Disaster Damage Research Articles

The Unequal Impact of Disasters: Assessing the Interplay Between Social Vulnerability, Public Assistance, Flood Insurance, and Migration in the U.S

Extreme weather events, such as hurricanes with intense rainfall and storm surges, are posing increasing challenges to local communities worldwide. These hazards not only result in substantial property damage but also lead to significant population displacement. Federal disaster assistance programs are crucial for providing financial support for disaster response and recovery, but the allocation of these resources often unequal due to the complex interplay of environmental, social, and institutional factors. Relying on datasets collected from diverse sources, this study employs a structural equation model to explore the complex relationships between disaster damage (DD), social vulnerability (SV), public disaster assistance (PDA), the national flood insurance (NFI), and population migration (PM) across counties in the contiguous US. Our findings reveal that communities with lower SV tend to experience higher levels of DD across US counties. SV is negatively associated with PM, PDA, and NFI, both directly and indirectly. Furthermore, PDA is positively linked to PM, whereas DD has a direct negative effect on PM but an indirect positive effect through PDA.

A Survey on Advanced Persistent Threat Detection: A Unified Framework, Challenges, and Countermeasures

In recent years, frequent Advanced Persistent Threat (APT) attacks have caused disastrous damage to critical facilities, leading to severe information leakages, economic losses, and even social disruptions. Via sophisticated, long-term, and stealthy network intrusions, APT attacks are often beyond the capabilities of traditional intrusion detection methods. Existing methods employ various techniques to enhance APT detection at different stages, but this makes it difficult to fairly and objectively evaluate the capability, value, and orthogonality of available techniques. Overly focusing on hardening specific APT detection stages cannot address some essential challenges from a global perspective, which would result in severe consequences. To holistically tackle this problem and explore effective solutions, we abstract a unified framework that covers the complete process of APT attack detection, with standardized summaries of state-of-the-art solutions and analysis of feasible techniques. Further, we provide an in-depth discussion of the challenges and countermeasures faced by each component of the detection framework. In addition, we comparatively analyze public datasets and outline the capability criteria to provide a reference for standardized evaluations. Finally, we discuss insights into potential areas for future research.

A Disparate Disaster: Spatial Patterns of Building Damage Caused by Hurricane Ian and Associated Socio-Economic Factors

The literature shows that communities under different socio-economic conditions suffer different levels of damage in disasters. In addition to the physical intensity of hazards, such differences are also related to the varying abilities of communities to prepare for and respond to disasters. This study analyzes the spatial patterns of building damage in Hurricane Ian in 2022 and investigates the socio-economic disparities related to the damage. Specifically, this study employs NASA’s Damage Proxy Map (DPM2) to analyze spatial patterns of building damage caused by the hurricane. Then, it uses statistical analysis to assess the relationships between building damage and hurricane intensity, building conditions, and socio-economic variables at the building and census tract levels. Furthermore, the study applies geographically weighted regression (GWR) to examine the spatial variation of the damage factors. The results provide valuable insights into the potential factors related to building damage and the spatial variation in the factors. The results also reveal the uneven distribution of building damage among different population groups, implying socio-economic inequalities in disaster adaptation and resilience. Moreover, the study provides actionable information for policymakers, emergency responders, and community leaders in formulating strategies to mitigate the impact of future hurricanes by identifying vulnerable communities and population groups.

Assessing social equity of federal disaster aid distribution: A nationwide analysis.

In this study, we conduct the first comprehensive, nationwide assessment of social equity performance of multiple federal post- and pre-disaster assistance programs that differ in targeted recipients, project types, forms of aid, and funding requirements. We draw on the social equity and distributive justice theory to develop and test a set of hypotheses on the influence of program design and specificity on their aid distributional patterns and equity performance. The analysis uses panel data of about 3000 US counties to examine the relationship between a county's receipt of federal assistance and its recent disaster damage, socioeconomic, demographic, political, local government, and geographic characteristics in a two-stage random effects Tobit model. Expectedly, we find that post-disaster grants are largely driven by recent disaster damage, while damage is simultaneously influenced by local socioeconomic conditions. For all disaster programs, disproportionately more federal aid is allocated to populous counties. For programs geared toward state and local governments and targeting community recovery and mitigation, more aid is received by counties with better socioeconomic conditions. Conversely, for programs targeting individual relief and recovery, more aid is given to counties with lower incomes and greater social vulnerability. Results also indicate that counties located in high-risk regions receive greater outlays. These findings shed light on the varying degrees of social equity of federal disaster assistance programs tied to their cost-share requirement, funding caps, and inherent complexity of application procedures.

A method for assessing the resilience of urban interdependent systems integrating physical damage and social loss

As systems in urban areas become increasingly interdependent, the effects of disasters extend beyond facilities damage, precipitating casualties, and public service disruptions. Establishing a holistic resilience assessment method is crucial for urban sustainability planning. Existing resilience assessment methods often focus on the physical damage; however, few studies examine the social loss. This study proposes a resilience assessment method that integrates physical damage and social loss. A multilayer network model of physical-social systems is first developed based on their interdependency. Then, the evolution of disaster damage within and between systems process, and the multi-task parallel restoration process are quantified. Resilience is assessed by measuring dynamic changes in service supply and demand throughout these processes. The method considers social loss as a combination of population harm and service interruption caused by physical damage. The proposed method was applied to an urban area in Southern China. The results reveal the impact of seismic events on infrastructure, buildings, and populations. Furthermore, they demonstrate the coupling impacts of supply and transportation on emergency and healthcare systems’ resilience. This comprehensive method could facilitate the development of efficient strategies to improve urban resilience to disasters.

Government emergency budgeting and disaster impact: Evidence from China

AbstractEmergency budgets have become indispensable fiscal tools for governments around the world to cope with disasters, but how governments determine the size of emergency budgets and to what extent such budgets are effective remain unclear. Drawing on organizational learning theory and using data collected from 30 provinces in China, we conduct a series of panel regression analysis and robustness checks to investigate the determinants and impact of emergency budgets. We find that both prior disaster experience and government fiscal ability as measured by budget surplus are positively related to the size of subnational governments' emergency budgets, but the interaction effect between the two is negative. Moreover, while emergency budgets can help maintain the level of government budget surplus, they only play a limited role in moderating the negative impact of disaster damage on governments' fiscal ability. In particular, this study reveals the importance of socioeconomic environment and organizational capacity for the decision‐making process and outcomes of emergency budgets, suggesting that subnational governments should always adopt a holistic approach and improve their financial preparedness for future emergencies by incorporating more information from past disasters and considering diverse drivers of the complex dynamics among emergency budgets, disaster experience, and government fiscal ability.

Indonesian economy under the shadow of catastrophic natural disasters: empirical evidences from additive mixed model with P-Spline smooth function

As located within the Ring of Fire with more than half of the volcanoes are active making Indonesia as one of the most vulnerable countries to natural disasters. Moreover, Indonesia was ranked 12th of 35 countries with the highest risk from natural disasters by the World Bank in 2021. Such multiple disasters could hamper the Indonesian economy through disaster loss. This study is conducted to investigate the impact of several natural disasters, including hydrological, meteorological, climatological, and geophysical, on Indonesian economic growth of 34 provinces in Indonesia from 2018 to 2022 represented by annual per capita real output growth. While the disaster damages are measured by the number of affected people and the number of damaged infrastructures. The econometric approach of panel data analysis is employed and further extended to the additive mixed model with P-spline smooth function to capture the non-linear relationship. The human development index (HDI) and financial realization of the unexpected budget are also incorporated in the models. The results show that the best model, the P-spline model, could capture the nature of the non-linear relationship between natural disasters and economic growth. In addition, the estimation process is also carried out separately for each group based on the HDI and financial ability. The variation of impact behaviour from natural disasters is clearly revealed by modelling each group based on HDI and financial ability indicating that each provincial group has a different impact transmitted by the natural disasters.

Major recent failures in Brazilian mine waste containment facilities, current cases of maximum emergency level and imminent risk of rupture, and a brief sustainability analysis.

Wasteisthe materials left over after the processing of ores. Significant disasters involving waste disposal structures have occurred in Brazil in recent years and caused severe damage by contaminating soil, rivers and coastal areas, destroying native fauna and flora, interrupting the water supply and compromising its potability, putting the population's health, livelihoods and economy at risk, as well as causing 289 irreparable human deaths. Regulatory laws have become stricter, and since 2019, after the tailings dam tragedies occurred in 2015 and 2019 in Mariana and Brumadinho, in Minas Gerais, the operation of upstream-raised tailings dams has been prohibitedin Brazil. In 2022, a waste slide from a sterile pile at the Pau Branco Mine in Nova Lima promoted a dike overflow. There was the death of five people whose car was buried by a landslide on a hillside. New strategies and technologies, such as reprocessing and recycling, can be tested to ascertain whether they can help improve practices in tailings management. Indeed, mining companies' corporate responsibility and sustainability practices need to be evaluated toverify whether they better match expectations. On the other hand, more specific and detailed regulations and resolutions are required to ensure the safe monitoring and management of sterile waste piles. This paper presents a review of the facts, a discussion of the literature (mainly on recent tailings dam disasters), the current situation of mining-containingwaste structures in Brazil, a brief sustainability analysisand perspectives aimed at preventing/minimising catastrophes in the future.

Training on creating learning media for handling of disaster mitigation for elementary school teachers

Background: Indonesia is known as a disaster-prone country, the total amount of damage due to disasters is said to be the fourth largest in the world. The impact of global warming results in very high rainfall and large-scale damage. Apart from weather disasters, a number of damages also occur due to geological disasters. To stop disaster damage in the long term, it is important to create sustainable communities. It is important not to separate the environment and disaster prevention, but to learn about the nature that sometimes threatens us just as we learn about the nature around us. Under these conditions, until now Indonesia has not included practical disaster education in the learning curriculum, because it is considered important to include disaster management training in school communities. Because of this, disaster management methods were tested in Japan, tested in elementary schools in the city of Mataram, Indonesia. This research aims to evaluate whether adapting traditional Japanese educational methods such as "exploring the environment (Machitanken)" and "picture story performances (Kamishibai)", and presentations (hapyoukai) are adapted to local conditions. existing policies in Indonesia, can be applied in Indonesia. Methods: This research was conducted in the city of Mataram, carried out for one year via Zoom, involving 7 elementary school teachers, one middle school teacher, three lecturers. Findings: The participants were given knowledge about how to provide disaster education. Conclusion: To further strengthen teachers' abilities and skills in teaching about disasters, teachers were given training for 6 months via Zoom and for one week in Kitakyushu City to make teaching materials. Novelty/Originality of this Study: The novelty of this study lies in its implementation of disaster mitigation education for elementary school teachers in Mataram using traditional Japanese methods such as Machitanken and Kamishibai. This approach is unique as it integrates cultural techniques from Japan into the Indonesian educational context, aiming to enhance teachers' ability to educate students on disaster preparedness in a practical and engaging manner.

A method to describe attenuation of river contamination under peak flows: Can the public water supply from Paraopeba River finally return after the Brumadinho dam disaster?

Tailings dams' disasters begin a stage of river water contamination with no endpoint at first sight. But when the river was formerly used for public water supply and the use was suspended as consequence of a dam break, a time window for safe suspension lift must be anticipated to help water managers. The purpose of this study was to seek for that moment in the case of Brumadinho dam disaster which occurred in 2019 and injected millions of cubic meters of iron- and manganese-rich tailings into the Paraopeba River, leading to the suspension of public water supply to Belo Horizonte metropolitan region with this resource, until now. To accomplish the proposed goal, an assemblage of artificial intelligence and socio-economic development models were used to anticipate precipitation, river discharge and metal concentrations (iron, manganese) until 2033. Then, the ratios of metal concentrations between impacted and non-impacted sites were determined and values representing extreme events of river discharge were selected for further assessment. A ratio ≈1 generally indicates a similarity between impacted and non-impacted areas or, put another way, a return of impacted areas to a pre-rupture condition. Moreover, when the ratio is estimated under the influence of peak flows, then a value of ≈1 indicates a return to pre-rupture conditions under the most unfavorable hydrologic regimes, thus a safe return. So, the extreme ratios were plotted against time and fitted to a straight line with intercept-x representing the requested safe time. The results pointed to 6.57 years after the accident, while using iron as contaminant indicator, or 8.71 years when manganese was considered. Despite of being a relatively low-risk timeframe, the suspension lift should be implemented in phases and monitored for precaution of potential sporadic contamination events, while dredging of the tailings from impacted areas should continue and be accelerated.

Knowledge and opinions on natural disasters and disaster education of pre-service teachers who survived the 6 February earthquake in Turkey

Human-related events that occur in an unexpected time and affect people’s lives adversely are defined as natural disasters. Today, when we live in the age of technology, several regions are faced with natural disasters such as earthquakes, floods and hurricanes. Not different from various countries in the world, Turkey faces such natural disasters frequently. Especially the earthquake disaster of February 6, 2023, which affected a very broad area, caused many people to suffer. After the earthquake, several problems such as unemployment, need for education and shelter, and psychological traumas, especially among children, emerged. Although preventing natural disasters is not possible, it is a well-known fact that damages can be minimized through disaster education given in schools from an early age. It is of vital importance that Turkey, which is located in an earthquake zone, attaches more importance to disaster education and that students are educated on this subject from an early age, as in countries such as Japan, in order to reduce the disaster damages. Some action has been taken in this area in Turkey especially after the 1999 Marmara earthquake, but the recent major earthquake disaster has shown that more attention should be paid to disaster education. This study was carried out to determine the knowledge and opinions on disaster and disaster education of pre-service teachers who survided the earthquake in Turkey on February 6, 2023. The study group consisted of students studying in different departments of education faculties of universities. The structured interview form developed by the researchers was used as a data collection tool.

Development of the Black–Scholes Model for Determining Insurance Premiums to Mitigate the Risk of Disaster Losses Using the Principles of Mutual Cooperation and Regional Economic Growth

The frequency and economic damage of natural disasters have increased globally over the last two decades due to climate change. This increase has an impact on the disaster insurance field, particularly in the calculation of premiums. Many regions have a shortcoming in employing insurance because the premium is too high compared with their budget allocation. As one of the solutions, the premium calculation can be developed by applying the cross-subsidies mechanism based on economic growth. Therefore, this research aims to develop premium models of natural disaster insurance that uniquely involve two new variables of an insured region: cross-subsidies and the economic growth rate. Another novelty is the development of the Black–Scholes model, considering the two new variables, and it is used to formulate the premium model. Following the modeling process, this study uses the model to estimate the premiums for natural disaster insurance in each province of Indonesia. The estimation results show that all new variables involved in the model novelties significantly affect the premiums. This research can be used by insurance companies to determine the premium of natural disaster insurance, which involves cross-subsidies and economic growth.

Next-generation core competency gaps for disaster risk management and preparedness in UNESCO-designated heritage sites

Heritage plays a critical role in sustainability. The absence of studies examining core competencies among UNESCO actors for disaster risk management (DRM) and preparedness in heritage sites prompted this survey. Respondents from 59 countries revealed a high rating of all listed competencies with significant discrepancies concerning relationship-building requiring attention. Additionally, substantial variations in competencies were linked to factors such as age, job positions, and previous experiences with disaster damages. Holistic DRM proficiency is the primary predictor of disaster preparedness within heritage sites. Thus, enhancing preparedness through experiential learning and coordinated knowledge-sharing mechanisms will preserve our collective heritage for sustainable futures.

Rheological Properties of a Tailing Thickened in an Excavated Ground Channel

Objectives: The recent tailings dam disasters emphasize the need to adopt best management practices focusing on the stability of these structures. This study aims to present the use of a thickening channel as an alternative for ultrafine tailings dewatering in a small iron ore mine in the Quadrilátero Ferrífero. Theoretical Framework: The research is based on the study of rheology, focusing on viscosity and yield stress as key parameters to characterize the behavior of thickened slurry. Method: The study involved the production of thickened slurry in a channel, followed by rheological characterization through sampling at different points in the thickening process. Results and Discussion: The findings indicate that the thickened slurry behaves as a non-Newtonian fluid, with all samples analyzed showing pseudoplastic behavior. There was an increase in viscosity and yield stress with increasing solids content. The deposition of thickened slurry resulted in a 36.9% increase in the volume of the studied reservoirs. Research Implications: This approach offers advantages such as low capital cost, increased water reuse, and improved geotechnical stability of deposition sites, contributing to safer and more sustainable tailings management practices. Originality/Value: The study provides a practical alternative for tailings dewatering, enhancing the safety and sustainability of tailings disposal practices in small iron ore mines.

Systematic Mapping of Global Research on Disaster Damage Estimation for Buildings: A Machine Learning-Aided Study

Systematic Mapping of Global Research on Disaster Damage Estimation for Buildings: A Machine Learning-Aided Study

Are there possible issues that we overlook when selecting green infrastructure?

Promoting green infrastructure (GN) as a tool for reducing natural disaster risk is promising, particularly in depopulated areas worldwide. Images of GN as being multifunctional and environment friendly seem to enhance citizens’ positive attitudes toward it. While conventional types of disaster prevention infrastructure, such as concrete levees, can completely prevent damage, GN can relieve the effects of natural hazards. By switching from conventional infrastructure to GN, societies could reduce the costs of disaster prevention infrastructure. However, the risk of disaster damage may increase in some areas. This study aimed to better understand citizens’ preference for GN. It was hypothesized that those who prefer GN are those who do not take the initiative to learn about it and that some citizens are not fully aware of the heterogeneous risks when selecting GN. To test the hypotheses, structural and measurement models, including latent variables, were developed, and structural equation modeling was performed. Data for constructing the measurement and structural equations were obtained using a web questionnaire administered by a professional research company in 2022 with 1,200 participants across Japan. Data from the portal site for the official statistics of Japan (e-Stat) were also used. The results confirm the hypothesis that individuals who favor GN are those who do not proactively seek to acquire knowledge concerning it. The findings highlight the importance of considering, in future policymaking, the possibility that citizens who prefer GN without knowledge about it may face high risks as a result of its uninformed adoption and use.

Site Selection for Offshore Wind Power Farms with Natural Disaster Risk Assessment: A Case Study of the Waters off Taiwan’s West Coast

This research examines the risk of natural disasters for offshore wind turbines together with their potential wind energy capacity to help the site selection of offshore wind power farms. Through evaluations of expert questionnaires, we use the fuzzy analytic hierarchy process to weight how natural disasters damage the sub-assemblies of an offshore wind turbine, then obtain the natural disaster risk assessment model, and finally utilize ArcGIS Pro 3.2 to map the potential wind farm sites for the waters off Taiwan’s west coast. We identify that typhoons are the most threatening type of disaster to generators, rotor blades, and rotor hubs; earthquakes are the most threatening to towers; and lightning is the most threatening to transformers. For the whole wind turbine, wind is ironically the most threatening natural disaster, followed by lightning, sea waves, and then earthquakes. Lastly, we examine the results by overlapping the offshore wind farms developed and planned in Taiwan, which coincide with locations in relatively low risk and high wind speed areas.

Fast Finance and the Political Economy of Catastrophic Dam Collapse in Lao PDR: The Case of Xe Pian-Xe Namnoy

In the dark of a July night in 2018, a 5-billion-cubic-metre torrent of muddy water crashed through rooftops and ripped through the downstream villages of southeast Lao People's Democratic Republic (Lao PDR). An auxiliary "saddle" dam had collapsed in the US$1.02 billion Xe Pian-Xe Namnoy (XPXN) Hydropower Project that was still under construction and had just reached financial contractual close five years prior, in 2013. In the aftermath of the collapse, official state narratives pointed to extreme weather conditions and "unforeseen" construction and engineering miscalculations, viewing soil conditions as the primary culprit. This paper examines the financial dimensions of dam failure and introduces the term "fast finance": financier-driven timelines that have drastically expedited and shortened the legal, social, and pre-construction processes involved in hydropower dam projects to the detriment of dam safety, due diligence, and local participatory input. Extreme weather and anthropogenic climate change are not sole explanatory factors in the XPXN dam disaster. This paper highlights the also significant role of financial and political interests as contributing factors in dam safety and failure alongside extreme weather. The paper challenges conventional "natural disaster" framing of dam collapse by bringing into focus ex-ante political decision-making, financial engineering, and construction planning prior to dam construction to highlight the ways in which the XPXN catastrophe also had anthropogenic and "unnatural" contributing factors. Fast finance encompasses the role of temporality and the responsibility of state-business actors in ex-ante financial and infrastructure decisions that conclude with catastrophic outcomes. The article examines the re-engineering of contemporary dam finance through a case study of Lao PDR and argues that issues of financial engineering should be examined alongside other forms of civil, mechanical, structural, and hydrological engineering in the analysis of dam disasters. The temporal logics of financial actors—particularly the financialized logic of fast finance—has displaced the public-good-producing logic of patient capital. Financial logics shape and condition other forms of engineering and construction and are central to considerations of dam safety and accountability. Naturalizing discourses around extreme weather and aging dams deflect from the financial decisions and policy action, or inaction, of state-business actors to prevent dam collapse.

Natural disaster damage analysis using lightweight spatial feature aggregated deep learning model

Natural disaster damage analysis using lightweight spatial feature aggregated deep learning model

Spatiotemporal Flood Hazard Map Prediction Using Machine Learning for a Flood Early Warning Case Study: Chiang Mai Province, Thailand

Floods cause disastrous damage to the environment, economy, and humanity. Flood losses can be reduced if adequate management is implemented in the pre-disaster period. Flood hazard maps comprise disaster risk information displayed on geo-location maps and the potential flood events that occur in an area. This paper proposes a spatiotemporal flood hazard map framework to generate a flood hazard map using spatiotemporal data. The framework has three processes: (1) temporal prediction, which uses the LSTM technique to predict water levels and rainfall for the next time; (2) spatial interpolation, which uses the IDW technique to estimate values; and (3) map generation, which uses the CNN technique to predict flood events and generate flood hazard maps. The study area is Chiang Mai Province, Thailand. The generated hazard map covers 20,107 km2. There are 14 water-level telemetry stations and 16 rain gauge stations. The proposed model accurately predicts water level and rainfall, as demonstrated by the evaluation results (RMSE, MAE, and R2). The generated map has a 95.25% mean accuracy and a 97.25% mean F1-score when compared to the actual flood event. The framework enhances the accuracy and responsiveness of flood hazard maps to reduce potential losses before floods occur.