical measures are studied. The impacts of different locations of anti-slide pile burial on bridge piles are analyzed and compared, and it is determined that the optimal location of anti-slide pile burial is the middle of the secondary slope. [ABSTRACT FROM AUTHOR]

In recent years, with the acceleration of urbanization and the frequent occurrence of extreme weather globally, the risk of urban flood disasters has gradually increased, and its potential consequences are immeasurable. Therefore, conducting risk assessment of urban flood disasters is of great significance, as it is one of the foundations and decision-making means for Disaster Prevention and Mitigation, and has become a hot topic and trend in current research. This paper starts by exploring the concept and formation mechanism of urban flood disasters, taking Hazard Factors, Disaster-prone Environment sensitivity, Vulnerability of Exposed Bodies, and Disaster Prevention and Mitigation Capabilities as primary indicators. Based on this, a risk assessment index system is established with 14 secondary indicators, such as annual average rainfall, distance to water systems, elevation, and terrain undulation. The spatialization of each indicator data point is processed through ArcGIS10.7, and the importance of hazard and sensitivity indicators is ranked using the Random Forest algorithm. The indicators are then weighted using a combination of the Analytic Hierarchy Process (AHP) and the entropy method, and the combined weights of each assessment indicator are calculated. Taking Wuhan City as the research area, the weights of each indicator are input into the established risk assessment model. ArcGIS spatial analysis techniques and raster calculation functions are utilized to solve the fuzzy comprehensive evaluation of the assessment model, obtaining zoning maps of risk levels for hazard, sensitivity, vulnerability, disaster prevention, and mitigation capabilities, as well as the distribution of comprehensive risk levels. The validity and rationality of the model results are verified by actual disaster data, providing important reference for urban flood disaster prevention in the future. [ABSTRACT FROM AUTHOR]

The convergence of cyber and physical systems through cyber–physical systems (CPSs) has been integrated into cyber–physical production systems (CPPSs), leading to a paradigm shift toward intelligent manufacturing. Despite the transformative benefits that CPPS provides, its increased connectivity exposes manufacturers to cyber-attacks through exploitable vulnerabilities. This paper presents a novel approach to CPPS security protection by leveraging digital twin (DT) technology to develop a comprehensive security model. This model enhances asset visibility and supports prioritization in mitigating vulnerable components through DT-based virtual tuning, providing quantitative assessment results for effective mitigation. Our proposed DT security model also serves as an advanced simulation environment, facilitating the evaluation of CPPS vulnerabilities across diverse attack scenarios without disrupting physical operations. The practicality and effectiveness of our approach are illustrated through its application in a human–robot collaborative assembly system, demonstrating the potential of DT technology. [ABSTRACT FROM AUTHOR]

The abandonment of inland areas has become a major demographical challenge, causing a condition of local fragility in terms of spatial marginalization. To deal with this issue in Italy, a number of policy actions have been implemented over the time, namely the National Strategy for Inland Areas, established a decade ago, and more recently the Next Generation EU (NGEU) to foster local economic recovery and employment. In this context, RI.P.R.O.VA.RE., a project funded by the former Italian Ministry of the Environment and Protection of Land and Sea (MATTM), was aimed at strengthening the resilience features of communities and territories, focusing on areas within the Matese and Ufita in the Campania region and the Medio Agri in the Basilicata region (southern Italy). Besides the ability to respond to different pressure factors (e.g., of demographic and economic origin), the project also addressed issues concerning seismic and flood risks. This paper synthesizes the methods and tools provided for their analysis and mitigation as a prerequisite for regenerating inland areas. After presenting the developed methods and tools, the results obtained for the Matese study area are presented and discussed. While, on the one hand, the retrieved risk zoning maps allow individuating those municipalities requiring priority structural interventions, on the other hand, the latter are properly individuated based on the peculiar characteristics of urban fabrics. [ABSTRACT FROM AUTHOR]

Kerinci Regency is located on the western to the southwestern part of the capital city of Jambi Province, Indonesia. It has interesting geomorphological sites consisting of the physiography of the Barisan Mountain Zone associated with the Sumatran Fault System known as a volcanic-tectonic complex. Geomorphology has an important role in providing information of the landscape in an area. This paper aims to determine the geomorphological characteristics of the area which can provide information regarding disaster mitigation, the direction of land-use innovation, and infrastructure development strategies. This research uses analyses of morphographic, morphometric, morphogenetic, morphoconservation, and morphochronological aspects. Analysis of satellite images and topographic contours is a method used to determine the characteristics of drainage patterns and geological mapping. A significant result of this research is a geomorphological map of Kerinci that divides the area into several geomorphological units, namely volcanic-denudational, karst, structural, volcanic-structural, structural-denudational, and fluvial morphologies. Based on the geomorphological map, the area has a very high potential hazard consisting of volcanic structural landforms, which are Tanco Isolated Hill (TIH), Kerinci Fault Escarpment Undulation (KFEU), Kerinci Fault Escarpment Volcanic Undulation (KFEVU), structural landforms (Alang Structural Valley (ASV), Kumun Fault Hills (KFH), and Pengasih Fault Undulation (PGFU)). This map can be used to design the Standard Operating Procedures (SOP) for regional development in Kerinci. [ABSTRACT FROM AUTHOR]

This review paper presents an analysis of safety practices in chemical laboratories. It encompasses a systematic exploration of various facets including risk assessment, hazard mitigation, and the implementation of safety protocols. Emphasis is placed on the critical role of continuous education and training, advocating a proactive safety culture, and adapting to technological advancements. Additionally, the paper underscores the importance of adhering to regulatory standards, promoting exceeding baseline compliance toward establishing best practices in laboratory safety. This comprehensive approach highlights the dynamic, multifaceted nature of laboratory safety, positioning it as a fundamental aspect of scientific research. [ABSTRACT FROM AUTHOR]

The rapid advancement of intelligent assisted driving technology has significantly enhanced transportation convenience in society and contributed to the mitigation of traffic safety hazards. Addressing the potential for drivers to experience abnormal physical conditions during the driving process, an enhanced lightweight network model based on YOLOv5 for detecting abnormal facial expressions of drivers is proposed in this paper. Initially, the lightweighting of the YOLOv5 backbone network is achieved by integrating the FasterNet Block, a lightweight module from the FasterNet network, with the C3 module in the main network. This combination forms the C3-faster module. Subsequently, the original convolutional modules in the YOLOv5 model are replaced with the improved GSConvns module to reduce computational load. Building upon the GSConvns module, the VoV-GSCSP module is constructed to ensure the lightweighting of the neck network while maintaining detection accuracy. Finally, channel pruning and fine-tuning operations are applied to the entire model. Channel pruning involves removing channels with minimal impact on output results, further reducing the model's computational load, parameters, and size. The fine-tuning operation compensates for any potential loss in detection accuracy. Experimental results demonstrate that the proposed model achieves a substantial reduction in both parameter count and computational load while maintaining a high detection accuracy of 84.5%. The improved model has a compact size of only 4.6 MB, making it more conducive to the efficient operation of onboard computers. [ABSTRACT FROM AUTHOR]

Snowmelt floods are highly hazardous meteorological disasters that can potentially threaten human lives and property. Hence, snowmelt susceptibility mapping (SSM) plays an important role in flood prevention systems and aids emergency responders and flood risk managers. In this paper, a method of identifying snowmelt flood hazards is proposed, and a large‐scale snowmelt flood hazard zonation scheme based on historical recordings and multisource remote sensing data is established. To assess the quality of our approach, the proposed model was tested in the cold and arid region of Xinjiang, China. Overall, 140 historical snowmelt flood events and 27 explanatory factors were selected to construct a geospatial dataset for SSM of the contemporary period. GridSearchCV was used to comprehensively search the candidate parameters from the grid of given parameters obtained with the random forest (RF) algorithm. Then, the geospatial dataset was divided into two subsets: 70% for training and 30% for testing. Next, SSM results were obtained with the RF algorithm using optimized parameters. The results indicate that our optimized RF classifier performs well for the task of SSM, with a high AUC value (0.975) for the test dataset. The validation and analysis suggest that the proposed method can efficiently identify snowmelt flood hazards in undersampled arid areas at a regional scale. [ABSTRACT FROM AUTHOR]

This research delves into the intricate dynamics of landslides, emphasizing their consequences on transportation infrastructure, specifically highways and roadway bridges in North Carolina. Based on a prior investigation of bridges in Puerto Rico after Hurricane Maria, we found that bridges above water and situated in valleys can be exposed to both landslide and flooding risks. These bridges faced heightened vulnerability to combined landslides and flooding events due to their low depth on the water surface and the potential for raised flood heights due to upstream landslides. Leveraging a dataset spanning more than a century and inclusive of landslide and bridge information, we employed logistic regression (LR) and random forest (RF) models to predict landslide susceptibility in North Carolina. The study considered conditioning factors such as elevation, aspect, slope, rainfall, distance to faults, and distance to rivers, yielding LR and RF models with accuracy rates of 76.3% and 82.7%, respectively. To establish that a bridge's location is at the bottom of a valley, data including landform, slope, and elevation difference near the bridge location were combined to delineate a bridge in a valley. The difference between bridge height and the lowest river elevation is established as an assumed flooding potential (AFP), which is then used to quantify the flooding risk. Compared to traditional flood risk values, the AFP, reported in elevation differences, is more straightforward and helps bridge engineers visualize the flood risk to a bridge. Specifically, a bridge (NCDOT ID: 740002) is found susceptible to both landslide (92%) and flooding (AFT of 6.61 m) risks and has been validated by field investigation, which is currently being retrofitted by North Carolina DOT with slope reinforcements (soil nailing and grouting). This paper is the first report evaluating the multi-hazard issue of bridges in valleys. The resulting high-fidelity risk map for North Carolina can help bridge engineers in proactive maintenance planning. Future endeavors will extend the analysis to incorporate actual flooding risk susceptibility analysis, thus enhancing our understanding of multi-hazard impacts and guiding resilient mitigation strategies for transportation infrastructure. [ABSTRACT FROM AUTHOR]

Hazard identification is a fundamental step in safety management that has the potential to reduce the number and severity of occupational injuries on construction sites. Researchers have identified and evaluated some of the hazards, but few have extensively discussed all of them and none have classified them by sector. The goal of this paper is to fill that research gap by considering hazard identification through an organized synthesis of the existing literature. After a comprehensive literature review, 236 publications were deemed eligible for further analysis. Eighteen safety hazards were identified and then categorized into four groups based on their physiological impacts, ranked based on frequency of citation, and classified by sector. The results revealed that falls from heights, material handling, and heavy machinery were the most frequently cited hazards and the most likely to impact all sectors. Mitigation strategies were also identified, and it was determined that most hazards can be mitigated through the use of personal protective equipment, and effective training and supervision. [ABSTRACT FROM AUTHOR]

Tsunami monitoring and early warning systems are mainly established to deal with seismogenic tsunamis generated by sudden seafloor fault displacement. However, a global tsunami triggered by the 2022 Tonga volcanic eruption promoted the need for tsunami early warning and hazard mitigation of non-seismogenic tsunamis in coastal countries. This paper studied the spatiotemporal distribution characteristics of historical volcanic tsunamis and summarized high-risk areas of volcanic tsunamis. The circum southwestern Pacific volcanic zone, including the Sunda volcanic belt and the Indo-Australian plate, is a concentrated area of active volcanoes and major volcanic tsunamis. In addition, the challenges associated with adapting seismogenic tsunami techniques for use in the context of volcanic tsunamis were elucidated. At the same time, based on historical records and post-disaster surveys, typical historical volcanic tsunami events and involved mechanisms were summarized. The results show that a majority of volcanic tsunamis may involve multiple generation mechanisms, and some mechanisms show geographical distribution characteristics. The complexity of volcanic tsunami mechanisms poses challenges to tsunami early warning by measuring tsunami sources to evaluate the possible extent of impact, or using numerical modeling to simulate the process of a tsunami. Therefore, a concise overview of the lessons learned and the current status of early warning systems for volcanic tsunamis was provided. Finally, a conceptual scheme of monitoring systems for volcanic tsunamis based on historical volcanoes, real-time volcanic eruption information and sea level data, as well as remote sensing images, was presented. [ABSTRACT FROM AUTHOR]

As climate change increases the frequency and severity of wildfires across the Western U.S., there is an urgent need for improved wildfire preparedness and responses. Socially marginalized communities are particularly vulnerable to wildfire effects because they disproportionately lack access to the resources necessary to prepare for and recover from wildfire and are frequently underrepresented in the wildfire planning process. As an exemplar of how to understand and improve preparedness in such communities, this research identified communities in Ventura County facing heightened marginalization and risk of wildfire using spatial analysis. Researchers then deployed a county-wide survey and held focus groups in two communities identified in the spatial analysis. Research revealed that non-English speakers, women, people of color, and newer residents in Ventura County are less prepared for wildfire than other groups. Based on these findings, this paper recommends an expansion of traditional risk mitigation programs, strengthened community engagement efforts, and strategies that increase community resources and leadership to decouple marginalization and wildfire vulnerability. [ABSTRACT FROM AUTHOR]

The landslide dynamics model is one of the methods for evaluating landslide motion processes, contributing to disaster prevention and mitigation. With the advancement of science and technology, GIS has become the mainstream platform for landslide simulation. However, the three-dimensional movement of landslides is intricate, leading to a lack of methods for three-dimensional landslide numerical simulation on GIS platforms. In this paper, we propose a three-dimensional, two-phase landslide dynamics model. Through the proposed solution, three-dimensional modeling and numerical simulation of landslides can be achieved on GIS platforms. Simultaneously, drawing inspiration from the SPH kernel functions, we visualize the results of the three-dimensional model on the GIS platform. Simulation of the Yigong landslide demonstrates that our solution can realize three-dimensional landslide simulation on the GIS platform. Our model adeptly captures numerous details in the landslide motion process. However, constrained by the inherent limitations of the three-dimensional model, the model results are susceptible to numerical oscillations and diffusion, with the accuracy of the model being controlled by grid partitioning. [ABSTRACT FROM AUTHOR]

High-altitude rockfalls, as one of the major geological disasters in mountains, is highly concerned about the study of failure mechanisms and disaster prevention and mitigation. In August 2020, the Babaoshan cliff in Yanhe County, Guizhou collapsed and falling rocks hit agricultural vehicles on the road and damaged residents' houses below. Based on on-site investigation, three rockfall types of tension-rotating, tension-shear-falling, compression-shear exist in the study area, and the compression-shear rockfall can conform to the chain law of rockfall. The paper used the dynamic analysis software Rocpro-3D to simulate and invert the movement characteristics and impact range of rockfall at Babaoshan cliff. The results show that: 1) the hazardous zone, which is about 95 m wide and 175 m long, was formed by the rockfall at R1 and covered localized roads and houses below, with the covered probability of 20%, 17% respectively; 2) the terrains on the rockfall paths in two rockfall disaster events are mainly characterized by stepped shape and overall flat angle respectively, and the behaviors are mainly characterized by ejection and rolling respectively, meanwhile, the times to reach the road and houses were 17 s and 24.3 s, respectively, in addition, the protruding rock mass below the rockfall location gives the falling rock horizontal velocity and good movement space, which will make the falling rock move further away; 3) the different rockfall directions reflect different terrain combinations, simulation inversions reveal that different terrain combinations have significant control over the distance and shape of the rockfall trajectories. And, it was found that the more times a falling rock is rebounded, the greater the energy obtained; 4) the probabilities of falling rocks at H1, H2, H3 invading residential areas are respectively 8.67%, 20%, 19.33%, meanwhile invading road zone are respectively 10.67%, 15.33%, 9.33%. At least one point or several points stopped within the zone of the affected houses in the rockfall disaster event 2 in three prediction of the rockfall impact range, which indicates that there is a great risk that this house will continue to be affected by disasters after rockfalls occur within the steep cliff area above. [ABSTRACT FROM AUTHOR]

Threshold selection is challenging when analyzing tail data with a generalized Pareto distribution. Data below the threshold was not used in the model, resulting in incomplete characterization of the whole data. This paper applied the Gamma distribution, Weibull distribution, and lognormal distribution to fit the central data separately, and a generalized Pareto distribution (GPD) was used to analyze the tail data. In such composite models, the thresholds are estimated directly as parameters. We proposed an empirical distribution function-based parameter estimation method. The absolute value of the difference between the empirical distribution function and the composite distribution function was used as a loss function to obtain an estimate of the parameter. This parameter estimation method is suitable for complex multiparameter distributions. The estimation method based on the empirical distribution function was verified to be feasible through simulation studies. The composite model and the estimation method based on the empirical distribution function were applied to study the earthquake magnitude data to provide a reference for earthquake hazard analysis. [ABSTRACT FROM AUTHOR]

Landslides are common natural disasters that cause serious damage to ecosystems and human societies. To effectively prevent and mitigate these disasters, an accurate assessment of landslide hazards is necessary. However, most traditional landslide hazard assessment methods rely on static assessment factors while ignoring the dynamic changes in landslides, which may lead to false-positive errors in the assessment results. This paper presents a novel landslide hazard assessment method for the Zagunao River basin, China. In this study, an updated landslide inventory was obtained for the Zagunao River basin using data from interferometric synthetic aperture radar (InSAR) and optical images. Based on this inventory, a landslide susceptibility map was developed using a random forest algorithm. Finally, an evaluation matrix was created by combining the results of deformation rates from both ascending and descending data to establish a hazard level that considers surface deformation. The method presented in this study can reflect recent landslide hazards in the region and produce dynamic assessments of regional landslide hazards. It provides a basis for the government to identify and manage high-risk areas. [ABSTRACT FROM AUTHOR]

Earthquakes have great damage potential and importance in risk management and structural engineering, causing fires in buildings such as residences and commercial spaces. Post-earthquake fires (PEF) are secondary disasters that can cause material and moral destruction and loss of life. Similar to natural disasters, they show the time of occurrence and possible scenarios in places. This study aims to analyse and examine what precautions can be taken to prevent or minimize PEF through risk assessment. In this study, a literature review was conducted with the tracking method, focusing on examples from the world where the fires that occur as a secondary effect of the earthquake can cause devastating damages and significant disasters, and inferences are made by classifying the data obtained. Many factors, such as gas leaks due to earthquakes, cracks in pipelines, and short circuits in electrical installations, can cause fires. In addition, flammable liquid or combustible gas emissions and fire protection disturbances create significant fire hazards after earthquakes. In this paper, in which the causes and consequences of fires are analysed, risks, the evaluation process depending on the risks, the precautions that can be taken according to the situations that the risks will cause, and the models developed are emphasized. The research is a reference study with the expectation that there will be an increase in the number of studies examining experimental and physical PEF models. [ABSTRACT FROM AUTHOR]

The share of wind energy in the energy mix is continuously increasing. However, a very important issue associated with its generation is the high failure rate of wind turbines. This situation particularly concerns large wind turbines, which are expensive and have a lower tolerance for system damage caused by various failures and faults. Vulnerable components include sensors, electronic control units, electrical systems, hydraulic systems, generators, gearboxes, rotor blades, and so on. As a result, significant emphasis is placed on improving the reliability, availability, and productivity of wind turbines. It is extremely important to detect and identify abnormalities as early as possible and predict potential failures and damages and the remaining useful life of components. One way to ensure turbine efficiency is to plan and implement preventive repairs. This work shows a semi-Markov model of a preventive maintenance system based on Enercon E82-2 wind turbines. The system's performance quality is evaluated based on profit over time and an asymptotic availability coefficient. The developed model establishes formulas describing the efficiency functions and formulates the conditions for the existence of extremes (maxima) of these functions. Computational examples provided at the end of the paper illustrate the obtained research results. A preventive maintenance model is developed that can be applied to wind turbine hazard prevention (determining optimal times for wind turbine preventive maintenance). [ABSTRACT FROM AUTHOR]

Large-scale two-dimensional hydrodynamic modeling at high resolution is still rarely performed because of its high computational cost and the lack of topographical data for some areas. Despite this, such modeling has been performed for the Odra River, the second largest river in Poland. This river has a high potential for flooding, which has been severely experienced many times in history, most recently in 1997 and 2010, when floods caused large losses. Since then, many different types of activities have been executed in order to reduce the risk of flooding. The paper presents a 2D modeling concept created during these activities. Given that the river valley is up to several kilometers wide, and consists of many complex topographical features and hydrotechnical facilities, a cascade of 25 2D models in MIKE21 software was developed. It covers a 600 km long section of the Odra River and an area of 5700 km2 in total. A regular grid resolution of 4–6 m was used in the modeling. The models were applied for numerous purposes, first for the elaboration of flood hazard and flood risk maps for larger cities, and then for the verification of historic flood data and stage–discharge relations at gauge stations, as well as the verification of design discharges via flood routing. Other important uses were the evaluation of the effectiveness of flood mitigating works, including the feasibility study for the Racibórz reservoir, and the assessment of flood hazard due to embankment failure or ice jamming. Selected applications, as well as practical aspects of the model's preparation and use, are presented. [ABSTRACT FROM AUTHOR]

Fire risk assessment is a crucial step in effective fire control, playing an important role in reducing fire losses. It has remained a significant topic in the field of fire safety. To explore the research hotspots and frontier trends in fire risk assessment and to understand its macroscopic development trajectory, a sample of 1596 papers from 1976 to 2023, extracted from the Web of Science (WoS) database, was utilized to create a knowledge map. The study employed bibliometric methods, visual analysis, and content analysis to uncover the research pulse and hotspots in the field, offering insights into its future development. The findings indicate that research in fire risk assessment has demonstrated continuous growth over the past 50 years. China and the United States are the dominant research forces in the field, while India and Australia show potential as new drivers for development. Expert groups have formed in this field, with intra-institutional cooperation being the primary focus, while inter-institutional collaboration remains limited. The research outcomes exhibit multidisciplinary crossovers, exerting a significant impact on various disciplinary domains. The research hotspots primarily revolve around investigating fire and explosion accidents, assessing the vulnerability of fire subjects, and identifying potential fire hazards. The application of artificial intelligence technology is identified as a pivotal tool for future development. However, to achieve substantial progress, it is important to enhance the importance accorded to fire risk assessment, foster multinational and cross-institutional cooperation, and prioritize research innovation. [ABSTRACT FROM AUTHOR]

Control of OHS risks in the mining industry has been attracting increasing attention in recent years. Because of their great diversity in a complex system, hazards can be difficult to identify and classify, especially when system components interact. Risk cannot be managed successfully without comprehensive investigation of all its aspects. A coherent and integrated classification for identifying and categorizing all hazards is currently lacking in mining. We propose an integrated system classification of OHS hazards in mining based on our review of 44 studies retrieved using PRISMA. Considering Canadian and international standards, regulations and conventions, new hazard categories are proposed and hazard prevention is discussed from 12 perspectives: physical, chemical, biological, ergonomic, accident and psychosocial risks, as well as policy, legislation, management, design, geography, and uncertainty, with reference to each of the four phases of a typical mine life cycle, the hazards were shown in a portrait. This paper provides suitable categories based on rational data for creating a portrait in order to OHS hazards prevention in life cycle activity in mine. [ABSTRACT FROM AUTHOR]

Modern supply chains comprise an increasing number of actors which deploy different information technology systems that capture information of a diverse nature and diverse sources (from sensors to order information). While the benefits of the automatic exchange of information between these systems have been recognized and have led to their interconnection, protecting the whole supply chain from potential attacks is a challenging issue given the attack proliferation reported in the literature. In this paper, we present the FISHY platform, which anticipates protecting the whole supply chain from potential attacks by (a) adopting novel technologies and approaches including machine learning-based tools to detect security threats and recommend mitigation policies and (b) employing blockchain-based tools to provide evidence of the captured events and suggested policies. This platform is also easily expandable to protect against additional attacks in the future. We experiment with this platform in the farm-to-fork supply chain to prove its operation and capabilities. The results show that the FISHY platform can effectively be used to protect the supply chain and offers high flexibility to its users. [ABSTRACT FROM AUTHOR]

Rapid and accurate landslide mapping following extreme triggering events is critical for emergency response, hazard prevention, and disaster management. Artificial intelligence- based approaches enable rapid landslide mapping, yet the lack of a high-resolution globally distributed and event-based dataset poses a severe challenge in developing generalized machine learning models for landslide detection. This paper addresses this issue by designing a diverse coseismic landslide dataset, the Globally Distributed Coseismic Landslide Dataset (GDCLD), which includes multi-source remote sensing images (i.e., PlanetScope, Gaofen-6, Map World, and Unmanned Aerial Vehicle) encompassing various geographical and geological backgrounds worldwide. The GDCLD can be accessed through this link: https://doi.org/10.5281/zenodo.11369484 (Fang et al., 2024). Furthermore, we evaluate the potential of GDCLD by analyzing mapping performance of the seven most popular semantic segmentation algorithms. We further validate the generalization capabilities of the dataset by deploying the models on three types of remote sensing images from four independent regions. Besides, we also assess the model on rainfall-induced landslide dataset and achieve good results, demonstrating its applicability in landslide segmentation under other triggering factors. The results indicate the superiority of the proposed dataset in landslide detection, offering a robust mapping solution for rapid assessment in future extreme events that trigger landslides across the globe. [ABSTRACT FROM AUTHOR]

Bayesian network (BN) is an important tool in probabilistic seismic risk analysis (PSRA) due to its holistic nature and powerful probabilistic inference capabilities. However, while the information that can be stored by BN includes variable values, probability distributions, and relationships between variables, it does not involve event quantities. The results obtained from PSRA and probabilistic seismic hazard analysis (PSHA) are commonly frequency‐related (the number of occurrences per unit time), fundamentally describing event numbers. BN assumes a fixed event number relationship between nodes, but the aftershock counts vary for different mainshock magnitudes. This limitation further restricts its effectiveness in lifespan PSRA for structures. Therefore, this study aims to propose an enhanced BN (EBN) for modeling aftershock PSHA (APSHA) considering frequency information. This paper first introduces the modeling method using BN, including PSHA and a simplified model of APSHA using Båth's law. Next, an EBN that can effectively address frequency issues between the mainshock and aftershocks is presented for modeling APSHA considering the modified Omori's law, while the mathematical principles of both forward and backward inferences for the EBN are elaborated in detail. Then, the article carefully analyzes the utilization of the EBN for APSHA modeling under different scenarios where the information regarding the mainshock is known to varying extents, followed by the extension of the EBN in a time domain to obtain time‐dependent aftershock hazard. Finally, an example of APSHA in a specific location in China is illustrated. [ABSTRACT FROM AUTHOR]

Smart Cities rely on the Internet of Things (IoT) which is characterised by its diverse, distributed and complex infrastructure. These complexities present a range of cybersecurity challenges, making IoT security an area of great importance. The existing vulnerabilities in IoT leaves Smart Cities susceptible to various types of malicious attacks. These vulnerabilities can be exploited, ranging from opportunistic monetary gains to acts of terrorism that disrupt the systems of rival nations. The fact that conventional cybersecurity protection systems cannot be applied to IoT environments in Smart Cities is an additional challenge. The relationship between cybersecurity and IoT security of Smart Cities has become a crucial gap that must be thoroughly investigated. Hence, this paper extensively reviewing the existing literature concerning IoT applications in Smart Cities, with emphasis on cybersecurity and IoT security concerns. This study concludes that real-time threat detection and mitigation by leveraging fog computing and artificial intelligence models represent a significant advancement in securing IoT infrastructure against cyberattacks. The research outcomes contribute to the critical understanding of the challenges regarding IoT security and paves the way for advancing the research of cybersecurity within the Smart Cities ecosystem. [ABSTRACT FROM AUTHOR]

After a landslide, swift and precise identification of the affected area is paramount for facilitating urgent rescue operations and damage assessments. This is particularly vital for land use planners and policymakers, enabling them to efficiently address hazard mitigation, the resettlement of those affected by the hazards, and to strategize land planning in the impacted regions. Despite the importance, conventional methods of monitoring landslides often fall short due to their restricted scope and the challenges associated with data acquisition. This study proposes a landslide detection method based on unsupervised multisource and target domain adaptive image segmentation (LUDAS) that is capable of achieving robust and generalized landslide mapping across multiple sources and target domains. Specifically, LUDAS consists of two phases. In the first phase, we introduce an unsupervised interdomain translation network to align the styles of multiple source domains to multiple target domains, generating pseudotarget domain data. Our interdomain translation network is capable of style transfer between any two domains. Through careful design of the network structure and loss functions, we ensure effective style transfer while preserving the content structure of the source domain images. In the second phase, the landslide segmentation model is trained in a supervised manner using annotated data from multiple source domains and multiple pseudotarget domains, resulting in a model with strong generalization capabilities that can adapt to multiple source and target domains. Finally, through extensive qualitative and quantitative analysis experiments, our study confirms that the proposed domain-adaptive segmentation model not only achieves exceptional landslide segmentation performance across multiple target domains but also, due to its good generalizability and transferability, has great potential for application in the emergency response to landslide. This capability can provide strong support for post-disaster emergency rescue, disaster assessment, and land planning in areas with scarce data. [ABSTRACT FROM AUTHOR]

As a country with the fourth largest population in the world prone to tsunami disasters, Indonesia needs a reliable, timely early warning system to mitigate the impact of disasters. Indonesia cable-based tsunameter (INA-CBT) is an undersea tsunami detection system comprising undersea pressure sensors and a shore station connected by underwater fiber optics designed to provide early warning to the threatened area. Since this system performs a critical role in disaster mitigation, the system must be resilient to link failure and deliver timely warning information. This system is still in its early implementation and still on a small scale. Network-wise, it uses a proprietary Layer 2 (L2) communication protocol. Extending such a network to a larger scale and assessing the system’s performance may introduce challenges due to high costs and offer less flexibility. This paper aims to address those challenges and presents a scalable simulation framework of the INA-CBT system by using L2 open protocols such as spanning tree protocol (STP) and rapid spanning tree protocol (RSTP). The framework is conducted in OMNET++ simulator. The experiment shows that the downtime duration using STP and RSTP is still below the allowed value. RSTP shows a faster failover time than STP, but RSTP downtime duration fluctuates compared to a steady one of STP. The experiments also demonstrated that the variation of downtime is affected by two aspects: the number of ocean bottom units (OBUs) in the network and the position of their blocked port. [ABSTRACT FROM AUTHOR]

The impacts of climate change manifest heterogeneously across regions, and in Khovd City, a semi-arid area in Western Mongolia, the escalating threat of flooding is evident through the occurrence of 10 flash floods in the last 30 years. The risk zone, encompassing rivers and flash floods, endangers ca. 32,000 residents, with 750–1,800 traditional nomadic dwellings (ger s) located on the floodplain of the Buyant River during summer. There is a risk of flash floods in the eastern part of Khovd City from the mountains, while the western part is at a higher risk of flooding from the Buyant River. This paper aims at assessing flood hazards through a detailed topographical survey conducted using an Unmanned Aerial Vehicle (UAV). 15,206 aerial photos were collected in Khovd City using the UAV and measured by Real-Time Kinematic (RTK) on 22 Ground Control Points (GCPs). A Digital Elevation Model (DEM) with a resolution of 2.7 meters was generated from the aerial drone mapping data, enabling surface morphology, hydrological and eight-direction pour point model analysis using a Geographic Information System (GIS). The resulting flood hazard map revealed 4 flood risk areas based on flood flow direction and topographical features. Recommendations for local govern and residents include enhancing flood protection facilities for flood disaster prevention on flood risk zones. [ABSTRACT FROM AUTHOR]

The M w 6.8 Murghob earthquake is the third earthquake in an M w 6.4+ sequence occurring in the Pamir initiated by the 2015 Sarez M w 7.2 earthquake. It is of great significance to investigate their interactions and to assess future seismic hazards in the region. In this paper, we use Sentinel-1 radar interferometric data to retrieve coseismic deformation, invert for the slip distributions of the four events, and then investigate their interactions. The cumulative Coulomb failure stress changes (ΔCFS) suggest that the 2023 Murghob earthquake was promoted by the three prior earthquakes in the sequence. Pre-stress from historical earthquakes is a key factor in explaining the triggering mechanism of the two 2016 M w 6.4+ earthquakes. Stress loading and unloading effects on major faults in the region indicate that future attention should be paid in (1) the segment of the Sarez-Karakul fault north of the Kokuibel Valley, (2) the segment of the Sarez-Murghab thrust fault west of the Sarez-Karakul fault and (3) the east segments of the Pamir thrust fault system, all with a large positive ΔCFS. [ABSTRACT FROM AUTHOR]

Natural disasters such as earthquakes endanger human lives and infrastructure, particularly in urban areas. With the advancements in science and technology in understanding natural hazards, recent studies have attempted to mitigate them by mapping the risks using geospatial technology. In this paper, we attempt to integrate the multi-criteria decision-making (MCDM) models, namely the Analytical Hierarchy Process (AHP) and the Criteria Importance Through Inter-criteria Correlation (CRITIC), besides using the artificial neural network (ANN) to assess the seismic risk in the eastern coast of India. The AHP-CRITIC technique is used to evaluate the earthquake coping capacity and vulnerability and has been further used to generate a training base for earthquake probability mapping by ANN. The earthquake probability and spatial intensity information are used to develop the hazard map. Following that, integrating vulnerability, hazard and coping capacity spatial information assessed earthquake risk. Our results indicate that approximately 5% of the study area is at high risk, whilst more than 11% of the population is at high risk due to seismic induced hazards. The area under the curve of the receiver operating characteristic curve is 0.85, which indicates reliable results. The results of this study may help various agencies involved in planning, development and disaster mitigation to develop seismic hazard mitigation methods by better understanding their impacts on the eastern coastal region of India. [ABSTRACT FROM AUTHOR]

The rock strength in an active fault zone is low and the surrounding rock is fractured and has poor stability, making any subsea tunnel crossing the active fault zone extremely susceptible to disasters such as tunnel collapse, sudden water ingress, and mud inrush. This poses a potential threat to the construction project, making the dynamic stability analysis of a subsea tunnel crossing an active fault zone of great significance. This study takes the second subsea tunnel crossing the Cangkou Fault in Jiaozhou Bay as the engineering background and conducts numerical simulations by employing different lining stiffnesses for tunnel excavation, as well as applying dynamic loads. The dynamic stability of the subsea tunnel crossing the active fault zone is evaluated by comparing and analyzing the lining's displacement, peak acceleration, and stress characteristics. This study explores the disaster-causing mechanisms of active fractures, determining that the hazard of orthogonal misalignment in an active fault zone is the least severe, while the hazard of opposite misalignment is the most severe. This research provides a basis for disaster prevention and mitigation in active fracture zones. [ABSTRACT FROM AUTHOR]

Debris flow is a typical natural disaster in the middle reaches of the Dadu River, Southwest China. Field physical model tests were conducted to reveal the mechanism of river blocking by debris flow in the middle reaches of the Dadu River. The dynamic processes of riHver blocking by debris flows were revealed, and based on which three typical river-blocking modes of debris flow are observed, i.e. thrust-type river blocking, mixed-flow-type river blocking and progressive river blocking. The test results showed that the material composition of debris flows plays an important role in the river-blocking mode, only the tests that adopted the mixed soil and gravel exhibited the thrust-type river blocking mode. The material composition has a controlling effect on the thrust-type river-blocking model. Mixed-flow-type river-blocking mode appears most often in the tests with an intersection angle of 60°, because the small intersection angle is conducive to the mixing of the debris flow and the water in the main channel. The debris flows composed of sand tend to block the river with mixed-flow-type river-blocking mode, accounting for 50% of the occurrences in the model tests. The high flow rate and discharge in the main channel and the low flow rate and discharge in the branch channel are the key factors controlling the progressive river-blocking mode. The test results in this study can support the debris flow disaster prevention and mitigation in this area. [ABSTRACT FROM AUTHOR]