Ali Nasiri Khiavi, Mehdi Vafakhah, Dongkun Kim
et al.
ABSTRACT This study develops a comprehensive framework for mapping flood susceptibility and vulnerability in the Cheshmeh‐Kileh forest watershed in northern Iran by integrating remote sensing (RS), local knowledge, and machine learning (ML) algorithms. This was accomplished through the application of various MLs, such as K‐nearest neighbor (KNN), random forest (RF), support vector regression (SVR), and Naive Bayes. In this study, flood susceptibility refers to the physical propensity of an area to experience flooding, influenced by geo‐environmental factors, while flood vulnerability captures the socio‐economic and institutional dimensions that determine a community's ability to cope with and recover from flood events. This research first identified critical geo‐environmental factors influencing flood susceptibility and utilized remote sensing to locate areas prone to runoff generation. Flood risk zoning was then implemented using machine learning techniques in Python. To assess flood vulnerability, data were collected from local residents via questionnaires, focusing on economic, infrastructural‐physical, institutional‐policy, and social‐cultural aspects. The flood vulnerability map was created by integrating these survey results with population density data to identify areas where high social exposure coincides with high physical susceptibility. Findings indicated that the combined remote sensing‐SVR model was the most effective for sensitivity classification, identifying sub‐watersheds 2 and 8 in the Sehezar River (a major basin within the study area) as the areas with the highest and lowest flooding susceptibility, respectively, with sub‐watershed 10 in the Dohezar River (another major basin) being the most vulnerable. The estimated values for Mean Absolute Error (0.041), Mean Square Error (0.042), Root Mean Square Error (0.205), and Area Under the Curve (0.980) demonstrated high model accuracy. The Friedman statistical test showed that the average scores for the different dimensions of vulnerability decreased in the order of: economic (0.48), social‐cultural (0.44), infrastructural‐physical (0.34), and institutional‐policy (0.28). Consequently, the economic dimension was prioritized for its highest score. Flood vulnerability mapping revealed that sub‐watersheds 5, 11, 14, and 15, which had higher population densities, were naturally more vulnerable to floods. This finding reflects a direct relationship between population density and flood vulnerability. Overall, this study underscores the urgent need for effective planning and preventive strategies to mitigate flood risks and enhance resilience in the region.
River protective works. Regulation. Flood control, Disasters and engineering
Rockburst disasters in deep underground engineering present significant safety hazards due to complex geological conditions and high in situ stresses. To address the limitations of traditional microseismic (MS) monitoring methods—namely, vulnerability to noise interference, low recognition accuracy, and limited computational efficiency—this study proposes an intelligent real-time monitoring and early warning framework that integrates deep learning, MS monitoring, and Internet of Things (IoT) technologies. The methodology includes db4 wavelet-based signal denoising for preprocessing, an improved Gaussian Mixture Model for automated waveform recognition, a U-Net-based neural network for P-wave arrival picking, and a particle swarm optimization algorithm with Lagrange multipliers for event localization. Furthermore, a cloud-based platform is developed to support automated data processing, three-dimensional visualization, real-time warning dissemination, and multi-user access. Field application in a deep-buried railway tunnel in Southwest China demonstrates the system’s effectiveness, achieving an early warning accuracy of 87.56% during 767 days of continuous monitoring. Comparative verification further indicates that the fine-tuned neural network outperforms manual approaches in waveform picking and event identification. Overall, the proposed system provides a robust, scalable, and intelligent solution for rockburst hazard mitigation in deep underground construction.
Abstract The eastern coast of India is a hotspot of both heatwaves and tropical cyclones (TCs). However, the potential for TCs to trigger or contribute to subsequent humid heatwaves over land (HHLs) remains unexplored. We assess compound interactions between marine heatwaves (MHWs), landfalling TCs, and HHLs during 1982–2023 at the Bay of Bengal (BoB), considering 33 urban and peri-urban sites within 200 km of coastline. HHLs at these sites demonstrate a significant upward trend, increasing from ~2 events/year in 1982−1991 to 6 events/year in 2014−2023. In contrast, TC-compounded HHLs—comprising 17% HHLs—maintain a stable frequency of ~1.4 events/year. In half of these compound extremes, HHLs follow TCs, often with ~8% higher HHL magnitudes within 5 days of landfall compared to uncompounded HHLs, especially for coastal sites. During the post-monsoon season, 33% of at-site record HHLs follow TCs, with record compounded HHL magnitudes exceeding up to 14% of record uncompounded HHL magnitudes. Meanwhile, over broad ocean areas, MHWs precondition up to 50% of TCs, and strong MHWs precondition up to 33% of rapidly intensified (RI) TCs; for the study sites, up to 50% of RI TCs are followed by HHLs. TC-heat compounding in the BoB—largely affected by MHW−TC−HHL event chains—occurs at rates (identified using seasonally varying thresholds) that notably exceed the previously reported global averages based on fixed thresholds.
Meteorology. Climatology, Disasters and engineering
Rock masses have complex hierarchical structures, and the deformation of rock masses under both static and dynamic conditions is primarily concentrated at weak structural layers, which provides the possibility for the whole translation and rotation of rock blocks, and may induce a new type of nonlinear-alternating displacement waves that are completely different from traditional seismic waves, namely the pendulum-type waves (including longitudinal and transverse pendulum-type waves) and rotational waves. Pendulum-type waves have the characteristics of low frequency, low velocity, large amplitude and high energy, which can cause strong compression and anomalously low friction effect in weak layers of rock masses, and may lead to overall instability and lateral sliding of the roadway structure, thereby inducing the rockburst disasters. At present, the study of pendulum-type waves has obtained many achievements and is gradually being applied in engineering, but there are still many problems to be solved. Therefore, it is necessary to systematically review and summarize the pendulum-type wave phenomenon in blocky rock masses. Firstly, a systematic summary of domestic and foreign research achievements related to the pendulum-type waves is conducted, and the discovery, verification, on-site tests, laboratory tests, theoretical modeling and application of pendulum-type waves are briefly described. Secondly, the research achievements of the author's team in the field of pendulum-type waves in recent years are briefly introduced. Through theoretical analysis and experimental research, the propagation laws and typical characteristics of pendulum-type waves in 1D and 2D blocky rock masses have been thoroughly studied, and the influence of hierarchical structures on pendulum-type wave propagation in blocky rock masses is determined. Furthermore, the application of pendulum-type wave theory in anti-impact support of roadway is analyzed, and the mechanism of low-frequency and low-velocity characteristics, rock rotation and the disaster induced by pendulum-type waves are revealed. Finally, the future research focus and development trend of pendulum-type waves in blocky rock masses are prospected, which can provide reference for related researchers.
Objective and SignificanceAs the coal mining depth increases, coal mining faces increasingly prominent challenges including coal and gas outbursts, rock bursts, and compound dynamic disasters. Deepening the understanding of disaster-causing mechanisms and developing diversified prevention and control technologies are significant for the safe production of coal mines. Employing the key technologies for coalbed methane (CBM) production to control gas-related dynamic disasters is an inevitable course for the safe production of coal mines. However, large-scale, suitable technology systems are yet to be developed. MethodsFrom the perspective of the application of key technologies for surface CBM production, this study systematically reviews the development history and research advances in technologies including well drilling and completion for CBM production and fracturing. From the angle of coal mine safety, this study organizes the disaster-causing mechanisms and critical control technologies for gas dynamic disasters over the past 70 years. In combination with the characteristics of CBM production technologies and the demand for the prevention and control of dynamic disasters in coal mines, this study proposes some suggestions for theoretical innovation and technological breakthroughs. Results and ConclusionsIn terms of theoretical research, it is necessary to deepen the comprehensive exploration of coals and CBM and conduct fine-scale geological studies by integrating multiple approaches. Regarding control technologies, efforts should be made to further explore the control technologies for coal and gas outbursts and rock bursts, with the former including (1) outburst elimination using cavity-type tube wells+high-pressure air/liquid nitrogen/CO2 scrubbing + negative-pressure drainage and (2) multistage fracturing of L-shaped surface horizontal wells+production and the latter including (1) multistage hydraulic fracturing of roofs using L-shaped wells and (2) proppant injection-based multistage hydraulic fracturing for roofs using L-shaped wells+production. Accordingly, advanced technologies such as multistage fracturing of L-shaped wells for CBM production should be employed to conduct on-site experiments on gas dynamic disaster control. It is necessary to explore the applicability of varying prevention and control theories and technologies under different geologic conditions based on scientific research and engineering integrated engineering and projects and develop technology systems for the prevention and control of gas dynamic disasters in coal mines, thus providing robust support for the safe production of coal mines in China.
Abstract Under the influence of factors such as climate and land use changes, it is highly useful to investigate the spatio-temporal occurrence characteristics of forest fires using remote sensing data. This study utilized long-term remote sensing data on Active Fire Spots (AFSs), Burned Areas (BA), and Land Cover Types (LCT) in Yunnan Province. Through pixelization of AFSs, spatial extraction, and spatio-temporal clustering, 39,101 Forest Fire Events (FFEs) were identified. The results indicate that FFEs in Yunnan Province exhibit spatio-temporal clustering, with an overall annual fluctuating decline trend. The clustering is more pronounced in spring and winter, with a delayed temporal span. Over 88% of FFEs are concentrated in southern Yunnan, and the frequent occurrence areas have shifted eastward in recent years. This study deepens the understanding of the spatio-temporal dynamics of forest fires and provides a basis for regional forest fire management to promote sustainable development in related fields.
Meteorology. Climatology, Disasters and engineering
Knowledge gaps and management shortcomings contribute to catastrophic dam failures On 25 January 2019, the structure damming a pond filled with iron ore mining wastes (tailings) burst at Brumadinho, Brazil (1), causing a massive mudslide that killed at least 232 people. This tailings dam failure was only the most recent in a long list of catastrophic tailings dam accidents (see the first figure) (2, 3). Similar accidents also occur at electric power stations, where ponds are used to store coal combustion residuals such as fly and bottom ash. There are about 1000 operating ash ponds in the United States (4), and coal consumption patterns suggest that there may be more than 9000 worldwide. The catastrophic accident at the Kingston fossil power plant in Tennessee in 2008 (5) highlights the destructive potential of ash pond failures. Detailed analysis of tailings dam and ash pond failures shows that little-understood processes such as time-delayed triggering mechanisms are more likely to manifest when best engineering practices are disregarded.
Preventing/mitigating natural disasters in urban areas can indirectly be part of the 17 sustainable economic and social development intentions according to the United Nations in 2015. Four types of natural disasters—flooding, heavy rain-induced slope failures/landslides; earthquakes causing structure failure/collapse, and land subsidence—are briefly considered in this article. With the increased frequency of climate change-induced extreme weathers, the numbers of flooding and heavy rain-induced slope failures/landslides in urban areas has increased in recent years. There are both engineering methods to prevent their occurrence, and more effectively early prediction and warning systems to mitigate the resulting damage. However, earthquakes still cannot be predicted to an extent that is sufficient to avoid damage, and developing and adopting structures that are resilient against earthquakes, that is, structures featuring earthquake resistance, vibration damping, and seismic isolation, are essential tasks for sustainable city development. Land subsidence results from human activity, and is mainly due to excessive pumping of groundwater, which is a “natural” disaster caused by human activity. Countermeasures include effective regional and/or national freshwater management and local water recycling to avoid excessive pumping the groundwater. Finally, perspectives for risk warning and hazard prevention through enhanced field monitoring, risk assessment with multi-criteria decision-making (MCDM), and artificial intelligence (AI) technology.
Background Marine geological disasters (i.e., catastrophic events occurring in marine environments) may seriously threaten the safety of engineering facilities, life, and property in shallow- and deep-sea areas. The development of marine resources and energy and the protection of the marine geo-environment are topics of intense interest globally, and these activities inevitably require the assessment of marine geological disasters, which are receiving increasing attention from academic and industrial communities. However, as a prospective analysis for the risk assessment and management of marine geological disasters, the susceptibility of marine geological disasters, referring to a qualitative or quantitative description of the type, volume (or area), and spatial distribution of existing or potential geological disasters, is still in the exploration stage. Results In this study, we systematically combine the theoretical basis and methods for the analysis of the susceptibility of marine geological disasters (i.e., heuristic approach, deterministic approach, and statistical approach). Taking two widely studied marine geological disasters (i.e., seabed liquefaction and submarine landslides) as examples, we review their triggering mechanism, condition factors, methodological advances, and susceptibility maps. Subsequently, some challenges in the susceptibility assessment of the marine geological disasters associated with seabed liquefaction and submarine landslides and extension to other types of marine geological disasters are briefly summarized and discussed, involving an incomplete evaluation system, poor applicability of methods, and insufficient databases. Conclusion Based on a literature review using the extensive literature database, we focused on the susceptibility of two typical marine geological disasters (i.e., seabed liquefaction and submarine landslides) and systematically summarized the development history, methods, results, problems, and future directions. According to the challenges of this field, we recommend that relevant organizations focus on the construction of a susceptibility system and study the triggering mechanisms of marine geological disasters. Long-term in situ observation efforts should also be supported to obtain more data to improve the disaster inventory. Ultimately, more reliable methods can help improve the credibility and usefulness of susceptibility analysis results.
Nigeria is susceptible to flood disasters, resulting in significant economic and social costs due to natural and human factors. This paper examines the implications of flood disasters on Nigeria's sustainable national development by identifying drivers, estimating costs, analyzing social dimensions, and discussing policy options. The methodology this paper adopted relied on a range of secondary sources such as government reports, academic studies, and media sources which were analyzed through qualitative methods of content and thematic analysis. The study revealed that flood disasters caused economic losses, including damage to infrastructure, loss of income, and reduced agricultural production, disproportionately affecting vulnerable populations. Effective disaster risk management requires an integrated approach, including investments in flood risk infrastructure, coordination among government levels, and engaging local communities to build disaster reduction capacity. The paper highlights the need for Nigeria to mainstream disaster risk reduction into national development planning for sustainable development.
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.
A large number of communities are impacted annually by the increasing frequency of tornado hazards resulting in damage to the infrastructure as well as disruption of community functions. The effect of the hazard geometry (center and angle of tornado path as well as the tornado width) is studied herein on how it influences the recovery of physical and social systems within the community. Given that pre-disaster preparedness including mitigation strategies (e.g., retrofits) and policies (e.g., insurance) is crucial for increasing the resilience of the community and facilitating a faster recovery process, in this study, the impact of various mitigation strategies and policies on the recovery trajectory and resilience of a typical US community subjected to a tornado is investigated considering different sources of uncertainties. The virtual testbed of Centerville is selected in this paper and is modeled by adopting the Agent-based modeling (ABM) approach which is a powerful tool for conducting community resilience analysis that simulates the behavior of different types of agents and their interactions to capture their interdependencies. The results are presented in the form of recovery time series as well as calculated resilience indices for various community systems (lifeline networks, schools, healthcare, businesses, and households). The results of this study can help deepen our understanding of how to efficiently expedite the recovery process of a community.
Disasters and engineering, Cities. Urban geography
Jenny Villalobos-Sequeira, Jacqueline Centeno-Morales, Stephanie Cordero-Cordero
et al.
The increase in floods as a consequence of climate change is causing considerable concern in vulnerable localities. The community of Pandora Oeste in Costa Rica has experienced increasingly frequent flooding. Therefore, the aim of this study was to describe the social vulnerability to flood risk, associated with people and housing characteristics, as well as current conditions, to generate information that contributes to integrated risk management. The action-research methodology utilized allowed the development of joint activities between local actors and academia to better understand several variables that influence social vulnerability. To achieve this, a survey was administered to community residents, and a social mapping workshop was conducted with the participation of members of the Valle la Estrella Community Emergency Committee. This gathered information serves as an input for community decision-making, directing efforts toward the implementation of flood risk mitigation actions. At the same time, the results have established an approach to the flood problem, providing the methodological scenarios implemented, which could potentially be replicated in other communities, including new perspectives from community management to the articulation of actors, strengthening shared responsibility for social resilience in the face of future extreme weather events.
Shelter is one of the most ‘intractable problems’ in humanitarian aid and yet there is little clarity on an overarching definition. Terminology for shelter and housing is often conflated, and the most prominent definition does not fully reflect recent progress in the Shelter and Settlements Sector. This paper explores the varying terminology utilised in definitions of shelter within humanitarian aid since 1990, reflecting on the concepts of ‘shelter’ and ‘housing’, alongside surrounding perceptions of ‘house’ versus ‘home’, and related measures of adequacy. The current, most prolific definition is also deconstructed, demonstrating ambiguity in some of terminology such as ‘dignity’ and ‘privacy’, and revealing that interpretation of this definition depends on the reader's knowledge. Lastly, a new definition of ‘sheltering’ is proposed, encompassing five key reflections: the concept of process over object; the inclusion of communities and individuals; the commonality of long‐term sheltering; the wider effects of shelter; and the impacts on host communities and environment.
Aiming at the problem of equipment failure in power distribution rooms under extreme rainstorms, a method for evaluating the probability of equipment failure during rainstorms and a risk assessment index for distribution networks are proposed. Firstly, based on historical data, a flooding model is used to simulate the dynamic process of flooding in cities under extreme rainstorm disasters. Secondly, the fault model of component is used to calculate the distribution equipment failure probability of IEEE 33-bus distribution network during the process. Finally, a hybrid Monte Carlo is used to get the operational status of distribution network and calculate the minimum lost load of the distribution network in order to propose a risk assessment index under this disaster. The method can provide a reference for emergency warning and disaster prevention and mitigation under extreme rainstorm disaster in a particular region.
Akylina Mereli, Evelpidou Niki, Sarantos Psycharis
et al.
The goal of our research is to educate students at primary schools in Greece on rapid ongoing natural disasters through the holistic-interdisciplinary science, technology, engineering, art, and mathematics (STEAM)-based method. As a learning tool, an integrated program was designed with a variety of actions and activities aiming to experientially educate students in a holistic-interdisciplinary STEAM-based way. These are based on science, technology, engineering, art, and mathematics. This three-month program was chosen to be conducted in a private school of Attica, Greece, for the course “skill laboratories”. It was conducted to students of the second (seven years old) and the fifth grade of primary school (10 years old). In the beginning and the end of the program, the 133 participating students were given questionnaires, in order for the program to be assessed as to whether it managed to accomplish the initial goals. A total of 266 digital questionnaires were collected through ArcGIS survey123 application (part of geospatial cloud by Esri), which is an integrated solution for the creation, distribution and analysis of survey data. From the statistical analysis of their answers, the conclusion was that the vast majority of the students felt stress, confusion, depression and shock when they saw a forest fire. Most kids stated that they have thought of the consequences of extended wildfires and the flood events that follow.
Flood, typhoon and heat wave are common natural disasters in the world. Satellite remote sensing technology has become an effective method for geological hazard assessment due to its wide coverage, large imaging area and high time resolution. Based on introducing the research progress of flood disaster remote sensing monitoring, this paper compares and summarizes the research progress of principle and method of multi-source remote sensing flood monitoring, and analyses the advantages and disadvantages of various data. We also analyze the comprehensive application of remote sensing technology in typhoon monitoring from the perspectives of conventional observation data, satellite remote sensing data and unmanned aerial vehicle remote sensing data. In this paper, remote sensing technology is also used to monitor urban heat island and other climatic problems through machine learning, starting from solving heat wave problems in the climatic field by remote sensing. At the same time, the existing problems of various data resources in the analysis of various disasters are summarized, and the remote sensing technology which needs to make comprehensive use of multi-source data, the construction of climate monitoring system and other aspects are summarized to study the remote sensing information system in the field of natural climate disasters. The development trend of this technology is also summarized and prospected.