Disaster Trends Research Articles

The state of disaster and resilience literature in British Columbia, Canada. A systematic scoping review

British Columbia (BC), Canada is exposed to diverse natural hazards, leading to extensive research into disaster and resilience topics in the province. However, within disaster studies there is commonly siloing of research and knowledge between different fields, hindering integrated risk reduction solutions. This review aims to summarize the current state of disaster and resilience research in BC to provide context for future innovative research and response efforts. A systematic scoping review was used to balance the need for quantitative and qualitative analysis. 24 databases were systematically searched, and additional records were added from a Google Scholar scan and recommendations from disaster researchers. In total 4403 records were screened, of which 343 documents were analyzed. 87% of documents named a natural hazard type/s as the primary subject matter, while 13% discussed disaster and resilience more generally. Earthquakes were the most frequently discussed hazard, while storm/weather and drought were the least. STEM disciplines published the most on the reviewed themes (73% of documents). A spatial disjuncture was found between locations discussed in the literature versus historic BC disaster trends. Overall, there were several hazards, scales and disciplines that were underrepresented. Furthermore, there was a trend towards application of methods and findings primarily to inform global conversations, missing opportunities to provide local or regional recommendations, or deeper acknowledgements of cultural and historical contexts. This review highlights strengths and gaps in the current disaster and resilience publications in BC and adds to the growing literature on the importance of interdisciplinary and place-based disaster research.

Global trend and epidemiological profiles of climate-related disasters from 2000 to 2021.

The objective of this study is to analyse the epidemiological profile of global climate-related disasters in terms of morbidity and mortality, as well as to examine their temporal trends. This cross-sectional study analysed climate-related global disasters from 2000 to 2021, utilising definitions and criteria from the United Nations Strategy for Disaster Reduction and the Centre for Research on the Epidemiology of Disasters. Data were sourced from the EM-DAT database. The study assessed trends over the entire period and compared them with previous years (1978-2000). A total of 7398 climate-related disasters were recorded, with hydrological disasters being the most frequent, followed by meteorological and climatological disasters. Statistically significant differences were noted in the average rates of affected individuals and injuries per million inhabitants. No significant trends were found in mortality rates, but the frequency trends for the entire period (1978-2021) and the subperiod (1978-2000) were increasing and statistically significant. However, the trend from 2000 onwards showed a non-significant decrease, potentially reflecting better disaster preparedness and response strategies under the Hyogo and Sendai Framework. The study highlights hydrological disasters as the most frequent and deadliest climate-related events, with climatological disasters affecting and injuring the most people. The lack of standardised criteria for disaster inclusion in databases presents a significant challenge in comparing results and analysing trends. Establishing uniform inclusion criteria is crucial for effective data analysis and disaster management.

Typhoon disaster emergency forecasting method based on big data.

Typhoons are natural disasters characterized by their high frequency of occurrence and significant impact, often leading to secondary disasters. In this study, we propose a prediction model for the trend of typhoon disasters. Utilizing neural networks, we calculate the forgetting gate, update gate, and output gate to forecast typhoon intensity, position, and disaster trends. By employing the concept of big data, we collected typhoon data using Python technology and verified the model's performance. Overall, the model exhibited a good fit, particularly for strong tropical storms. However, improvements are needed to enhance the forecasting accuracy for tropical depressions, typhoons, and strong typhoons. The model demonstrated a small average error in predicting the latitude and longitude of the typhoon's center position, and the predicted path closely aligned with the actual trajectory.

Analysis and Evaluation of Trends in Natural Disasters

Analysis and Evaluation of Trends in Natural Disasters

Analysis and Evaluation of Trends in Natural Disasters

Analysis and Evaluation of Trends in Natural Disasters

Spatiotemporal changes of climatic disasters and population displacements in Africa

ABSTRACT Frequent global climatic disasters are posing a growing threat, especially in populous Africa. Understanding the intrinsic interactions between climatic disaster and the resulting affected population in Africa can provide a representative sample of developing countries for global governance of climate change. This study explored the spatiotemporal dynamics in climatic disasters and disaster-related displacements in Africa from a geographical perspective. The results showed that climatic disasters in Africa occurred with seasonality consistent with African climate characterized by distinct dry and rainy seasons, manifested as flood, storm, and heat wave events occurring in the rainy season, wildfire and cold wave events taking place in the dry season, and prolonged droughts spanning both dry and rainy seasons. Meanwhile, the spatial pattern and variation trend of climatic disasters and displacements varied greatly by the five African sub-regions. East Africa experienced the highest number of disasters and displacements, while Southern Africa bore the least. Flood and drought triggered a third of total displacements in the most populated West Africa. The least frequent disasters dominated by flood only affected less than 10.9% of the total in Central Africa. 6.8% of the total displacements were primarily induced by coastal flood in North Africa.

Upaya Pengelolaan Lingkungan Akibat Bencana Banjir di Kecamatan Empang, Kabupaten Sumbawa

Indonesia is a country that is prone to natural disasters from a geological perspective. Based on information from the Head of the Information Data Center and Public Relations of the National Disaster Management Agency, natural disaster trends have increased by 350% in the last three decades. A significant increase is hydrometeorological disasters which are influenced by weather aspects, such as floods, landslides, tornadoes, and droughts. Sumbawa Regency is one of the areas in Indonesia that is being hit by an increasing trend of natural disasters. The most recent natural disaster that hit one of the Sumbawa Regency areas was the flood disaster in Empang District. The cause of flooding itself can occur due to various things both natural and human. Floods can be caused by natural events such as rainfall over a long period of time, soil flooding leaving only rocks, and no water absorption. Therefore it is essential to analyze the flood disaster that occurred in Empang District so that a good environmental management strategy can be carried out. The management carried out is to restore environmental functions that have been lost due to damage caused by the disaster. Installing drainage and implementing the Internet of Things in overcoming flooding is considered to be quite effective. The relocation and reclamation activities of corn plantation areas carried out by bioremediation and revegetation processes can improve land conditions.

Hydrometeorological Disaster: Challenges and Mitigation in Indonesia

Climate change, which includes increasing global temperatures, irregular rainfall patterns, and extreme changes in weather, has resulted in detrimental consequences for society and the economy, especially concerning an increase in hydrometeorological disasters. Indonesia is prone to natural disasters, primarily related to hydrometeorological events such as floods, landslides, and droughts. Hydrometeorological disasters can cause enormous economic and social losses; therefore, it is vital to holistically address climate change's social and economic impacts. This study aims to analyse trends in hydrometeorological disasters, especially in disaster-prone areas, so that the affected areas know comprehensive mitigation efforts to overcome them. The research methodology uses qualitative methods with descriptive analysis of hydrometeorological disasters in West Java and DKI Jakarta. The study results show that the trend of hydrometeorological disasters in West Java and DKI Jakarta Provinces tends to increase yearly. Several factors, including climate change, uncontrolled development, increasing population, topography and geographical location, and land subsidence, cause the latest disasters. The Indonesian government is actively trying to mitigate the risk of hydrometeorological disasters but is still experiencing some challenges, including topography and geographic location, climate change, limited resources, and low public awareness. Pentahelix collaboration and comprehensive public education are ways of overcoming these disasters. The Pentahelix collaboration allows for synergy between government, industry, and academia in identifying risks, formulating policies, and implementing mitigation programs.

Forecasting and assessment of efficiency and reliability of construction systems during emergency response

The aim of the work involves the improvement of management processes during the life cycle of major construction objects, focused on enhancing the efficiency and reliability of construction systems in emergency situations with limited availability of resources. The relevance of the study is stipulated by the increasing trend in natural and man-made disasters on the territory of the Russian Federation, including floods. Registered emergencies associated with floods indicate that it is necessary to optimize the construction management processes through adequate and timely resource allocation in order to prevent and mitigate the consequences of such emergencies, which can be achieved by using the target-focused principles for construction management. The paper systematizes the challenges in construction management and identifies trends, specific features, and regularities of the organization of construction processes in emergency response. Based on this analysis, the recommendations are offered for improving construction processes using the target-focused principles in emergency response and ensuring the fail-safety of buildings exposed to flood waters.

Community power outage prediction modeling for the Eastern United States

In the United States, weather-related power outages cost the economy tens of billions annually, and there has been an upward trend in billion-dollar disasters over the last two decades. Thus, it is of growing importance to be able to predict outages and understand local resilience. However, many outage prediction models rely on utility infrastructure and outage data, which can be difficult to obtain when a study domain covers many utility territories. This study demonstrates two gradient-boosting machine-learning models driven by utility-agnostic non-proprietary data, eliminating the need for utility-specific data, and allowing individuals or communities to build and use such models for emergency planning or vulnerability analysis. Further, the framework is novel for its ability to incorporate data from various ecoregions, utilize infrastructure proxy data, and provide outage predictions for a breadth of storm types over a large and scalable domain. In this study, vegetation, land cover, energy infrastructure proxy, and weather data are used as model inputs to evaluate 15,872 events across 17 states in the Eastern U.S., where an event is defined as a unique combination of geographic county and storm episode ID. The model predicting all storm types except thunderstorms was validated using 10-fold cross-validation where folds were split chronologically, and demonstrates an r-squared value between predicted and actual outages of 0.61. Similarly, the thunderstorm-only model demonstrates an r-squared of 0.31. For future work, the addition of flooding data may be considered as the r-squared for the various-storm-type model increases to 0.77 when data from New York and New Jersey for Hurricane Sandy are removed. Additionally, the framework demonstrated here can be used to create a real-time outage prediction forecasting tool for storm events, and can be used to analyze resilience at a county resolution under future climate scenarios.

The record and trends of natural disasters caused by gullies in Brazil

Ravines and gullies are advanced stages of linear erosion that occur in many countries, causing economic, social, and environmental impacts. This research aims at analyzing the official record of disasters caused by ravines and gullies in Brazil, with a focus on analyzing the economic impacts. The Brazilian Civil Defense Integrated Information System (S2ID) database was applied in the analysis, combined with a bibliographic review made in the Scopus database. The results obtained from the civil defense database show a growing trend in the number of disasters related to ravines and gullies in the last decade (2011–2020), with 76 cases recorded between January 2013 and May 2019. From these 76 cases, 24 of them were further analyzed to provide information about the socioeconomic impacts. In total, an estimated loss of US$ 54 million was recorded in the considered period. The greatest economic impacts were related to damage to public infrastructure, such as sanitary and sewage water system, buildings and, especially, residential areas in urban perimeters. The spatial distribution of disasters related to linear erosion in Brazil suggests a connection between the development of ravines and gullies and the agricultural frontier of the country, especially in the North and Midwest regions, including the biomes of Cerrado (Brazilian Savanna) and Amazon Rainforest, where the greatest changes in land use occurred between the end of the twentieth and the beginning of the twenty-first century. Although the S2ID is an important data base for analyzing the impacts caused by ravines and gullies, the results suggest that the system's records do not account for medium- and long-term impacts.

Disaster Policy Strengthening in Indonesia: Case of Batu City

The article addresses the pioneer of policy transformation in emergency management system at sub national government of Indonesia by comparing two situation from previous starting condition and after the disaster flash flood. The Kota Batu Flash Flood in November 2021 helped to uncover problems with the Indonesia emergency management system. This study also analyses the importance of decentralized commitment and its relation of implementing cluster collaboration during emergency response. The paper also supported with a tool of geospatial aspect in disaster events of Indonesia to provide better understanding and trend of disaster, combined with the strength’s empirical practice of Kota Batu will upscale the benchmark on the cluster based implementation of disaster emergency management for national level policy in Indonesia. Policy learning and administrative reforms, including changes in the local disaster response organizations and practices in the Kota Batu Flash flood were highlighted. Our findings pointed out that we can collaborate with multiple helix in cluster emergency management system by investing goodwill of enabling policy and community awareness, collaborative model of management in decentralized context, facilitating leadership, and Institutional design relates to procedures and inclusiveness. These findings highlight the importance of focusing efforts on addressing cluster collaboration in disaster emergency management both on 1. National scale disaster by activating post command of emergency disaster management and cluster coordination and 2. Province/Municipal disaster by activating post command assistance as platform cluster.

Transportation Disaster Trends and Impacts in Western Asia: A Comprehensive Analysis from 2003 to 2023

This research undertakes a focused analysis of transportation disasters in Western Asia from 2003 to 2023. Utilizing a curated dataset from the EM-DAT database, we delve into the patterns and outcomes of these significant events, categorizing by modality such as air, rail, road, and water. The results highlight a concerning surge in mishaps between 2003 and 2010, followed by a welcome decline. Road-related incidents emerge as a dominant category, but a large portion (73.8%) remains ambiguously categorized as “Unknown”, underscoring potential data gaps or reporting inconsistencies. Turkey stands out, accounting for nearly 45% of all documented incidents, emphasizing its central role in the regional transportation disaster landscape. Advanced ANOVA analyses illustrate variations in fatality rates across years and countries, although differences in injury rates across disaster types did not exhibit statistical significance. The study underscores the importance of continuous safety enhancements, public awareness efforts, and regional cooperation. Ultimately, it underscores the pressing need for strengthened safety frameworks and the value of inter-regional collaboration to uplift transportation safety standards in Western Asia.

Indicators of community disaster fatigue: A case study in the New South Wales Blue Mountains

A succession of disasters affecting eastern Australia left communities, regions, and states with physical, mental, and resource exhaustion during 2019–2022. Fire, pandemic, and flood occurred in successive waves, hampering recovery efforts. We propose the phenomenon of community disaster fatigue to explain the failure of a community to recover, effectively function, and move forward following a series of disasters. To investigate indicators of community disaster fatigue, we undertook a case study in the Blue Mountains of New South Wales (NSW) and interviewed community leaders. The interviews were thematically analysed and then categorised through the application of the three overarching domains previously used to define community disaster fatigue: (A) defeatism, deterioration, and a lack of planning, (B) weakening health and wellbeing, and (C) corrosion of economic entrepreneurialism and decline in social capital. The results explain how disaster fatigue manifests in a diverse group of community leaders and the issues arising for their careers, volunteer workers, and communities. A major finding is that community disaster fatigue appears to be associated, on a collective level, with elements reflecting the breakdown of community resilience. Thus, as a contribution to practice, a theory of community disaster fatigue can also be useful in developing a strategy for building community resilience. Furthermore, the lack of surge funding, disengagement as a means of self-protection, and closure of local businesses, put the viability of the community at risk. Recent events indicate that closely occurring disasters should be factored into emergency planning, which is a realistic approach given the current trend of recurrent disasters in Australia.

Evidence-based disaster risk assessment in Southeast Asian countries

This paper aims to provide an overview of the risks and trends of natural disasters in Southeast Asian countries and discuss necessary future countermeasures. Quantitative analysis of natural disasters was performed using data collected from EM-DAT. The disaster risk assessment for countries and disaster types was conducted using a frequency-impact risk matrix and risk ranking identification, which is a novel approach based on actual disaster data. The findings suggest that Indonesia, the Philippines, and Thailand face the highest mortality, affected population, and economic damage risks, respectively. Moreover, the study reveals that Southeast Asian countries are vulnerable to climate-related disasters. This risk assessment gives us a comprehensive understanding of natural disaster risks in Southeast Asian countries, enabling us to identify the most vulnerable countries in the region and determine the most significant disaster-type countermeasures for each country.

Development of convenient flood risk assessment method to community level: the case in the Deduru Oya basin in Sri Lanka

Purpose Floods have been identified as the most frequent and threatening disaster in Sri Lanka amidst an increasing trend of natural and man-made disasters in the world. Subject experts state that disaster risk management should be based on the results of risk assessments, but flood risk management in Sri Lanka is seemingly not based on community-level flood risk assessments. Accordingly, the purpose of this paper is to introduce a community-level flood risk assessment method to the local context of Sri Lanka. Design/methodology/approach The sample (n = 425) for the study was selected using the stratified random sampling method, and the Deduru Oya basin was selected as the study area. The risk assessment model introduced by Bollin et al. (2003) was used for the current study, but with some modifications. Accordingly, 16 variables were selected for the risk assessment. Descriptive data analysis methods were used in the study. Findings Community-level flood risk assessment method was introduced. Variable index, flood risk index and flood risk map were developed for the study area. The Grama Niladari Divisions (GNDs) were grouped into five categories from very high risk to very low risk. The GNDs named Wirakumandaluwa, Thimbilla, Deduru Oya, Bangadeniya and Elivitiya were ranked as the most flood-risk GNDs, respectively. Originality/value This paper produces a flood risk assessment method for the local context. Flood risk in the study area was assessed based on people’s perceptions. Accordingly, the flood risk index and flood risk map for the study area were developed based on the empirical data. GNDs were ranked based on the flood risk index.

Experience in handling the 2009 earthquake in Padang City and the role of The Regional Disaster Management Agency in disaster management

The city of Padang is beautiful, but has many potential disasters such as floods, landslides, tornadoes, storms, coastal erosion, earthquakes, and tsunamis. Based on disaster trend data, floods have been the most frequent disaster in the last 15 years, but the disaster that greatly impacted the city of Padang was the earthquake on September 30, 2009, which resulted in 383 deaths. After the 2009 earthquake, the Government of Padang City continuously made efforts to reduce disaster risk with the Padang City Regional Disaster Management Agency as the leading sector. Various mitigation and preparedness efforts have been carried out to minimize risk, especially for the potential for an earthquake that can trigger a tsunami on the Mentawai Megathrust fault.

기후변화 대응을 위한 디지털 물 관리 기술의 적용

As abnormal climates occur frequently around the world, the frequency and intensity of natural disasters are increased. In this study, trends of natural disasters are analyzed and identified the applied technology of smart water grid and digital water management, which are the latest water management systems to respond to climate change. Water-related damages such as typhoons and floods accounted for a large proportion of natural disasters around the world. In the case of Asia, it was found that over the past 50 years, typhoons caused the largest casualties of human life, and the biggest economic loss was caused by floods. In the case of Korea, the biggest economic loss over the past 10 years was disasters caused by floods and typhoons. In order to minimize the damage caused by these disasters, digital water resource technology is being applied worldwide. In this study, application cases of smart water management and digital technologies were investigated. In addition, the application direction of digital water management technology was proposed.

Identification and Prediction of Thermodynamic Disasters During Deep Coal Mining

Researching the methods to identify and predict thermodynamic disasters during deep coal mining is a very important work for the design of mine emergency systems and the decision-making of mine rescue and personnel evacuation, however, existing studies only built static models without evaluating or predicting the development trend of thermodynamic disasters, the research on dynamic modeling methods and rescue decision-making is insufficient, and they generally ignored the mechanism of mutual conversion between fire and gas explosion in deep coal mines. Thus, this paper aims to study the identification and prediction of thermodynamic disasters during deep coal mining. At first, the method for analyzing the thermal field in deep coal mining areas is introduced in detail, and the finite element thermal analysis method is adopted to study the thermodynamic disasters during deep coal mining; then, this paper establishes a thermodynamic disaster prediction model based on the improved Kernel-based Extreme Learning Machine (KELM), and introduces the improved Crow Search Algorithm (CSA) to solve the instability of prediction results caused by artificial selection of model parameters. At last, this paper uses experimental results to verify the validity of the proposed model.

500-Year Records Demonstrating a Sharp Increase in Intensities of Three Natural Hazards at Multiple Spatiotemporal Scales in China

China has experienced frequent natural disasters, including droughts, floods, and heavy snowfall. This study discusses the temporal-spatial patterns in the country since 1500. The intensity of drought in Henan and Inner Mongolia was higher than that in Guizhou and Qinghai, while little difference in flood intensity was observed among these provinces. The intensity of snow disasters in Qinghai was much higher. Except for the slightly decreasing drought trend in Henan, the three natural disasters showed a significant increase over time. Drought disasters in Guizhou, Henan, and Qinghai showed few seasonal differences, whereas those in Inner Mongolia mostly occurred in winter and spring. Floods were concentrated during the summer, while snow disasters occurred mainly during winter and spring. According to the Mann–Kendall (M–K) test, the seasonal differences in disaster trends in Guizhou, Henan, and Qinghai were unclear and similar to the overall trend. However, the disaster trends in Inner Mongolia showed seasonal differences. The spatial distribution of natural disasters in Guizhou and Henan were similar, and their changing trends were extremely scattered, while in Inner Mongolia and Qinghai, they were clustered. The spatial distribution of disaster intensity had few seasonal differences and was similar to the overall distribution. However, when considering the spatial distribution of disaster trends by season, seasonal differences were evident. This study has provided an earlier signal on how to prevent and mitigate natural disasters based on 500 years' tempo-spatial pattern, and the measures on how to improve the management practices of natural hazards under climate change were also suggested.