Occurrence Of Disasters Research Articles

Resilience of young adults in Korea: Navigating the impact of collective trauma and anxiety.

Amidst increasing occurrences of disasters and traumatic events, there is growing concern about the declining mental health of young adults, who are facing rising societal pressures and uncertainty about their futures. This study investigates the interplay between collective trauma, anxiety, and resilience among young adults in the Korean context. Based on survey data collected in 2023 from 323 Korean young adults aged 18 to 34 years, a multiple linear regression and independent t-tests were used to examine their experiences of collective trauma, collective anxiety, and resilience, taking gender differences into account. Collective anxiety was associated with resilience, but collective trauma was not. Gender differences were observed: competition- and security-related anxiety, education, and income were positively associated with resilience only for men, while fairness-related anxiety was negatively associated only with women's resilience. Adaptation-related anxiety was a significant factor for both groups. Certain types of collective anxiety and socioeconomic status may act as protective factors against trauma. Gender should be considered when designing mental health assessments and services for young adults to address the unique needs and challenges in building resilience and managing anxiety.

An Intelligent Optimazitation Method for Evacuation Route Planning in the Occurrence of Natural Disasters

This research aims to design and apply intelligent optimization methods using various algorithms to find disaster evacuation routes. The efficiency and effectiveness of evacuation routes are essential in disaster situations to ensure the safety of the affected residents. This research focuses on developing an intelligent optimization method utilizing the Multi Vertex Multi Goals (MVMG) scheme to find optimal evacuation routes. In this scheme, multiple starting points and evacuation destinations reflect the actual conditions on the ground. The Ant Colony Optimization (ACO) algorithm was chosen because of its superiority in finding optimal solutions in dynamic and complex conditions. This research also compares the performance of ACO with traditional algorithms, such as Dijkstra and Breadth-First Search (BFS). The test results show that ACO consistently achieves the lowest evacuation time and the highest efficiency compared to the other two algorithms. In addition, this research opens opportunities for further research by considering complex factors, including traffic congestion and disaster-prone areas, to improve the robustness and application of optimization algorithms in more realistic and dynamic scenarios.

Recovering NDVI over lake surfaces: Initial insights from CYGNSS data enhanced by ERA-5 inputs

The escalating water pollution in many lakes has led to more frequent occurrences of algal bloom disasters in recent decades. The severity of these disasters can be assessed through remote sensing techniques, specifically using the Normalized Difference Vegetation Index (NDVI) for measurement. However, NDVI observations using optical sensors are often affected by cloud and fog in areas with numerous water bodies, such as Taihu Lake. Sensors operating in the microwave band can effectively mitigate this issue, particularly the emerging Global Navigation Satellite System Reflectometry (GNSS-R), which offers high temporal resolution and cost-effectiveness. In this paper, we propose a new method to recover lake-surface NDVI on cloudy days, utilizing GNSS-R observables and auxiliary meteorological data in conjunction with a machine learning regression algorithm called Bagging Tree. We also examine the effective range of GNSS-R data within this application scenario. Meanwhile, the Weighted Linear Regression-Laplacian Prior Regulation Method (WLR-LPRM) image gap-filling algorithm is used as a benchmark to evaluate recovery accuracy. The regression coefficient of NDVI retrieved using the proposed method is 0.95, with a root mean square error (RMSE) of 0.021 and a mean absolute error (MAE) of 0.010. Compared to the previous work on GNSS-R algal bloom detection with overall accuracy of 0.82, this work shows significant improvement in both accuracy and utility. The recovery of lake surface NDVI provides detailed insights into algal blooms, including quantifiable metrics such as the amount and spatial distribution, which are crucial for effective monitoring and management. Additionally, the recovered image textures exhibit high clarity and closely resemble the reference NDVI images. Experimental evaluation using simulated and actual cloud blocks indicates the model’s robustness to recover NDVI under varying cloud cover conditions. In summary, this study demonstrates the capability of GNSS-R aided by supplementary data for recovering missing NDVI values on lake surfaces when optical observations are absent for the first time.

Pengelompokkan daerah rawan bencana di kabupaten Boyolali menggunakan algoritma k-means

The country of Indonesia, which is located in the Southeast Asia region, faces a high challenge of disasters due to demographic, geological and geographical factors that influence the occurrence of disasters, both those caused by natural, non-natural and human factors. In the Province of Central Java, especially Boyolali, disasters pose a significant threat, especially when the weather is uncertain. However, to identify priority areas for the lowest and highest levels of natural disasters in Boyolali, it is necessary to improve using data mining methods, therefore to facilitate analysis and grouping of data in identifying disaster-prone areas in Boyolali, the K-Means clustering algorithm is used. The method used in this research is qualitative and the data is analyzed using the Rapidminer Studio Ver application. 9.10. Based on the results of the analysis, there is a division of disaster-prone areas into 3 clusters in Boyolali Regency, namely very high vulnerability, medium vulnerability, and low vulnerability. The results of calculations with Rapidminer show that there are 3 sub-districts in cluster 2, 2 sub-districts in cluster 1, and 17 sub-districts in cluster 0. It should be noted that manual calculations can produce differences because the cluster center point or centroid is taken randomly for each calculation method. It is hoped that this grouping of areas can be used as a support for the Boyolali regional BPBD to focus on anticipatory steps to reduce the impact of disasters on society that may occur in the future.

A Study of Underwriting Decision Making Based on ARIMA Modeling with Composite Poisson Processes

Facing the problem of frequent occurrence of natural disasters, how to accurately predict the scale of loss and the probability of insolvency is the key for insurance companies to reduce risk and optimize underwriting strategies. This paper explores the multiple influencing factors of catastrophe risk and works to establish a practical risk prediction model. The model is divided into two parts: the first part uses ARIMA model to predict the risk loss, considering the influence of disaster factors, vulnerability, exposure, and disaster prevention ability on the risk size; the second part establishes a positive risk model based on the bankruptcy theory, and assumes that the insurance enrollment process is a composite Poisson process, and constructs a model of the claims process. The probability of insolvency for each year is estimated by substituting the predicted loss values into the claims model and calculating the initial and annual premiums. The study conducted a five-year risk prediction for the Philippines and Australia, and the results show that there is a significant difference in disaster risk management between the two countries, which provides a theoretical basis and practical guidance for subsequent underwriting recommendations.

The impact of diurnal temperature range on the risk of hospitalizations in a low-income setting: the case of the Central Coast of Vietnam.

The study aims to evaluate the effects of diurnal temperature range (DTR) on all causes, cardiovascular and respiratory conditions in the Central Coast of Vietnam, a tropical, low-income region with high DTR exposure but limited research. Daily hospital admission data from the largest hospitals in three provinces were analyzed alongside meteorological data. A time-series analysis using a generalized linear distributed lag model was conducted to examine the non-linear DTR-hospitalization association. A random-effect meta-analysis using restricted maximum likelihood was performed to calculate the pooled effects across three provinces. Stratified analyses by gender, age, season and natural disaster occurrence were conducted to identify vulnerable subpopulations. The multi-province pooled effects indicated that a 1°C increase in DTR raised the risk of hospitalizations for all causes and respiratory diseases by 1.5% [1.2-1.8%] and 0.5% [0.0-1.0%], at lag 0-6 days. The effects of DTR on cardiovascular diseases, as well as those stratified by subgroups, were not statistically significant. Additionally, DTR had a greater adverse effect during the dry season and in the presence of natural disaster. Females and the elderly were slightly more susceptible to respiratory admissions, while males and younger individuals had a higher risk of all-cause admissions due to greater DTR effects. DTR was an independent risk factor for the exacerbation of all and specific causes, particularly among the susceptible subgroups. The findings suggested that it is necessary to take preventive measures to protect these at-risk populations from the adverse effects of extreme DTR exposure.

Analysing the emerging discourses in the Ghanaian media around perennial flooding in Accra

ABSTRACT Climate change coupled with poor urban planning has facilitated the occurrence of flood disasters across cities in the Global South. While the media landscape remains a vibrant platform where expert knowledge is shared about the causes, patterns, risks and mitigation measures of the ravaging flood disasters, there is limited scientific knowledge about how the media narratives evolve and inform better policy formulation in addressing the floods. Using a Corpus-Assisted Discourse Studies (CADS) approach, we explore the discursive construction of perennial flooding in Accra in the Ghanaian press to bring to light emerging discourses around the phenomenon and how that contribute to remedying the problem. The findings revealed a hazy identification of the major causes of the floods in the news, and underscore the urgent need to embrace cogent measures and more proactive policies, firm commitment from the government, stakeholders and the inhabitants in the city to tackle the perennial floods.

Features of causes of indirect certified disaster-related death in areas affected by the Fukushima Daiichi nuclear power plant accident: an observational study

ObjectivesTo investigate the details of disaster-related deaths due to the indirect health effects of the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident following the Great East-Japan Earthquake in 2011 and...

Особливості застосування телемедичних технологій на основі штучного інтелекту в медицині катастроф

Recent years have seen a rapid and exponential growth in the amount of digital health-related data generated by citizens themselves as well as healthcare providers. As a result, due to the spread of medical information technologies, there has been a movement towards universal electronic medical record systems and automated accumulation of patient information. The availability of large data sets, combined with the rapid development of computational data science (including AI-based machine learning techniques), offer promising opportunities for new insights and actionable insights that can significantly improve health outcomes. This more complex, data-rich environment, in turn, enables better clinical decision-making through the support of automated means, encouraging the movement towards intelligent care and diagnostics. Telemedicine technologies are increasingly spreading in health care, achieving various goals, namely remote health monitoring and self-monitoring of patients, which can contribute to the rapid adoption of correct decisions by medical personnel during extraordinary situations and conditions, including the occurrence of natural disasters and man-made disasters.

Mainstreaming disaster risk reduction (DRR) into development: effectiveness of DRR investment in Khyber Pakhtunkhwa, Pakistan

As a low-income country, Pakistan is particularly vulnerable to various natural and human-induced disasters, which have significant consequences for both the environment and human life. A substantial share of the provincial budget is allocated to disaster response and recovery efforts. Prioritizing investment in disaster risk reduction (DRR) is essential to protect lives and assets. Although there is a complex relationship between investments made before and after disasters and their effectiveness in DRR, this dynamic remains insufficiently understood in Pakistan’s Khyber Pakhtunkhwa (KP) province. The current study was designed to analyze the developmental budgeting for DRR in the financial years 2000–2022 in KP province. The Sen’s Slope Estimator and modified Mann-Kendall tests were used to determine the significance trend, while the correlation coefficient test was used to find the correlation between investment in DRR and disaster-induced damages such as deaths, injuries and houses damaged. The study findings reveal that the occurrence of disasters influences post-disaster spending in the KP province, with a significant negative correlation between expenditure and disaster-related damages, implying that increased DRR investment has significantly reduced the consequences of disasters. To minimize vulnerability to future disasters, the province should integrate risk-sensitive planning across all sectoral departments at local, district, and provincial levels, guided by a risk-informed development approach. This proactive strategy would embed disaster resilience within developmental activities, ensuring that each sector aligns with principles of risk reduction and sustainable growth.

Analysis of a Markovian Queue of Single Server Performing in MultiPhase Subject to Disaster, Recovery and Repair

In this paper, we can study about Markovian single-server queue with servers in distinct phases of disaster and repair. The server can stay in full-active Phase or passive Phase randomly and alternately. The server is set to serve in two Phases, such as the full active Phase and passive Phase. When the server operates in full active Phase, the customers arrive and served in First Come: First Serve (FCFS) queue discipline. However, when the server switches from full active to passive Phase, it can only offer to provide service at a rate lower than that of the server in full active Phase. During passive Phase, customers are not allowed to join the system. The server moves to repair Phase immediately after the last customer is served, irrespective of the Phase. The customers will be restricted from joining the queue in repair Phase. After the repair Phase, the server will enter the full active Phase. The server remains in the system for a random period of time. In the event of a disaster, in full active and passive Phases, all customers in system aredropped out, and system moves to repair Phase. The expressions for the steady state probabilities and some key performance metrics are obtained. A numerical illustration is made to study the effects of server shifting from full active phase to passive phase that affects the customers in the system and the occurrence of disaster which has an adverse effect on the customers in that phase.

OGC API: Ldproxy, an Updated and Contemporary Approach to Geodata Provision in Disaster Mapping

Abstract. Natural disaster occurrences have been rising for the past decades. It causes severe damage both in human properties and lives. To minimize the risk caused by disaster and accelerate the recovery, the accessibility of geospatial data is critical. WebGIS utilizes the internet to make the geospatial data accessible to a wider audience. In addition, the emergence of novel standards from OGC APIs also accelerates the accessibility of geospatial data. However, the abundance of Geospatial data requires a better performance of the webGIS. Ldproxy as a tool that follows OGC API standards could be an alternative to traditional tools such as Geoserver. This study focuses on developing a WebGIS application for accessing disaster-related geospatial data and evaluating the performance of Ldproxy in comparison to Geoserver. The method is to build a Single Page Application (SPA) using open-source data from Google Earth Engine (GEE) and OpenStreetMap (OSM). The functionalities of the webGIS enable users to retrieve OSM and GEE data and examine the impact of the disasters. The performance of Ldproxy and Geoserver is tested using Google Light House for comparison. The parameters that are tested are Speed Index, Total Blocking Time, Time to Interactive, Max Potential First Input Delay, Network Server Latency, and Total Byte Weight. As a result, Ldproxy shows slower performance in NSL compared to Geoserver. However, it offers an mvt feature format that makes the feature data can be loaded more efficiently and quickly.

Analysis of Flood Risk in the Lower Hydrographic Basin of the Río Negro (Argentina)

The recurrent floods in the lower hydrographic basin of the Río Negro (RN), documented since 1899, have caused significant damage to the resident population settled in flood-prone areas, whose socioeconomic condition is unfavorable. The aim of this study was to analyze the risk associated with flood occurrences in this area by integrating the flood susceptibility level (hazard) of the study area and the vulnerability of the population. The risk analysis was derived from the algebraic overlay of hazard and vulnerability maps, developed according to criteria published by Renda et al. (2017). In the study area, floods are primarily caused by intense rainfall and winds, upstream water discharges from the Limay and Neuquén rivers, and interactions between increased upstream flow from the lower hydrographic basin of the RN and extreme meteorological events known as Sudestadas. Every certain period, such as every 2 years for winds exceeding 75 km/h and precipitation exceeding 37 mm in 24 hours, as well as every 100 years for flows exceeding 4,000 , the occurrence of floods in the lower basin of the RN is expected to be derived from these events. Based on terrain characteristics and topography, 41.7% of the lower RN basin area showed moderate to high susceptibility to flooding. INDEC data (2010) indicated that 51.0% of the population in the study area was vulnerable to floods due to unfavorable socioeconomic conditions. According to hazard and vulnerability analyses, 43.2% of residents in the lower RN basin lived in high-risk areas, with homes located near the riverbank and on the outskirts of the Viedma-Carmen de Patagones urban conglomerate, hence being the most vulnerable. The results obtained in this research showed the influence of the natural and anthropogenic factors on the occurrence of flood-related disasters in the lower hydrographic basin of the RN. In addition, they served as a preliminary study that will enable decision-makers to create better prevention and mitigation plans contributing to improving the quality of life of its inhabitants.

Using Resistivity Structure to Study the Seismogenic Mechanism of the 2021 Luxian Ms6.0 Earthquakes

Over the past few years, there has been a noticeable change in the occurrence of seismic disasters in Sichuan, China. The focus has shifted from Western Sichuan to the previously more stable Southeastern Sichuan. The recent Ms6.0 earthquake in Luxian, Southeastern Sichuan, on 16 September 2021, has once again captured the interest of scholars, who are closely examining the seismogenic environment and potential seismic hazards in the region. We conducted a magnetotelluric (MT) array survey in the Luxian earthquake area to explore the deep seismogenic environment of the 2021 Luxian Ms6.0 earthquake zone and understand the potential effects of industrial extraction on seismic activities. Here are the insights we obtained: Underneath the anticline in the Luxian Ms6.0 earthquake area, there is a structure that mainly exhibits high resistance. On the other hand, beneath the syncline, a structure with medium to low resistance is observed. The epicenter of the mainshock was identified near the intersection of high- and low-resistance media within the Fuji syncline area. Smaller aftershocks that followed the mainshock were mainly concentrated in the low-resistance layers at depths of 3–5 km in the Fuji syncline area. MT survey results have confirmed the existence of a detachment zone in the shallow crust near the epicenter of the Luxian Ms6.0 earthquake. It is believed that this detachment layer played a significant role in the seismogenic process of the Luxian Ms6.0 earthquake. During different stress conditions, this layer became active and caused the compression and faulting of a hidden fault below, resulting in the Luxian Ms6.0 earthquake. After the main earthquake, a series of smaller aftershocks with varying focal mechanisms occurred as the stress fields continued to release. It is important to note that the Luxian Ms6.0 earthquake highlights the ongoing high stress levels in the southern region of the Sichuan Basin. This emphasizes the need for continued monitoring and consideration of potential seismic hazards in the southern Sichuan area.

Linking regional economic impacts of temperature-related disasters to underlying climatic hazards

Abstract Temperature-induced disasters lead to major human and economic damage, but the relationship between their climatic drivers and impacts is difficult to quantify. In part, this is due to a lack of data with suitable resolution, scale and coverage on impacts and disaster occurrence. Here, we address this gap using new datasets on subnational sector-disaggregated economic productivity and geo-coded disaster locations to quantify the role of climatic hazards on economic impacts of temperature-induced disasters at a subnational scale. Using a regression-based approach, we find that the regional economic impacts of heat-related disasters are most strongly linked to the daily maximum temperature (TXx) index. This effect is largest in the agricultural sector (6.37% regional growth rate reduction per standard deviation increase in TXx anomaly), being almost twice as strong as in the manufacturing sector (3.98%), service sector (3.64%), and whole economy (3.64%). We also highlight the role of compound climatic hazards in worsening impacts, showing that in the agriculture sector, compound hot-and-dry conditions amplify the impacts of heat-related disasters on growth rates by a factor of two. In contrast, in the service and manufacturing sectors, stronger impacts are found to be associated with compound hot and wet conditions. These findings present a first step in understanding the relationship between temperature-related hazards and regional economic impacts using a multi-event database, and highlight the need for further research to better understand the complex mechanisms including compound effects underlying these impacts across sectors.

Effect of Sandstone Pore Morphology on Mechanics, Acoustic Emission, and Energy Evolution

Roadway section form is an important part of the underground engineering structure, and it directly affects the overall stability of the roadway and the occurrence of underground disasters in coal mines. Based on this, this paper adopts a TYJ-500 electro-hydraulic servo rock shear rheology testing machine to conduct a uniaxial compression test on sandstone containing different prefabricated hole section morphology and analyzes the damage characteristics seen during the damage evolution process, with the help of a high-speed camera and acoustic emission monitoring equipment. The test results show that the pore morphology is the main factor affecting the mechanical parameters of sandstone, and the peak stress and elastic modulus of sandstone with pore sections have the characteristics of increasing and decreasing at the same time, except for the intact rock samples. The pore morphology exhibits central symmetry (circular holes and rectangular holes) damage, more pressure-shear cracks and shear cracks, and the acoustic emission characteristics of high-energy–low-amplitude–low-count of the “two low-trend and one high-trend characteristic curves” attributes; moreover, due to the special existence of its pore morphology, it leads to the rock samples having less energy accumulation and release. The axisymmetric hole types (trapezoidal holes and straight-wall domed holes) are damaged by tensile cracks and shear cracks, and their acoustic emission characteristics show the characteristic properties of “three high-trend characteristic curves” of high-energy–high-amplitude–high-count, and there is a strong elastic energy accumulation and output. The conclusions of this article can provide a certain theoretical basis for the design of coal mine roadway sections in underground structures, failure analysis, and stability evaluation of roadway structures.

Towards a Legal Regulation of Insurance Against Natural Disasters in Jordanian Legislation

Objectives: The current study aims at clarifying the legal solutions that can overcome the serious damage caused by natural disasters, within the framework of insurance contracts, and to clarify the mechanisms that enable insurance companies to cover natural disasters' risks. Theoretical Framework: In the first section, the concept of the insurance contract against natural disasters is explained, in the second section, the effects of the insurance contract against natural disasters are addressed while the third section, the confronting the effects of natural disasters' mechanisms are discussed. Methodology: This analytical comparative study addresses insurance against natural disasters in Jordanian legislation by reviewing and comparing the related legal texts in the compared legislations. Results: The study revealed a group of results, the most important among which include that introducing special system for insurance against natural disasters in Jordanian legislation requires that its content be based on the idea of social solidarity and also, the reinsurance process is also one of the means that can contribute to reducing the serious effects resulting from the occurrence of natural disasters. Recommendations: In light of the results revealed, the study concludes with a group of recommendations among which the necessity of formulating a special system for compulsory insurance of real estate properties built on the land of the Hashemite Kingdom of Jordan against the risks of natural disasters, in addition to the necessity of this system adopting a mechanism based on distributing the burden of compensating for damages resulting from the occurrence of these disasters on insurance companies on the one hand and reinsurance companies on the other hand, with the necessity of providing the necessary support from the state in this area.

Forest History Association of Wisconsin

The Enterprise Radiation Forest (ERF) study was initially introduced as a topic of discussion at the Institute of Forest Genetics, USDA, USFS, in the late 1960s. During that period, a program was endorsed for investigating the impacts of radiation on the forest ecosystem. The rationale for this was to facilitate the prediction of potential outcomes in the occurrence of a nuclear disaster. The research location was situated within the forested lands in Enterprise of Oneida County, Wisconsin, United States. The radiation source in question was a 10,000 curie source of Cesium-137, characterized by a halflife of 33 years. Furthermore, a study concerning lichens was also carried out, the data, photographs, and micrographs were meticulously gathered to illustrate the pre-irradiation activity of the species. This subject holds significant value for dissemination among peers in the scientific community, particularly considering the resilience exhibited by natural ecosystems in response to varying levels of radiation. The information is reviewed with the objective of the entire program to ascertain the potential consequences for a northern forest ecosystem in the event of a nuclear disaster, in addition to the two publications from the Atomic Energy Commission.

Advancing Disaster Management through Remote Sensing: Applications, Challenges, and Future Prospects

The increasing occurrence and intensity of natural disasters, driven by factors such as climate change and urbanization, emphasize the urgent requirement for advanced monitoring and management approaches. This study investigates the critical function of remote sensing technologies in disaster management, concentrating on their application across various natural disasters, including earthquakes, floods, landslides, tropical cyclones, wildfires, and droughts. By utilizing satellite, aerial, and ground-based remote sensing techniques, this research illustrates how these technologies enhance real-time monitoring, early warning systems, and recovery efforts following disasters. The results demonstrate that remote sensing provides considerable benefits, such as extensive coverage and the capability to access otherwise unreachable areas, although challenges persist regarding data resolution and integration. Additionally, the study explores future potential, particularly the integration of remote sensing with artificial intelligence and big data analytics. These advancements highlight the essential role of remote sensing in global disaster risk reduction, offering critical insights for policymakers and disaster management professionals.

A scenario study on disaster preparedness behaviours

Abstract Europe has faced several crises over recent years, including the COVID-19 pandemic and the war in Ukraine. Additionally, the climate crisis has led to an increase in the occurrence of extreme weather events and natural disasters. Getting citizens on board when it comes to being prepared for the changing risk landscape in the EU is essential in building societal resilience. The importance of the population’s preparedness to deal with disasters has also been underlined by the Commission’s identification of the Union Disaster Resilience Goals (2023/C 56/01). One of these goals focuses on increasing risk awareness and the adoption of risk prevention and preparedness measures among the population. Research has shown that simply advising people of potential risks in their region is not necessarily sufficient to motivate them to prepare. Yet, preparation is key to an adequate responses in emergency situations and improving preparedness may thus be a powerful tool to support the population’s ability to respond in times of crisis. The EC JRC’s Competence Centre on Behavioural Insights will present a study conducted in five member states (N = ∼1000 per country), which investigates the effect of envisioning a disaster situation, and therefore explicitly eliciting personal affectedness, on individuals’ self-reported preparedness intentions and preparedness behaviours. The study uses multiple measures for intentions and preparedness behaviours, including click-through to external information and an incentivised preparedness game.