Disaster Management Research Articles

Reshaping disaster management: An integrated community‐led approach

AbstractThe management of disasters has traditionally involved public, private, and nongovernmental organisations working together. While scholars have examined the value of collaborations among these entities, less is known about how to successfully engage and empower communities in disaster management. Based on network governance theory, this article contributes to the growing body of public management literature on community engagement by presenting findings from an Australian research initiative conducted after the 2019/20 Black Summer bushfires in New South Wales. Through workshops and semi‐structured interviews with a total of 58 members from local communities and emergency agencies, this paper identifies differing perspectives on power distribution among stakeholders, indicating complexities in achieving an integrated and community‐led disaster management approach. The findings underscore the need to shift from exclusively centralised to more inclusive systems, recognising the unique contributions of nonofficial community‐based groups. To address this, the study suggests: a funded community consultation committee, ensuring government and local community representation; collaborative debriefing sessions, leveraging technology for knowledge capture; and the adoption of different leadership styles able to identify, include, and integrate communities as both steerers and rowers within established hierarchical arrangements.Points for practitioners The current centralised emergency management system, which relies on recognised experts and state‐controlled facilities, limits the integration of nonofficial resources and community‐based knowledge. A shift towards a more community‐centric and integrated approach (collaborative polycentric governance) is needed to enhance disaster resilience and response in Australia. Different stages of disaster reduction could and should have different leadership styles: a transformational, collaborative community‐based style should be implemented before and after the disaster, while a transactional leadership style, more focused on restructuring the system or how it is applied, should be adopted during the disaster.

Green Management for Disasters Using an Inflatable Tent Prototype with a Solar Power Plant

Given the ever-increasing number of natural disasters, disaster management must be understood and implemented by all parties in a manner that includes green management and technology. This research begins with the problem of disaster preparedness management which currently uses less environmentally friendly facilities and infrastructure, including using tents with conventional structures and technological systems that are less flexible and require electricity with a gasoline-fueled generator. The aim of this research is to create a green technology-based disaster response facility in the form of an inflatable tent prototype for disaster preparedness using solar electricity. The method used in this study is experimental, designing and manufacturing prototype inflatable tents that use solar power plants. Tests are carried out on several variables: strength of tarpaulins, speed in construction and disassembly, comfort of air temperature, and performance of solar power generation. The results are of the experimental method are: the design and application of two prototype inflatable tents dimensions 6x9 square meters with a capacity of 20 patients, a 3,600 WP power plant using solar power, and a VRLA battery with a voltage capacity of 48 volts and a current of 200 Ah that is capable storing 4,800 watts of electricity. Thus, these devices meet electricity needs for air conditioning, lighting, and medical equipment in inflatable tents without using electricity from the state electricity company or gasoline generators. Keywords: disaster, inflatable tent, solar power generation

Selecting facility location of Gendarmerie Search and Rescue (GSR) Units; An analysis of efficiency in disaster response

Disasters, referred to as events that result in physical, economic, and social losses for individuals and disrupt the daily activities of human communities, necessitate ongoing preparedness due to their unpredictable nature. Swift response during and after a disaster is crucial for preserving human life. Hence, it is imperative to initiate planning immediately following a disaster to ensure readiness for various tasks. Given these factors, search and rescue units must carefully select a base location that enables them to promptly reach affected areas.Disasters exhibit unique characteristics across different regions of Türkiye. While some regions are prone to earthquakes, others face the risks of landslides, avalanches, or floods. Consequently, the required measures for disaster management vary from region to region. Nevertheless, when the term “disaster” is mentioned in Türkiye, earthquakes often come to mind due to their frequent occurrence and significant impact. The Gendarmerie Search and Rescue (GSR) units have been actively responding to these earthquakes, renowned for their exemplary institutional discipline and working methods. This study aims to examine the operations and deployment locations of GSR units, which play a crucial role in mitigating the impact of frequent earthquakes in Türkiye, utilizing a SWOT analysis. Additionally, a Multi-Criteria Decision Making-based mathematical model will be employed to optimize task activities and to select the most suitable facility locations for GSR units. The use of mathematical modeling in this context ensures that GSR units are strategically positioned to maximize their operational effectiveness and minimize response times. The results will be evaluated through sensitivity analysis.

Community Participation in Flood Management Systems in Aceh Utara Regency

Flooding remains a persistent challenge in Aceh Utara Regency, representing a complex, cross-sectoral issue. If not addressed through collaboration among various stakeholders, including community groups, it has the potential to lead to new societal problems. This research seeks to assess the effectiveness and impact of using a participatory model in flood management efforts in the region. A qualitative approach was employed, gathering data through in-depth interviews with stakeholders such as local communities, government authorities, and non-governmental organizations involved in flood mitigation programs. The findings emphasize the urgency of adopting a participatory model to enhance the effectiveness of flood management systems. Actively engaging the community in planning, execution, and evaluation processes leads to a deeper understanding of local conditions, needs, and suitable solutions. Key aspects of the participatory model include raising public awareness of flood risks and mitigation measures, improving flood management infrastructure based on community input, creating more accessible and effective evacuation plans, and strengthening the community’s capacity for emergency response and simple mitigation efforts. In conclusion, this study aims to further explore the relevance and effectiveness of the participatory model in flood management in Aceh Utara Regency, ensuring the long-term sustainability of the region's disaster management system.

Geospatial analysis and AHP for flood risk mapping in Quetta, Pakistan: a tool for disaster management and mitigation

The 2022 flood events in Quetta, Pakistan, caused severe damage to the economy, properties, and lives. Therefore, flood risk mapping to identify flood-prone areas is essential for planners and decision-makers to take critical protective measures to control the effects of flooding. This study focuses on mapping flood-prone regions in the Quetta district of Pakistan using an analytical hierarchy process (AHP) and a geographic information system (GIS). The factors influencing flood used in the present study were topographic witness index (TWI), elevation, slope, land use, land cover, precipitation, stream distance, drainage density, and soil type. Weights and ranks were allocated separately to all factors through AHP and were interpreted in a GIS environment. The produced flood hazard model of the study area depicted four zones. These zones ranged from low (19.49%), moderate (43.34%), high (28.30%), to very high (8.87%). The model was further validated through previous flood events in the study area. Around 90% of flood hazard events in the past took place mainly in the produced model's very high and high zones, which is why the current model is reliable. Finally, integrating geospatial approaches with AHP in flood hazard mapping is a quick, reliable, and affordable method that may be utilized in the area.

A tale of two disasters: Unpacking how social learning from the Ebola epidemic shaped COVID‐19 response in informal settlements in Freetown

AbstractPrior disaster experiences often provide lessons for communities to respond to new disasters. In informal communities prone to disasters but conditioned within reactive disaster management regimes, residents and Community‐Based Organizations (CBOs) play immense roles in disaster risk reduction and response. In Freetown, Sierra Leone, limited government disaster capacities during health disasters like Ebola and the COVID‐19 pandemic occasioned community action led by residents and CBOs. This paper, utilizing qualitative data, draws on the social learning theory to unpack how residents’ and CBOs’ experiences with the Ebola epidemic provided profound lessons that contributed to the COVID‐19 pandemic response in two informal communities. Findings highlight how prior disaster experiences consolidate memory and generate attention, retention, motivation, and reproduction of lessons for future disasters. The paper also fronts how lessons from peoples’ lived experiences with disasters can offer pluralistic ways of knowing about disasters and responding to future risks through co‐productive and equitable strategies.

A LoRa-Based Disaster Management System for Search and Rescue Mission

A LoRa-Based Disaster Management System for Search and Rescue Mission

Seismic monitoring of 2020 Baghjan oil-well blowout incident in Assam, India

Characterization of a productive oil/gas well blowout through seismological methods is relatively uncommon. In this paper, we conduct an in-depth seismic evaluation of one of the world’s most significant onshore oil well blowout incidents, which occurred in 2020 at the Baghjan oil field in Assam, northeast India. We show that the blowout and related on-site activities generated distinct signals that can be distinguished by their spectral characteristics, temporal variation in geometric spreading, and sharp attenuation of daytime noise in comparison to the nighttime. A micro-earthquake potentially triggered by the blowout was also detected. Furthermore, we show how seismic data can be used to reasonably estimate blowout gas exit velocity and flame height. Our results demonstrate that a detailed characterization and spatiotemporal variation of blowout activity can be successfully captured through seismic monitoring, opening new opportunities for hazard mitigation and cost-effective disaster management for such catastrophic events.

A Survey of Middleware Adoption in Nonprofit Sectors: A Sustainable Development Perspective

Nonprofit Organizations (NPOs) are adopting technology to improve their quality of services, scale up, or reduce operation costs. However, due to the heterogeneity of systems they use, NPOs face system-integration challenges when collaborating with other organizations. Middleware is an intermediary software that assists dissimilar systems in working together. This paper explores middleware applications, opportunities, and challenges within the sector. It extensively reviewed the current state of research on middleware usage in the nonprofit sector for all papers published in Scopus and Web of Science (WoS) until 2023. Out of 127 papers returned, only 31 remained after removing duplicates, invalid entries, and out-of-scope publications. Then, we synthesized insights from a thorough survey of these selected papers. In light of the survey results, we observed that NPOs primarily use middleware in a few of the Sustainable Development Goals (SDGs), namely, health (SDG 3), NPO operations (SDG 8 and 9), NPO collaborations (SDG 17), development of sustainable cities (SDG 11), security and disaster management (SDG 16), and education (SDG 4). We also identified several challenges related to using middleware in the nonprofit sector, which include privacy, security, system development and performance, data processing and transfer, and volunteer attrition.

Measuring Amazon Rainfall Intensity With Sound Recorders

AbstractGround weather observations are scarce in many parts of the globe, hampering effective climate monitoring and disaster management. In the Amazon basin, this occurs due to its remoteness and the challenging measurement of rainfall within the forest. Innovative rainfall estimation methods are thus requested to fill this gap. Here we present an approach to estimate rainfall based on sound measurements. We identified the best frequency range to estimate rainfall occurrence and intensity, trained classification and regression models with sound and rain gauge data collected in the Central Amazon during 9 months. By training a random forest classifier/regression model based on power spectrum values it was possible to identify and satisfactorily estimate hourly rainfall rates in two vegetation environments distinct from the training site, located 30 km from it. The proposed method is a promising approach for future weather monitoring in remote tropical areas.

Analyzing the Spatiotemporal Changes in Climatic Extremes in Cold and Mountainous Environment: Insights from the Himalayan Mountains of Pakistan

This study assessed the past changes in extreme precipitation and temperature events across the Himalayan Mountains of Pakistan. This cold and mountainous environmental region has witnessed a significant increase in climate-related disasters over the past few decades. Spatiotemporal changes in extreme temperature and precipitation events were analyzed using 24 indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). For this study, in situ data of 16 national meteorological stations were obtained from the Pakistan Meteorological Department (PMD) for the past three decades (1991–2020). The significance of the trends was assessed using the modified Mann–Kendall (MMK) test, and the Theil–Sen (TS) slope estimator was used to estimate the slope of the trend. The results showed that there has been a consistent decline in the total precipitation amount across the Himalayan Mountains of Pakistan. The trend exhibited a decrease in the annual average precipitation at a rate of −6.56 mm/year. Simultaneously, there was an increasing trend in the annual average minimum and maximum temperatures at rates of 0.02 °C/year and 0.07 °C/year, respectively. The frequencies of consecutive wet days (CWDs) and maximum 5-day precipitation (RX5day) have decreased significantly, with decreasing rates of −0.40 days/year and −1.18 mm/year, respectively. The amount of precipitation during very wet days (R95p) and extremely wet days was decreased by −19.20 and −13.60 mm/decade, respectively. The warm spell duration (WSDI) and the frequency of warm days (TX90p) across the Himalayan Range both increased by 1.5 and 1.4 days/decade. The number of cold days (TX10p) and cold nights (TN10p) decreased by 2.9 and 3.4 days/decade. The average temperature of the hottest nights (TXn) and the diurnal temperature range (DTR) were increased by 0.10 and 0.30 °C/decade. The results indicated an increasing tendency of dry and warm weather in the Himalayan region of Pakistan, which could have adverse consequences for water resources, agriculture, and disaster management in the country. Therefore, it is essential to prioritize the implementation of localized adaptation techniques in order to enhance sustainable climate resilience and effectively address the emerging climate challenges faced by these mountainous regions.

Geospatial Mapping and Meteorological Flood Risk Assessment: A Global Research Trend Analysis.

Flooding is a global threat causing significant economic and environmental damage, necessitating a policy response and collaborative strategy. This study assessed global research trends and advances in geospatial and meteorological flood risk assessment (G_MFRA), considering the ongoing debate on flood risk management and adaptation strategies. A total of 1872 original articles were downloaded in BibTex format using the Web of Science (WOS) and Scopus databases to retrieve G_MFRA studies published from 1985 to 2023. The annual growth rate of 15.48% implies that the field of G_MFRA has been increasing over time during the study period. The analysis of global trends in flood risk research and practice highlights the key themes, methodologies, and emerging directions. There exists a notable gap in data and methodologies for flood risk assessment studies between developed and developing countries, particularly in Africa and South America, highlighting the urgency of coordinated research efforts and cohesive policy actions. The challenges identified in the body of extant literature include technical expertise, complex communication networks, and resource constraints associated with the application gaps of the study methodologies. This study advocates for a holistic research approach to flood disaster management through ecosystem-based adaptation that underpins the Sustainable Development Goals to develop innovative flood techniques and models with the potential to influence global decision-making in the G_MFRA domain. Addressing these global challenges requires a networked partnership between the research community, institutions, and countries.

Enhancing precision of flood estimation in EOS-04 SAR imagery: a statistical approach

Floods pose a recurrent and devastating natural disaster in India, and accurate and timely assessment of their extent is crucial for effective disaster management and mitigation efforts. In this regard, this study proposes a novel approach for flood inundation estimation through the statistical analysis of two key geospatial datasets: the Normalized Difference Flood Index (NDFI) and temporal Standard Deviation images. To establish a baseline under ordinary conditions, two products were derived. The first product is the mean image during the non-flood season, and the second is the temporal Standard Deviation image for the entire year. These images are derived from Sentinel-1A Synthetic Aperture Radar (SAR) data using Google Earth Engine (GEE). The NDFI is calculated by comparing the mean image to the image obtained during flood event, allowing the identification of flood-affected areas. The process involves constructing Kernel Density Estimation (KDE) plots for NDFI and Standard Deviation, from which a 95% density ellipse is generated using the covariance matrix and eigenvalues. Multiple SAR scenes from diverse regions in India are analyzed individually, yielding density ellipses for each location. The innovative step lies in synthesizing these individual ellipses into the best fit ellipse through the convex hull method. This best fit ellipse encapsulates the general flood characteristics observed across disparate geographic regions, providing a unified representation. The derived best fit ellipse serves as a powerful tool for generating near-real-time flood inundation maps, with an overall accuracy of over 98.2%. Thus, the fusion of statistical insights and historical SAR information enables rapid near-real-time flood mapping, with enhanced accuracy of flood extent predictions.

Analyzing Public Interest in Geohazards Using Google Trends Data

This study investigates public interest in geological disasters by analyzing Google Trends data from 2023. This research focuses on earthquakes, hurricanes, floods, tornadoes, and tsunamis to understand how search behaviors reflect public awareness and concern. This study identifies temporal and geographical patterns in search trends. Key findings reveal that public interest spikes during significant disaster events, such as the February 2023 earthquake in Turkey and Syria and the August 2023 hurricanes in the United States. This study highlights the importance of timely and accurate information dissemination for disaster preparedness and response. Google Trends proves to be a valuable tool for monitoring public interest, offering real-time insights that can enhance disaster management strategies and improve community resilience. This study’s insights are essential for policymakers, disaster management agencies, and educational efforts aimed at mitigating the impacts of natural disasters.

Assessing coastal community resilience to climate change in Central Vietnam through the Climate Disaster Resilience Index (CDRI)

Abstract This study investigates the climate resilience of coastal communities in Vietnam's Nghe An province, a region highly exposed due to its extensive coastline and dense population. Employing the Climate Disaster Resilience Index (CDRI), the research assesses the resilience of three districts — Quynh Luu, Dien Chau, and Nghi Loc — to climate-induced disasters. The analysis reveals good to high overall resilience across five dimensions (physical, social, economic, institutional, and natural). Dien Chau boasts the highest score (4.06), followed by Quynh Luu (4.04), and Nghi Loc (4.01). While strong infrastructure and essential services contribute to high physical resilience, social capital development requires further attention. Economic resilience is bolstered by employment rates, but income and asset accumulation need improvement. Effective policies and disaster risk management strategies highlight strong institutional resilience. Natural resource management demonstrates adaptability, but land-use planning warrants enhancement. This study underscores the districts' good preparedness for climate challenges while pinpointing areas for improvement across all CDRI dimensions. By addressing these vulnerabilities, Nghe An's coastal communities can further strengthen their resilience.

An Analysis of Heat Waves in Disaster Management

This paper examines the current state of disaster management for heat waves in the United States. The paper begins by providing the status of heat waves in the U. S. A. and the detrimental effects they can have on society, such as human and animal health concerns, damage to infrastructure, and strained power grids. The paper then provides a synopsis of the disaster management framework provided by the U. S. government. This entails a description of the five stages of disaster management: Prevention, Protection, Mitigation, Response, and Recovery. Next, the current public health measures taken to address extreme heat are organized within this framework, described, and assessed based on a review of existing literature. These public health measures include protection of the power grid, incorporating green and cool spaces into city design, cooling centers, and heat warning systems. The results of the literature review show that actions taken prior to an extreme heat event are more effective than actions taken in response to the event or during the recovery from it. Measures taken in the Protection and Mitigation stages have a more reliable and documentable benefit to human health than measures in the Response and Recovery stages. Additionally, these actions, such as safeguarding power grids and installing green infrastructure in urban environments, generally provide financial benefits that exceed their costs, making them good investments for both public and private entities. It is therefore recommended to focus programs and investment on measures in the Protection and Mitigation phases.

Seismicity and fractal analysis in Aswan region, southern Egypt

Seismic activity in Aswan is influenced by the complex interactions of tectonic plates, the accumulation of stress, and the presence of geological fault systems. It revealed that epicenters are well distributed along four fault segments in a conjugate pattern, indicating a prominent E-W compressional stress. This research aims to explore the characteristics of seismicity and seismotectonics, with a focus on assessing their implications for risk reduction and disaster management in this densely populated region. A data review from the Egyptian National Seismological Network (ENSN) identified 464 earthquakes occurred between 2000 and 2021, with local magnitudes ranging from 0.3 to 4.4, and depths up to 25 km. The calculated Gutenberg-Richter b-value is approximately 0.87 ± 0.05, indicating a gradual stress accumulation. The current analysis shows a more consistent level of moderate seismic activity, unlike previous studies in Aswan region that reported a wide range of b-values from 0.554 to 1.07. This suggests that while earlier research captured a wider range of seismic behaviors, recent data indicates a stabilization in earthquake frequency and intensity. Additionally, the fractal dimension (Dc) calculated at 1.57 ± 0.04 shows an intermediate level of complexity and reflecting a clustering pattern of earthquakes. The variations in the b-value with different magnitudes and depths signify the involvement of active smaller faults, responsible for earthquakes up to magnitude 2.2, which then transition to fractured zones inducing earthquakes up to magnitude 2.5. This transition is followed by a decline in seismic activity, indicating regions that are potentially more likely to experience larger earthquakes. Moreover, stress disparities at various depths contribute to smaller earthquakes within the 5–10 km depth range. Return period analysis suggests that the earthquakes of magnitude 3.7 or higher are expected to occur approximately once every decade in Aswan. These findings are of utmost importance for earthquake risk reduction, hazard assessment, and the sustainable development of Aswan area.

Collaborative governance and integrated risk management framework of natural disasters

PurposeThis study aims to align the objectives of key stakeholders by developing an integrated framework for high-impact natural disaster risk management. High-impact natural disasters have emerged as one of the most challenging policy issues.Design/methodology/approachThe authors have applied the thematic text analysis for analysing the list of questions essential to develop an integrated framework. For theory, the authors have used the theoretical framework of collaborative governance.FindingsThe current work explains how to identify key stakeholders. Furthermore, it describes the framework to fit stakeholders' actions into the actionable components of risk management. Additionally, this framework also helps the firms that fall under the category of the industries “in the proximity of risks” and “the support industries” in modifying their role in the context of natural disaster risk.Research limitations/implicationsThe limitation of this framework is that the authors relied on commonly occurring natural disaster risks to develop the framework. Therefore, risk-specific aspects are less likely to be thoroughly covered in this framework. However, this limitation is not directly impacting the goal of this study. Additionally, in the future more comprehensive framework with the additional element in the existing framework can overcome these limitations.Practical implicationsThe findings of the study offer insights that can be useful for policymakers in developing various preventive strategies. Managers can use the results and align their objectives with policy goals.Social implicationsSocially, if communities try to design local risk management strategies, this framework would be helpful.Originality/valueThis study illustrates the role of objective alignment in high-impact risk management. This study is crucial in extending current knowledge on high-impact natural disaster risk management.

Urban Flooding Disaster Risk Assessment Utilizing the MaxEnt Model and Game Theory: A Case Study of Changchun, China

This research employs the maximum entropy (MaxEnt) model alongside game theory, integrated with an extensive framework of natural disaster risk management theory, to conduct a thorough analysis of the indicator factors related to urban flooding. This study conducts an assessment of the risks associated with urban flooding disasters using Changchun city as a case study. The validation outcomes pertaining to urban flooding hotspots reveal that 88.66% of the identified flooding sites are situated within areas classified as high-risk and very high-risk. This finding is considered to be more reliable and justifiable when contrasted with the 77.73% assessment results derived from the MaxEnt model. Utilizing the methodology of exploratory spatial data analysis (ESDA), this study applies both global and local spatial autocorrelation to investigate the disparities in the spatial patterns of flood risk within Changchun. This study concludes that urban flooding occurs primarily in the city center of Changchun and shows a significant agglomeration effect. The region is economically developed, with a high concentration of buildings and a high percentage of impervious surfaces. The Receiver Operating Characteristic (ROC) curve demonstrates that the MaxEnt model achieves an accuracy of 90.3%. On this basis, the contribution of each indicator is analyzed and ranked using the MaxEnt model. The primary determinants affecting urban flooding in Changchun are identified as impervious surfaces, population density, drainage density, maximum daily precipitation, and the Normalized Difference Vegetation Index (NDVI), with respective contributions of 20.6%, 18.1%, 13.1%, 9.6%, and 8.5%. This research offers a scientific basis for solving the urban flooding problem in Changchun city, as well as a theoretical reference for early warnings for urban disaster, and is conducive to the realization of sustainable urban development.

Whether higher risk indicates severe loss in the flood disaster assessment: A comparative analysis in the Hubei province of central China

Study regionHubei province, Yangtze River Basin, Central China Study focusRisk and loss analysis constitutes a critical element of flood disaster management. Nevertheless, the relationship between risk and loss has been infrequently examined in the literature. Here we developed a comparative analysis framework for assessing flood risk and loss in Hubei Province. The risk model incorporates 22 indicators in terms of hazard, exposure, vulnerability and emergency response & recovery capability. Indicator weights were determined through a combination of objective and subjective weighting methods based on the game theory. Flood risk and loss levels were classified using fuzzy comprehensive evaluation and grey correlation analysis respectively. New hydrological insightsAnnual risk and loss maps exhibit a spatial pattern of higher levels in the eastern regions and lower levels in the western regions. However, the relationship between risk and loss was not as well as expected during designated flood periods. While regions impacted by disasters typically demonstrated higher risk levels, the risk in the regions unaffected by flood disasters appeared to be overestimated. By analyzing flood risk and loss across various temporal scales, this research contributes a novel perspective for the evaluation of flood risk models.