Natural Disasters Research Articles

Seismic Behavior of RC Multistorey Building Frame Structure with Different Plan Configuration

Today’s world facing some of the major problems causing by the nature. One of the major natural disasters is the Earthquake. We never know the Direction of the attack and magnitude of the Earthquake, so it will be the challenge the science and Technology. Past few years’ research done on the various issues of Earthquake. Now a Days people live in Multi-Story Buildings such case when Earthquake knockout the populated areas it will be cause massive loss of Damage. Hence Earthquake analysis get importance to Analysis the structure safe against the collapse and design the structure to safe against earthquake occur during the life time of the structure. In this study model a G+11 Structure with square plan configuration in Staad Pro and Analysis the Earthquake analysis of the Structure in seismic city Jabalpur which is located in seismic region III with Soft, Hard and Medium soil with different seismic and structural parameters are used as per Indian Standard code. The analysis is done by using STAAD Pro V8i software by Linear Static Analysis and compared the analysis of RC multistory building framed structure in the term of Maximum Bending MomentStory wise Displacement

National critical infrastructure protection via supply chain security in the United States of America

The protection of critical infrastructure in the United States is vital for ensuring national security, economic stability, and public safety. As sectors such as energy, transportation, water, and communications become increasingly reliant on globalized supply chains, vulnerabilities to cyberattacks, natural disasters, and geopolitical tensions have heightened. This study examines the role of secure supply chain practices, including vendor screening, technology integration, and adherence to regulatory frameworks, in mitigating risks to critical infrastructure. Through content and thematic analysis of secondary data, this research identifies key security measures, such as blockchain, artificial intelligence (AI), and real-time monitoring, which enhance the resilience of supply chains. The study highlights the importance of cybersecurity, intermodal coordination, and geopolitical risk management in safeguarding infrastructure. Case studies, particularly the 2021 Colonial Pipeline ransomware attack, emphasize the need for proactive security measures, such as continuous monitoring, regular cybersecurity assessments, and improved stakeholder collaboration. The study provides strategic recommendations for strengthening supply chain security, including prioritizing vendor screening, adopting advanced technologies, enhancing intermodal coordination, and diversifying supply networks to mitigate geopolitical risks. These measures are essential for reinforcing the resilience, efficiency, and continuity of critical infrastructure in the face of evolving threats.

The Mediating Role of Difficulties in Emotion Regulation and Earthquake Stress Coping in the Relationship Between Posttraumatic Cognitive Attribution and Posttraumatic Stress Disorder in Türkiye 2023 Earthquake Survivors.

Natural disasters such as earthquakes leave deep psychological effects on individuals that can lead to posttraumatic stress disorder, and understanding these effects is vital to support psychological recovery processes after trauma. In this context, the aim of this study was to examine the mediating role of emotion regulation difficulties, religious coping, positive reappraisal and seeking social support in the relationship between posttraumatic cognitive attributions and posttraumatic stress disorder in 2023 Kahramanmaraş Pazarcık, Elbistan and Hatay Yayladağı earthquake survivors (N = 408). The findings from the multiple mediation analysis showed the indirect effect of posttraumatic cognitive attribution on PTSD through difficulties in emotion regulation, religious coping, positive reappraisal, and seeking social support. Therefore, difficulties in emotion regulation may be a risk factor for PTSD, while religious coping, positive reappraisal and seeking social support may be protective factors. Strategies to reduce difficulties in emotion regulation and to improve religious coping, positive reappraisal and social support seeking in earthquake survivors may be necessary to reduce PTSD that may be caused by the earthquake.

A sustainable and resilient humanitarian relief chain network design for distributing assembled relief items dynamically considering perishability, under disruption

Purpose Due to mitigate against natural disasters like earthquake and to distribute relief items, designing humanitarian relief chain networks is an attentional issue. Agile and efficient distribution of relief items after occurring a disaster is significant, especially when some of the relief items are perishable. Therefore, the purpose of this paper is to create a resilient and integrated decision-making structure to distribute relief items at demand points, considering two dimensions of sustainability, under disruption. Design/methodology/approach This study developed a mixed-integer nonlinear mathematical model to handle the pre- and post-disaster planning when a disaster occurs. The represented model has two objective functions: minimizing weighted unmet demand and total costs. Therefore, to convert this multi-objective problem into a single objective one, the e-constraint method was applied. Findings The main results showed that considering some resilience strategies has a significant effect in reducing the weighted amount of unmet demand and saves the total costs. More precisely, considering resilience strategies results in a 60% reduction in total unmet demand and 11% reduction in total pre-positioning costs. On the other hand, reducing the maximum response time with applying resilience strategies is another achievement of the present study. For these reasons, the use of these strategies can reduce people’s pain and suffer from natural disasters. In general, the application and effectiveness of sustainability dimensions and resilience strategies in the introduced humanitarian relief chain network were analyzed. Practical implications To verify the applicability of this study, this model is applied on a probable real-life case study in Tehran. Finally, some managerial insights are discussed to help humanitarian organizations, managers and stakeholders to make better decisions to reduce negative effects of natural disasters. Originality/value This paper introduced a two-stage stochastic mathematical model for designing a resilient humanitarian relief chain network under disruption, at pre- and post-disaster stages. Also, economic and social dimensions of sustainability are considered in this study. Moreover, assembling perishable and im-perishable relief items as relief kits, dynamically is a main contribution of this research.

Vulnerability to natural disasters and sustainable consumption: Unraveling political and regional differences

The urgent calls for action on climate change underscore the importance of increasing sustainable behavior among individuals who have traditionally veered away from it, such as those on the political right. Utilizing data from four geopolitical regions across 24 countries, we explore whether vulnerability to natural disasters, brought on by either experiencing or anticipating a natural disaster, is a crucial factor. We find that as vulnerability to natural disasters increases, sustainable consumption intentions significantly increase among rightists in Western Europe, Israel, and the United States. Environmental motives, rather than economic or trend motives, are found to drive this effect. This suggests that, for rightists, the expectation of being directly impacted by climate change can override their established attitudes and foster more sustainable behavior with the goal of helping the environment. In contrast, the same increase in sustainable consumption intentions is weaker among leftists, who already embrace sustainable behavior. Interestingly, in Central and Eastern Europe, this interplay between political ideology and vulnerability to natural disasters is absent, highlighting the unique postcommunist context of this region. These findings underscore the necessity of tailored strategies for promoting sustainable behavior across regional contexts and provide vital insight into how sustainable consumption may increase among groups that have traditionally resisted it. In a quasiexperiment, we test the potential of an intervention using messages that highlight recent natural disasters in one's locality and demonstrate its effectiveness in pushing rightists toward sustainable consumption.

Enhancing Smart Microgrid Resilience Under Natural Disaster Conditions: Virtual Power Plant Allocation Using the Jellyfish Search Algorithm

Electric power networks face critical challenges from extreme weather events and natural disasters, disrupting socioeconomic activities and jeopardizing energy security. This study presents an innovative approach incorporating virtual power plants (VPPs) within networked microgrids (MGs) to address these challenges. VPPs integrate diverse distributed energy resources such as solar- and wind-based generation, diesel generators, shunt capacitors, battery energy storage systems, and electric vehicles (EVs). These resources enhance MG autonomy during grid disruptions, ensuring uninterrupted power supply to critical services. EVs function as mobile energy storage units during emergencies, while shunt capacitors stabilize the system. Excess energy from distributed generation is stored in battery systems for future use. The seamless integration of VPPs and networked technologies enables MGs to operate independently under extreme weather conditions. Prosumers, acting as both energy producers and consumers, actively strengthen system resilience and efficiency. Energy management and VPP allocation are optimized using the jellyfish search optimization algorithm, enhancing resource scheduling during outages. This study evaluates the proposed approach’s resilience, reliability, stability, and emission reduction capabilities using real-world scenarios, including the IEEE 34-bus and Indian 52-bus radial distribution systems. Various weather conditions are analyzed, and a multi-objective function is employed to optimize system performance during disasters. The results demonstrate that networked microgrids with VPPs significantly enhance distribution grid resilience, offering a promising solution to mitigate the impacts of extreme weather events on energy infrastructure.

Bridging the gap: community health workers as a vital link in humanitarian medical responses

Community Health Workers (CHWs) have proven essential in improving health outcomes and building community trust and their role in humanitarian emergency medical responses warrants further study. We illustrate this point with two case studies, the integration of community health workers into Mobile Medical Teams [MMTs] in both The Bahamas and Sierra Leone. CHWs in these examples came to the forefront of addressing community mistrust for external medical teams, health communication efforts and patient follow-up care. In Sierra Leone, this program resulted in a 32% rise in referrals to established health services. By exploring these contexts, the paper provides a new framework for enhancing humanitarian responses through CHWs, outlining the strategic, logistical, and cultural benefits of such an approach. This research suggests that integrating CHWs with MMT's can bolster health outcomes, especially in communities affected by political instability, natural disasters, and resource limitations. The paper ends by providing policy implications and recommendations for further research on the use of CHWs during a range of emergency contexts.

Disrupting neoliberalism in the academy: Normalizing loss and enfranchising student grief

AbstractDespite long‐standing research demonstrating the prevalence of trauma/loss and increased visibility in the recent pandemic, natural disasters, and political violence, many institutions maintaining neoliberal ideologies and practices minimize or disregard the presence and impact of loss and grief on individuals, families, and communities. This deficit in education informs pedagogical approaches and support gaps wherein students remain the forgotten mourners with missed opportunities for development around the universal human experience of loss. In contrast to the neoliberal academy, drawing on feminist, arts‐based, and trauma‐informed pedagogies, we offer a disruption to neoliberalism by encouraging a theoretical push for scholars to normalize loss in development, enfranchise grief, and promote restorative practices. We share an example featuring art paired with Human Development and Family Science content (Healing in the Arts/HITA), whereby students drew on and/or observed performance art to engage with trauma, loss, and grief. We share strategies for faculty to address trauma and loss and offer resources and support.

Risk Management in Education: A Systematic Literature Review of the Last Five Years

Objective: This article aims to analyze current strategies and practices in risk management in education over the past five years, with a particular focus on identifying the types of risks faced by educational institutions. Theoretical Framework: Risk management in education has gained relevance in a global context marked by natural disasters, health crises and social inequalities. This approach focuses on identifying, evaluating and mitigating risks that may affect the functioning and quality of learning in educational institutions. Method: The methodology used is based on the PRISMA method for systematic reviews, which ensures a rigorous and transparent process. An exhaustive search was carried out in databases such as Scopus, SciELO and Redalyc, applying specific inclusion and exclusion criteria to filter relevant studies published between 2020 and 2024. Boolean operators were used to optimize the search and the information was organized using a matrix of data extraction. Results and Discussion: The results indicate a diversity of risk types that include natural, financial, psychosocial and health crisis-related risks. The strategies implemented by educational institutions have evolved towards more proactive approaches, integrating risk management into their strategic plans. The active participation of students and teachers has been identified as key to fostering a culture of prevention. In addition, it was found that adequate management contributes to minimizing interruptions in learning and improves the general well-being of students. Implications of the Research: This study highlights the urgent need for educational institutions to develop and implement effective strategies to manage identified risks. It is suggested that increased ongoing training and a collaborative approach can strengthen institutional resilience and ensure a safe educational environment. Originality/Value: This systematic review provides a comprehensive view on current practices in risk management in education, highlighting the importance of addressing these challenges from a multidimensional approach. The findings can serve as a basis for future research and for the development of more effective educational policies.

Dataset on Complex Power Systems: Design for Resilient Transmission Networks using a Generative Model

Abstract Interdependent critical infrastructures are prone to be a target of disruptions from either natural disasters or deliberate attacks that can cause a great magnitude of negative consequences on the system. To withstand and reduce the impacts of disruptive events, it is beneficial to consider them in the early stage of design to create a configuration that can maintain its performance as much as possible. However, due to the complexity of modern systems, it is difficult to optimize the large-scale system design with complicated constraints directly. To overcome this issue, it is advantageous to tackle the problem with a state-of-the-art data-driven approach. However, the problem arises due to the limited amount of data for power systems available to the public. Hence, synthesized power systems that resemble existing networks are collected and processed, which can be utilized for implementing machine-learning models. The power system networks are represented as graphs with features holding information on the nodes and edges that relate to electrical components. Using the generated dataset, this research implements a generative approach based on Wasserstein GAN to create intelligent designs. Afterwards, performance measures are employed to induce the generation of a population with more appealing characteristics. To demonstrate the practicality of the dataset on data-driven design, it was applied to train the generative model for the 57-bus system. The results have shown that the model could generate feasible designs of higher resilience.

Machine learning for predicting earthquake magnitudes in the Central Himalaya

Human intervention cannot halt natural disasters like earthquakes, but machine learning application expertise can be utilized to detect patterns in data and increase understanding and predictive power. Recent development of machine learning models has increasingly developed interest in forecasting and predicting the magnitude of earthquakes. In this work, Random Forest Regressor (RFR), Multi-Layer Perceptron Regressor(MLPR), and Support Vector Regression (SVR) models were employed to predict the magnitude of greater than 6 mb earthquakes that occurred in the year 2015 in the central Himalaya. We noticed RFR method had been able to predict the magnitude of the Gorkha earthquake (6.9mb), and the Kodariearthquake (6.7 mb) in comparison with the other two models. We also checked the performance of these models by three parameters Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE) and noticed the better performance of RFR model. The findings illustrate that RFR is achieving better performance than the other two algorithms, as the predicted magnitudes are close to the actual magnitudes.

Caring Through the Trauma of Natural Disasters

Caring Through the Trauma of Natural Disasters

Developing the Recovery Gap Index: A Comprehensive Tool for Assessing National Disaster Recovery Capacities

The increasing frequency and severity of extreme natural events, along with their escalating impacts, highlight the urgent need for robust tools to assess and strengthen national capacities for disaster preparedness and recovery. In this context, this paper introduces one of these tools, called the Recovery Gap Index (RGI), a comprehensive composite index designed to quantify and evaluate the post-extreme natural event response and recovery capabilities at the country level. The tool addresses the need for a systematic approach to quantify resilience and evaluate the impacts of consecutive events on vulnerable areas. The RGI synthesizes data from three well-established indices: the World Risk Index, INFORM, and Global Infrastructure Risk Model and Index (GIRI), covering critical dimensions related to sociodemographic factors, infrastructure, governance, technology, and economic resilience. By extracting key parameters from these diverse indices and aggregating them, the RGI provides a detailed assessment of each nation’s ability to manage the aftermath of extreme natural events. The index findings reveal significant regional disparities in recovery capacities, with European countries exhibiting stronger resilience, whereas many African and Asian nations face substantial challenges. Furthermore, this study proposes several potential future enhancements, such as the incorporation of early warning systems and insurance coverage metrics, aimed at improving its accuracy and practical application. The RGI aims to be a valuable tool for policymakers, disaster management professionals, and stakeholders, enabling them to make informed decisions and implement targeted interventions to further enhance global disaster resilience.

Disaster Mitigation and Emergency Response in the School Environment

Natural disasters are a significant threat in vulnerable areas, including Indonesia which frequently experiences floods, earthquakes, and landslides. This study explores disaster mitigation and emergency response management in schools in Sembakung and Lumbis Districts, Nunukan Regency. The objectives are to understand the challenges, human resource (HR) readiness, availability of facilities and infrastructure, community participation, technology utilization, and post-disaster psychosocial support. Qualitative methods were used with in-depth interviews with school principals, teachers, and staff. The findings show limited disaster mitigation and simulation training, minimal disaster-resistant school infrastructure, and low community participation and technology limitations in remote areas. This study recommends a holistic approach to improving disaster preparedness through training, infrastructure strengthening, community participation, technology utilization, and psychosocial support. Collaboration between government, schools, and local communities is needed to create a safe and resilient educational environment in the face of disasters.

UNet-GCViT: a UNet-based framework with global context vision transformer blocks for building damage detection

ABSTRACT Natural and man-made disasters take place around the world and cause significant financial and human losses. An accurate and fast post-disaster building damage mapping could play a crucial role in rapid rescue planning and operations. Remote sensing satellite images are the main source of building damage map generation. Usually, both pre-disaster and post-disaster satellite images are used for the generation of building damage maps, which encounter some challenges such as registration errors, noise, and atmospheric conditions. This study proposed a new method for building damage detection based only on post images with the UNet architecture network and Global Context Vision Transformer blocks. The deep learning network proposed in this research is automatic without any further processing. The proposed method comprises four main steps: (1) pre-processing, (2) network training, (3) building damage map generation, and (4) accuracy assessment for the final damage map. This network is applied to three different natural and man-made disaster datasets. The first dataset is the post-satellite image of the 2023 Turkey earthquake, the second one is the post-satellite image of the 2021 Bata explosion and the last one is the post-satellite image of the 2011 haiti earthquake. Results of the final building damage map indicate that the proposed method is highly effective with OA above 96%, which is superior to the other deep learning methods.

Artificial Intelligence and its Impact on Social Policy-Making

This study aims to analyze the role of artificial intelligence (AI) in shaping social policies, focusing on its impacts on poverty, unemployment, education, and healthcare. The research explores the concept, origins, types, and dimensions of AI, as well as the stages of social policymaking. It highlights how AI technologies contribute to building simulation models that support governmental decision-making and enhance civic engagement through interactive platforms that allow citizens to express their opinions and participate in policymaking. Additionally, AI facilitates monitoring and analyzing social trends, enabling governments to respond swiftly to social and economic changes and crises, such as pandemics and natural disasters. The study concludes that AI plays a crucial role in improving transparency, building trust in governments, and offering innovative solutions to social challenges.

The Impact of River Mouth Sediment Deposition on Flood Risk: The Case Study of The Sakarya River

Flooding is a natural disaster that causes loss of life and property worldwide. Floods can be predicted and their damages can be reduced. Various natural and man-made factors can cause floods. Sediment movement can be counted as one of the causes of floods, albeit rarely. The Sakarya River bed and river mouth is one of the risky areas for flooding due to sediment deposition. Due to the activities of quarries on the Sakarya River, the amount of sediment carried by the river increases, and the damage to the river bed morphology. In rare cases, the mouth of the river is completely closed due to sedimentation, which has caused many disasters such as coastal flooding and capsizing of marine vessels, leading to loss of life and property. Therefore, the occurrence of floods due to sediment deposition at the mouth of Sakarya River was investigated. The 5, 10, 25, 50, 100, and 500-year return period flows in the downstream part of the Sakarya River and Karasu district were analyzed with the 2D flood model in case of insufficient discharge from the river mouth. Water depth, velocity, and flood hazard maps for these return periods were prepared. The impact of flooding on Karasu district was analyzed in terms of affected buildings and affected area (ha). Thus, the effects of the floods occurring in the downstream region as a result of the interventions to the river bed in the upstream region were analyzed.

Spatial and Temporal Analysis of Earthquake Events in Kahramanmaraş on 6 February 2023

Earthquakes are one of the most destructive natural disasters that occur as a result of the energy resulting from the movements of the earth's crust spreading and shaking the earth's surface. Since it is not possible to predict when and where earthquakes will occur, it has become possible to make various inferences and take necessary precautions by analyzing previous earthquakes. Spatial and temporal analysis of natural disasters such as earthquakes with geographic information systems provides useful information to local and global decision-makers in measures to be taken and mitigation studies. The objective of this study is to demonstrate that the general orientation of stress accumulation on fault lines can be monitored by weighted average centre points with the use of Geographic Information Systems (GIS). Spatio-temporal analyses of two earthquakes with a magnitude of 7.7 Mw and 7.6 Mw in Kahramanmaraş and aftershocks were performed. Ten-week spatial distributions of the aftershocks were examined with the weighted average center method and it was determined that the earthquake intensity and average centers shifted towards the north. When the spatial distribution of the earthquake centers is examined with the help of standard deviation ellipses weekly, it has been determined that they show orientation along the Eastern Anatolian Fault System.

The Impact of Emergencies on Corruption Risks: Italian Natural Disasters and Public Procurement

ABSTRACTTheory and case studies suggest that emergencies and disasters increase corruption, especially in public procurement, hampering relief and reconstruction efforts. Despite a growing interest in the topic, including in research, there is still little systematic evidence about these effects, their structure and trajectories. We set out to investigate the medium‐term impact of disasters on corruption risks, using large‐scale administrative data on public tenders in Italy from 2007 to 2020, combined with data on 5 natural disasters. We employ logistic regression, coarsened exact matching and difference‐in‐differences estimators. We find that disasters increase corruption risks in the medium‐term (3 or more years after the disaster), even more than on the short term (1 year after the disaster). In the matched and diff‐in‐diff analyses, we find 3%–10% points more non‐open procedures used, 19%–21% points fewer call for tenders published, 19%–29% points more tenders with short advertisement period and 14%–17% points more single bidding tenders. Our findings highlight the importance of ring‐fencing corruption risks associated with disaster response, especially in the medium to long term.

Hydrometeorological Disasters in the Context of the Climate Crisis: A Regional Disaster Inventory Study in Türkiye

The rapid growth of the global population, irregular urbanization and industrialization, present challenges to the sustainability of life and the world is currently facing an increasing prevalence of both natural and anthropogenic disasters. Climate change further exacerbates this situation by contributing to the rising frequency and intensity of hydrometeorological events. To effectively minimize the negative impacts of disasters, knowing assessing and analyzingtheir frequency, intensity, and consequences is essential. This necessitates the development of comprehensive disaster inventories. Such studies involve collecting and analyzing critical data to identify and manage potential disaster risks within specific regions. In this present study evaluates the long-term diversity of hydrometeorological disasters in the Sakarya, Kocaeli, and Istanbul provinces, situated in the Çatalca-Kocaeli section in the Marmara Region of Turkey. The study utilizes data from the General Directorate of Meteorology to analyze hydrometeorological disasters occurring from 1975 to 2020 across these provinces, with a focus on diversity, frequency, damages, and fatalities, evaluated on both an annual and seasonal basis. Damages are classified as light, moderate, or severe. This inventory is designed to offer valuable insights for researchers and policymakers aimed at mitigating loss of life and property damage. Additionally, it encompasses recommendations for disaster risk reduction strategies.