Climate-related Disasters Research Articles

A Systematic Review on Women’s Disaster Adaptation Strategies in Changing Climate

Climate change has posed a serious threat to humanity, particularly to women, who are among the most vulnerable. Adaptation as a measure of disaster mitigation has received a lot of attention in the wake of climate change, but nearly all of it has disregarded women's contribution to disaster adaptation as a change agent. This research aims to review the available literature on women's adaptation methods in the face of climate-related disasters. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) technique was used to guide this research. With a thorough screening method, 19 articles out of 695 were selected utilizing two databases: Scopus and EBSCo discovery service. The findings are presented in a thematic way titled after the various adaption tactics employed by women across the world. The findings suggest that women have demonstrated their ability to use beneficial adaptation techniques in the face of several societal constraints, including reproductive responsibility. As a result of the findings, certain policy recommendations have been made, emphasizing the relevance of women's capacity building in disaster impact mitigation.

An Assessment of the Impact of COVID-19 on the Agri-Food System in Caribbean Small Island Developing States

The COVID-19 pandemic impacts have arguable been more pronounced in the developing world, such as the Small Island States (SIDS) of the Caribbean, where a plethora of geophysical and socio-political factors have led to increased vulnerability, particularly in fragile sectors such as agriculture. The pandemic added another layer of complexity to the unstable agri-food systems of SIDS in the Caribbean. Measures to contain the unfolding crisis have tremendously disrupted food systems by threatening the production, distribution, and marketing of commodities which exposed the frailty of the region's food security. Caribbean SIDS are highly dependent on food imports and relies on international markets to secure food. Many are also dependent on agricultural exports and have a large portion of their population involved in agriculture making them particularly vulnerable to the rigors of the pandemic. Export restrictions on foodstuff and prohibitions due to lockdowns and border closures further exacerbated these challenges. Additionally, food and nutrition security in the region is also subjected to the effects of climate change and climate-related disasters. Dealing with the impacts of co-occurring disasters is, therefore, an ever-present threat. This study examines the impact of COVID-19 on the agri-food supply in the Caribbean. It also identified measures and initiatives adopted to cope with these disruptive consequences. The study involves the use of internet-based surveys and focus group discussions and internet-based surveys with stakeholders and online searches for related literature. A total of 96 farmers, 60 food distributors, 84 food service operators, and 237 consumers from the region participated in the online survey and 4 focus group discussions between January and November 2021. The results confirmed that the impacts of the COVID-19 pandemic were evident along the entire agri-food supply chain and numerous challenges and shocks were identified across all participating groups and countries. Some challenges and shocks such as loss of income and related challenges including lower sales and loss of markets affected all groups in the study but to varying degrees and based on socio-demographic factors. In general people of lower income status and smaller businesses were more susceptible to the negative impacts of the pandemic.

Legal Claims and Compensation in Climate-Related Disasters

Legal Claims and Compensation in Climate-Related Disasters

Open Collaborative Platform for Multi-Drones to Support Search and Rescue Operations

Climate-related natural disasters have affected the lives of thousands of people. Global warming creates warmer and drier conditions which increase the risk of wildfires. In large-scale disasters such as wildfires, search and rescue (SAR) operations become extremely challenging due to low visibility, difficulty to breath, and high temperature from fire and smoke. Unmanned aerial vehicles (UAVs), such as drones, have been used to support such operations. In our previous work, a Krypto module is proposed to “sniff” out wireless signals from mobile phones to locate any possible survivors. With the increased popularity of drones, it is possible to allow people to volunteer in SAR operations with their drones. In this paper, we propose an Open Collaborative Platform for multiple drones to assist SAR operations. The open platform manages different searching drones that carry the Krypto module to collaborate by sharing information and planning search paths/areas. With our Open Collaborative Platform, anyone can participate in SAR operations and contribute to finding possible survivors. The novelty of this work is the openness and collaboration of the platform that “crowdsourcing” the searching operation to a large group of people who share information and contribute to finding possible survivors in a large disaster such as wildfires. Our experimental study shows that the Open Collaborative Platform is effective in reducing both the number of drones required and the search time for finding survivors.

EMPOWERING GEO-BASED AI ALGORITHM TO AID COASTAL FLOOD RISK ANALYSIS: A REVIEW AND FRAMEWORK DEVELOPMENT

Abstract. Climate change and current susceptibilities exacerbated the coastal flood loss and damage resulting in livelihoods and property damage. Urban areas in the Low to Lower-Middle Income Countries are expected to be disproportionately impacted by the disaster, given a higher share of citizens living in the Low Elevation Coastal Zone, limited financial resources, and poorly constructed disaster protection. Documentation of historical coastal floods, population, and property affected, could advance the assessment by considering those parameters in risk analysis. Besides, incorporating such geographic features e.g., mangroves as the ecological solution for alternative coastal flood protection in the prediction is also essential. Mangrove is considered fit for the LLMIC primarily situated in the tropical zone. The prediction utilizing spatial Machine Learning (ML) could aid climate-related disaster risk analysis and contribute to risk reduction and policy suggestions to improve disaster resilience. The research aims to archive recent studies on the application of geospatial science empowering Artificial Intelligence, notably ML in coastal flood risk assessment, so-called GIS-based AI. Another aim is to document population, property, and mangrove distribution across the LLMIC. Artificial Neural Networks were mostly utilized for disaster risk assessment in past research. The number of 58 historical coastal flood events and 908 expected coastal flood hotspots for 2006 to 2021 has been documented. Over 1,2 million Km2 falls under vulnerable areas toward coastal flood in LLMIC under different settlement types where Large City (urban areas) dominates it. Mangrove distribution is mainly distributed across tropical regions mostly distributed along the Southeast Asia coast.

Managing Sustainability and Resilience of the Built Environment in Developing Communities

Sustainable built environment has been the primary focus in academic and industrial fields in recent years. The major forces behind sustainable engineering are the rise in climate-related disasters, constant challenges in the energy sector, and a substantial shift in consumers’ consciousness toward conserving natural resources. Further, many professional bodies have developed guidelines and specifications to implement sustainable practices and rate their impacts. Regardless, promoting analytical procedures for creating a context-sensitive design requires professionals to become familiar with standard sustainable practices and feel comfortable implementing more innovative materials and techniques in civil engineering design. In addition, the socio-political environment and macro-economic culture interact with engineering decisions. Hence, these considerations are necessary to deploy these elements in developing communities through best management practices during the lifecycle of sustainable and resilient projects. This paper endeavors to review these practices using lessons learned from applied examples and existing literature. Discussions cover various aspects of project development, from planning to demolition. Recommendations address challenges and opportunities in the sustainable development of resilient built infrastructure in developing regions.

Machine Learning in Disaster Management: Recent Developments in Methods and Applications

Recent years include the world’s hottest year, while they have been marked mainly, besides the COVID-19 pandemic, by climate-related disasters, based on data collected by the Emergency Events Database (EM-DAT). Besides the human losses, disasters cause significant and often catastrophic socioeconomic impacts, including economic losses. Recent developments in artificial intelligence (AI) and especially in machine learning (ML) and deep learning (DL) have been used to better cope with the severe and often catastrophic impacts of disasters. This paper aims to provide an overview of the research studies, presented since 2017, focusing on ML and DL developed methods for disaster management. In particular, focus has been given on studies in the areas of disaster and hazard prediction, risk and vulnerability assessment, disaster detection, early warning systems, disaster monitoring, damage assessment and post-disaster response as well as cases studies. Furthermore, some recently developed ML and DL applications for disaster management have been analyzed. A discussion of the findings is provided as well as directions for further research.

Temperature targets, deep uncertainty and extreme events in the design of optimal climate policy

We study optimal climate policy consistent with the constraint that average global temperature remains below 1.5 ∘ C relative to pre-industrial levels. We consider a holistic representation of uncertainty including traditional risk, deep uncertainty and stochastic arrivals of climate-related disasters. Using robust control methods, we derive optimal emission and carbon tax paths and calculate when temperature exceeds the target in the absence of the constraint. We show that policy under deep uncertainty requires strong action now relative to pure risk but the policy stringency is reversed later. Preliminary estimates suggest that the COVID-19 impact on attainment of the temperature target is negligible.

A Social Insurance Perspective on Pandemic Fiscal Policy: Implications for Unemployment Insurance and Hazard Pay

This paper considers fiscal policy during the pandemic through the lens of optimal social insurance. We develop a simple framework to analyze how government taxes and transfers could mimic the insurance that people would like to have had against pandemic income losses. Permutations of the framework provide insight into how unemployment insurance should be structured, when and how much hazard pay is called for, and whether fiscal policy should aim just to redistribute income or also to stimulate aggregate demand during a pandemic. When we use the insights from the model to evaluate unemployment insurance measures taken during the pandemic, we find that some, but far from all, of the implications of the social insurance framework were followed. In the case of hazard pay, we find that the proposal for a national program (the never-implemented HEROES Act) was both broader and more generous than a social insurance perspective would call for. We suggest that the social insurance perspective on fiscal policy is likely to become increasingly relevant as pandemics and climate-related natural disasters become more common causes of unemployment and recessions.

Prenatal Exposure to a Climate-Related Disaster Results in Changes of the Placental Transcriptome and Infant Temperament.

Maternal stress during pregnancy exerts long-term effects on the mental well-being of the offspring. However, the long-term effect of prenatal exposure on the offspring’s mental status is only partially understood. The placenta plays a vital role in connecting the maternal side to the fetus, thereby serving as an important interface between maternal exposure and fetal development. Here, we profiled the placental transcriptome of women who were pregnant during a hurricane (Superstorm Sandy), which struck New York City in 2012. The offspring were followed longitudinally and their temperament was assessed during the first 6–12 months of age. The data identified a significant correlation between a Superstorm Sandy stress factor score and infant temperament. Further, analysis of the placental transcriptomes identified an enrichment of functional pathways related to inflammation, extracellular matrix integrity and sensory perception in the specimen from those infants with “Slow-to-Warm-up” temperament during the first year of life. Together, these findings provide initial evidence that maternal exposure to climate-related disasters results in altered placental transcriptome, which may be related to long-term emotional and behavioral consequences in children.

Effects of changing climate variables on residential building fabrics in North Central Nigeria

Climate change has become a global concern and its impact has continued to affect human lives, influencing the livelihood of most people across the globe and the concern is based on increasing records, incidents and impacts of climate related disasters on physical infrastructures. This study evaluated the effects of changing climate variables on residential buildings fabrics in North Central, Nigeria. Data on climate pattern for the last thirty years were collected from the Nigerian Meteorological Agency (NIMET), National Space Research and Development Agency (NASRDA) and Data Interim (DIT), and were analysed using trend analysis. The Mohr’s test kit was utilised to establish the extent of the climate defects on residential building fabrics within the study area using severity index calculation. The study revealed constant fluctuations in climate variables within the study area with Nasarawa and Kogi States recording peaks in solar intensity and rainfall readings. Also, most of the buildings investigated experienced effects of climate in one way or the other showing defects such as flaking of mortar, biological growths, blistering and peeling of paints. Based on the results obtained from the study, recommendations include provision of moisture barriers, surface water drains around buildings, use of fibre materials, use of bright colours for finishing’s and introduction of larger sized windows around residential buildings.

Study on Numerical Model and Dynamic Response of Ring Net in Flexible Rockfall Barriers

Developing reliable, sustainable and resilient infrastructure of high quality and improving the ability of countries to resist and adapt to climate-related disasters and natural disasters have been endorsed by the Inter-Agency Expert Group on Sustainable Development Goals (IAEG-SDGs) as key indicators for monitoring SDGs. Landslides pose a serious threat to vehicle traffic and infrastructure in mountain areas all over the world, so it is urgent and necessary to prevent and control them. However, the traditional rigid protective structure is not conducive to the long-term prevention and control of landslide disasters because of its poor impact resistance, high material consumption and difficult maintenance in the later period. Therefore, this study is aimed at the flexible rockfall barriers with good corrosion resistance, material saving and strong cushioning performance, and proposes a fine numerical model of a ring net. This model is used to simulate the existing experiments, and the simulation results are in good agreement with the experimental data. In addition, the numerical model is also used to study the influence of boundary conditions, rockfall gravity and rockfall impact angle on the energy consumption of the ring net. It is indicated that the fixed constraint of four corners increases the deformability, flexibility and energy dissipation ability of the ring net. Apart from that, the influence of gravity on the energy dissipation of the overall protective structure should not be neglected during the numerical simulation analysis when the diameter of rockfall is large enough. As the impact angle rises, the impact energy of the rockfall on the ring net will experience a gradual decline, and the ring at the lower support ropes will be broken. When the numerical model proposed in this study is used to simulate the dynamic response of flexible rockfall barriers, it can increase the accuracy of data and make the research results more credible. Meanwhile, flexible rockfall barriers are the most popular infrastructure for landslide prevention and control at present, which improves the ability of countries to resist natural disasters to some extent. Therefore, the research results provide technical support for the better development and application of flexible rockfall barriers in landslide disasters prevention and control, and also provide an important and optional reference for evaluating sustainable development goals (SDGs) globally and regionally according to specific application goals.

The stress before the storm: Psychological correlates of hurricane-related evacuation stressors on mothers and children.

Natural disasters, such as hurricanes, can contribute to the development of posttraumatic stress symptoms (PTSS), anxiety, and depression. Furthermore, mothers and children are especially vulnerable postdisasters. Despite the rise in the frequency of climate-related disasters and also the threat of disasters (e.g., storms that threaten but do not make landfall), little is known about how predisaster experiences are associated with mothers' and children's postdisaster psychological functioning. This study examined evacuation-related stressors as predictors of mothers' and youths' psychological functioning 3 months after Hurricane Irma. Mothers (N = 535; 33% ethnic/racial minorities) from South Florida counties most affected by Hurricane Irma completed an online survey that assessed evacuation-related stressors (both pre- and posthurricane), hurricane exposure (i.e., life threat, loss/disruption), and posthurricane social support and mental health symptomatology (i.e., PTSS, anxiety, depression). Mothers of children aged 7-17 years (n = 226) also reported on their child's psychological functioning. Using a risk and resilience model, evacuation stressors significantly predicted mothers' and youths' PTSS and symptoms of anxiety and depression, even after accounting for demographic factors, hurricane exposure, and availability of social support. Mothers of older children also reported significantly higher levels of PTSS, anxiety, and depression than mothers who only had young children (aged 6 or younger) at home. Evacuation experiences represent significant stressors that may put mothers and children at risk for PTSS and psychological distress. Resilience-building efforts should include efforts to better prepare families for prestorm evacuations, thereby reducing risk in mothers and youth and ultimately contributing to better psychosocial functioning. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Challenges of Data Availability and Use in Conducting Health-EDRM Research in a Post-COVID-19 World.

Disasters disrupt communication channels, infrastructure, and overburden health systems. This creates unique challenges to the functionality of surveillance tools, data collection systems, and information sharing platforms. The WHO Health Emergency and Disaster Risk Management (Health-EDRM) framework highlights the need for appropriate data collection, data interpretation, and data use from individual, community, and global levels. The COVID-19 crisis has evolved the way hazards and risks are viewed. No longer as a linear event but as a protracted hazard, with cascading and compound risks that affect communities facing complex risks such as climate-related disasters or urban growth. The large-scale disruptions of COVID-19 show that disaster data must evolve beyond mortality and frequency of events, in order to encompass the impact on the livelihood of communities, differentiated between population groups. This includes relative economic losses and psychosocial damage. COVID-19 has created a global opportunity to review how the scientific community classifies data, and how comparable indicators are selected to inform evidence-based resilience building and emergency preparedness. A shift into microlevel data, and regional-level information sharing is necessary to tailor community-level interventions for risk mitigation and disaster preparedness. Real-time data sharing, open governance, cross-organisational, and inter-platform collaboration are necessary not just in Health-EDRM and control of biological hazards, but for all natural hazards and man-made disasters.

Flood Risk Perception and Its Attributes among Rural Households under Developing Country Conditions: The Case of Pakistan

Managing and communicating flood risks necessitates a strong understanding of how people perceive risk. It has become critical to examine risk perception to implement effective disaster risk management (DRM) measures. Socioeconomic determinants have an impact on risk perception, which in turn affects future adaptive capacity and disaster preparedness. First and foremost, this research attempts to determine how Pakistani people in rural areas perceive flood risk, and second, to examine the factors that can influence rural residents’ perceptions of flood risk. The data for this study were collected through face-to-face interviews with 600 respondents (household heads) from Charsadda and Nowshera districts that were severely affected by the 2010 flood. A flood risk perception index was developed (using a risk matrix) using relevant attributes on a Likert scale and classified into two categories: high and low perceived risk. Furthermore, a binary regression model was used to examine the influence of socioeconomic and institutional factors on rural households’ risk perception. Flood risk was perceived by 67 percent of the total sampled participants in the study regions. The results of binary logistic regression demonstrate that flood risk perception is strongly linked to socioeconomic variables such as age, education, house ownership, family size, past flood experience, and distance from the nearest river source, as well as institutional factors such as access to credit and extreme weather forecast information. The findings of the current study additionally revealed that flood risk perception varied among household heads based on education (1–10 years perceived high flood risk (51.47%)), age (age greater than 40 years perceived high flood risk (52.83%)), and monthly income levels (lower monthly income group perceived high flood risk (73.02%)). The findings of this study shed light on rural households’ perception of flood risk and the factors that shape such perceptions. These findings can assist provincial and local disaster management authorities in better understanding flood risk and adopting local actions that could be used to respond to flood and other climate-related disasters.

Social vulnerability of coastal fish farming community to tidal (Rob) flooding: a case study from Indramayu, Indonesia

Climate-related disasters increasingly threaten over one-third of the global population, specifical communities within 100 km of coastal zones. Indonesia, the world’s largest archipelago with the second-longest coastline, faces tidal (Rob) flooding from high tides, land subsidence, and sea-level rise. This study assess fish farmers’ vulnerability to Rob flooding in Java’s Indramayu District. Our Social Vulnerability Index (SoVI)’s development involved 150 questionnaires, focus group discussion, and key-informant interviews between 16 and 20 October 2019. It found a high vulnerability, a SoVI score of + 1.76 comprising nine principal components (PCs): external support and government mitigation, local knowledge, income, expenditure, family size, seasonal-expenditure, education, experience, and ethnicity. Contributing to ‘vulnerability’ and ‘resilience’ concepts, it highlights community memory of repeated disasters and its impact on local adaptive capacity. Findings inform policymakers to address the PCs influencing vulnerability, including critically-needed livelihood support and early-warning systems relevant to the country’s 12,000 + coastal-villages and developing countries where over 90% of fishermen live.

Шилийн Богд орчмын хээрийн түймрийн шаталтын зэрэглэлийг тооцоолох болон нөхөн сэргэх үйл явцын мониторинг судалгаа

Due to the increase in global climate change and related natural disasters, satellite observation and mapping technology have made it possible to monitor, predict, evaluate, and detect the environment, which is a clear indication of the importance of remote sensing. The main purpose of this study is to monitor the occurrence of fire disasters as a result of Sentinel-2 satellite imaging technology, to determine the burned area with its classification and the recovery process. The study area was sampled in the southeastern part of Mongolia, near the Shiliin Bogd mountain at the natural steppe zone. In terms of research methodology, the normalized burn ratio (NBR) index was used to map the area of ​​the fire site and the classification of the burned area into 5 categories: unburned, low, low-medium, high-medium, and high, which are process-defined work. As a result of the estimation, the burned area was mapped from the satellite images and the total burned area was 1164.27 km2, of which 757.34 km2 (65 percent) was weak, 404.57 km2 (34.7 percent) was low-medium and the remaining 2.36 km2 (0.3 percent) was high-medium. Finally, we believe that this research is important for emergency workers, researchers, and environmental specialists.

A Scoping Review of Climate Change, Climate-Related Disasters, and Mental Disorders among Children in Low- and Middle-Income Countries.

Children, particularly those living in low- and middle-income countries (LMICs), are highly vulnerable to climate change and its impacts. Our main objective was to conduct a scoping literature review to determine how exposure to climate change and climate-related disasters influences the presence of mental disorders among children in LMICs. We also aimed to identify gaps in this area of scholarship. We included studies of children in LMICs that had a climate change or climate-related disaster exposure and mental disorder outcome. Twenty-three studies were included in the final synthesis. Fourteen studies were conducted in China, three in India, two each in Pakistan and the Philippines, and one each in Namibia and Dominica. All studies assessed the association between a climate-related disaster exposure and a mental disorder outcome, while none explored broader climate change-related exposures. Post-traumatic stress disorder (n = 21 studies) and depression (n = 8 studies) were the most common mental disorder outcomes. There was considerable between-study heterogeneity in terms of sample size, follow-up length, and outcome measurement. Overall, the literature in this area was sparse. Additional high-quality research is required to better understand the impacts of climate-related disasters and climate change on mental disorders within this population to ultimately inform future policies and interventions.

Climate-related disasters and agricultural land conversion: towards prevention policies

ABSTRACT Climate-related disasters (CRDs) and hazards such as droughts, floods, and storms are the main patterns of natural events in long-term weather cycles which are potentially affected by climate change. Unsustainable use of land has contributed to the increase of vulnerability to disasters. Disasters and land use change have become major concerns all over the world. Agricultural land conversion (ALC) has been identified as one of the most significant drivers that influences ecosystems, and poses numerous challenges to agricultural development and human life. This systematic review study aimed to review the drivers and effects of ALC and CRDs on the one hand and their relations on the other. The paper further proposes a prevention policy framework towards the management of ALC and CRDs including three dimensions, i.e. monitoring-based policies, driver-based policies, and effect-based policies. All three types of these policies are important and essential because ALC and CRDs and their effects and drivers are interdependent. The study concludes that managing these phenomena not only needs to control and monitor their drivers but also requires preventing the effects. Avoiding the drivers and effects also involves monitoring the past, present, and future of ALC and CRD trends.

Lesson learned and enhanced adaptation strategies for isolated indigenous community in West Papua

Isolated indigenous communities are groups of people who live their lives very apprehensively. Most of the people live in places that are difficult to reach geographically, such as inland, beaches, forests, hills and remote islands (outer, inland, and left behind). Remoteness is the biggest contributing factor to their inability to be part of the development process and coupled with climate-related disasters. Descriptive methods with in-depth interviews and Focus Group Discussion (FGD) are used to explore local knowledge in efforts to adapt to climate change and the introduction of adaptation strategies, especially related to enhance local knowledge (SASI).