Pub Date : 2025-03-20DOI: 10.1016/j.ijdrr.2025.105416
Zahide Gül Aktepe , M. Engin Deniz , Yavuz Erişen , Gaye Bırni , Begüm Satıcı , Yağmur Kaya
The earthquake is not only a destruction of buildings, but also a shattering of people's mental states. How survivors regulate dysfunctional feelings and thoughts toward death in the aftermath of an earthquake is a matter of curiosity. Therefore, this study examined the role of hope, psychological inflexibility, and psychache, which will provide a better understanding of people's obsession with death after the earthquake in Turkey. Participants were 419 Turkish individuals aged 18–59 years from 61 cities in Turkey. Structural equation modeling was performed. The findings showed the full mediation model that psychological inflexibility and psychache had significant mediating roles in the relationship between hope and death obsession, respectively. Whether directly or indirectly, increased hope is associated with less psychological inflexibility and less psychache among earthquake survivors. Positive and healing potentials of hope and psychological flexibility in reducing obsession with death in individuals with earthquakes or other traumatic experiences have been revealed.
{"title":"Hope and death obsession after the Maras earthquake: Psychological inflexibility and psychache as serial mediators","authors":"Zahide Gül Aktepe , M. Engin Deniz , Yavuz Erişen , Gaye Bırni , Begüm Satıcı , Yağmur Kaya","doi":"10.1016/j.ijdrr.2025.105416","DOIUrl":"10.1016/j.ijdrr.2025.105416","url":null,"abstract":"<div><div>The earthquake is not only a destruction of buildings, but also a shattering of people's mental states. How survivors regulate dysfunctional feelings and thoughts toward death in the aftermath of an earthquake is a matter of curiosity. Therefore, this study examined the role of hope, psychological inflexibility, and psychache, which will provide a better understanding of people's obsession with death after the earthquake in Turkey. Participants were 419 Turkish individuals aged 18–59 years from 61 cities in Turkey. Structural equation modeling was performed. The findings showed the full mediation model that psychological inflexibility and psychache had significant mediating roles in the relationship between hope and death obsession, respectively. Whether directly or indirectly, increased hope is associated with less psychological inflexibility and less psychache among earthquake survivors. Positive and healing potentials of hope and psychological flexibility in reducing obsession with death in individuals with earthquakes or other traumatic experiences have been revealed.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"121 ","pages":"Article 105416"},"PeriodicalIF":4.2,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-19DOI: 10.1016/j.ijdrr.2025.105402
Erhan Tunç , Gülşah Candemir
This qualitative study, in which the phenomenon of “being affected by an earthquake as a traumatic experience” was examined in order to contribute to the management of risk situations that may arise in possible disasters, was conducted with a interpretive/phenomenological design. The data were obtained by interviewing adults who experienced the earthquake in Kahramanmaraş (Turkey) on February 6, 2023. A semi-structured interview questions including psychological interpretation steps was used. The data obtained from the interviews were visualized using MAXQDA software and contributed to making them more understandable for the reader. Most of the participants explained the earthquake with the metaphor of “apocalypse”. It was understood that they explained the moment of the earthquake as “humming and explosion sounds”, “death” and “collapse of the building” and showed reactions such as “being under the rubble”, “helplessness”, “shock” and “praying”. In the adaptation process after the earthquake, it was observed that they felt the “need to make sense” and resorted to “social support repertoire” to cope. This study on post-earthquake reactions emphasized the individual and social effects of the earthquake.
{"title":"Earthquake as a traumatic experience: Earthquake survivors' post-earthquake reactions, meaning-making and reconstruction processes","authors":"Erhan Tunç , Gülşah Candemir","doi":"10.1016/j.ijdrr.2025.105402","DOIUrl":"10.1016/j.ijdrr.2025.105402","url":null,"abstract":"<div><div>This qualitative study, in which the phenomenon of “being affected by an earthquake as a traumatic experience” was examined in order to contribute to the management of risk situations that may arise in possible disasters, was conducted with a interpretive/phenomenological design. The data were obtained by interviewing adults who experienced the earthquake in Kahramanmaraş (Turkey) on February 6, 2023. A semi-structured interview questions including psychological interpretation steps was used. The data obtained from the interviews were visualized using MAXQDA software and contributed to making them more understandable for the reader. Most of the participants explained the earthquake with the metaphor of “apocalypse”. It was understood that they explained the moment of the earthquake as “humming and explosion sounds”, “death” and “collapse of the building” and showed reactions such as “being under the rubble”, “helplessness”, “shock” and “praying”. In the adaptation process after the earthquake, it was observed that they felt the “need to make sense” and resorted to “social support repertoire” to cope. This study on post-earthquake reactions emphasized the individual and social effects of the earthquake.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"121 ","pages":"Article 105402"},"PeriodicalIF":4.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-19DOI: 10.1016/j.ijdrr.2025.105417
Bo Liu , Haixiang Guo , Haizhong Wang
Accurately identifying interrelationships between disasters is essential for comprehensive multi-disaster risk assessment. Traditional manual methods rely heavily on expert judgment, which may lead to overlooked or inconsistently documented disaster interrelationships. To address this challenge, this study develops an AI-driven approach to automatically extract disaster interrelationships from large-scale textual data using a fine-tuned Universal Information Extraction model. First, disaster interrelationships are systematically categorized into six distinct types, considering both disaster causation and impact perspectives. Secondly, a large-scale dataset is constructed by collecting 5212 Chinese-language disaster-related paper abstracts from the China National Knowledge Infrastructure (CNKI). Among them, 267 abstracts were manually annotated to train and evaluate the model. Thirdly, the fine-tuned model is applied to the remaining 4945 abstracts to extract large-scale disaster relationship triplets, with manual validation conducted for less common triplets to ensure result reliability. Finally, disaster interrelationships are visualized using complex network graphs and matrices, providing an intuitive representation of multi-disaster interrelationships. The key contribution of this research is the development of an AI-driven approach to systematically extract disaster interrelationships from large-scale datasets, improving the accuracy and scalability of identifying disaster interrelationships. Furthermore, this study establishes a comprehensive and updatable database of disaster interrelationships, addressing limitations in previous research, such as incomplete data coverage and limited exploration of relationship types, and helps scholars to identify disaster interrelationships that may have been previously overlooked.
{"title":"An AI-driven approach to extract interrelationships between disasters","authors":"Bo Liu , Haixiang Guo , Haizhong Wang","doi":"10.1016/j.ijdrr.2025.105417","DOIUrl":"10.1016/j.ijdrr.2025.105417","url":null,"abstract":"<div><div>Accurately identifying interrelationships between disasters is essential for comprehensive multi-disaster risk assessment. Traditional manual methods rely heavily on expert judgment, which may lead to overlooked or inconsistently documented disaster interrelationships. To address this challenge, this study develops an AI-driven approach to automatically extract disaster interrelationships from large-scale textual data using a fine-tuned Universal Information Extraction model. First, disaster interrelationships are systematically categorized into six distinct types, considering both disaster causation and impact perspectives. Secondly, a large-scale dataset is constructed by collecting 5212 Chinese-language disaster-related paper abstracts from the China National Knowledge Infrastructure (CNKI). Among them, 267 abstracts were manually annotated to train and evaluate the model. Thirdly, the fine-tuned model is applied to the remaining 4945 abstracts to extract large-scale disaster relationship triplets, with manual validation conducted for less common triplets to ensure result reliability. Finally, disaster interrelationships are visualized using complex network graphs and matrices, providing an intuitive representation of multi-disaster interrelationships. The key contribution of this research is the development of an AI-driven approach to systematically extract disaster interrelationships from large-scale datasets, improving the accuracy and scalability of identifying disaster interrelationships. Furthermore, this study establishes a comprehensive and updatable database of disaster interrelationships, addressing limitations in previous research, such as incomplete data coverage and limited exploration of relationship types, and helps scholars to identify disaster interrelationships that may have been previously overlooked.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"121 ","pages":"Article 105417"},"PeriodicalIF":4.2,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Extreme flooding can inundate critical nodes in urban metro network, triggering system failures. However, comprehensive indicators for identifying critical nodes and assessing network impacts under disruptions remain underdeveloped. Research also largely relies on hypothetical disruptions rather than flood events with specific intensities and spatial extents. This study replicates the “7·20” extreme rainstorm that occurred in Zhengzhou and applies it to Shanghai through a numerical flood simulation. Using Shanghai's weighted metro network, which includes stations, lines and passenger flow, we employ a complex network method to identify critical nodes and simulate the impact of their failure due to flooding on network functionality. Finally, we discuss the recovery priorities for failed nodes in terms of network functionality. Our results indicate that 54 stations, comprising 14.2 % of the total, may experience water inflow and failure. Stations with high centrality scores, primarily located within the city's inner ring, are particularly prone to flooding. Successive station failures lead to a loss of 1.6 %–76.5 % in the network efficiency (NE) and 0.7 %–82.7 % in the giant connected component (GCC). When the number of failed stations reaches 13, network functionality experiences a dramatic loss of approximately 50 %. Compared to the greedy algorithm (GA), the criticality-based approach is less efficient in restoring network functionality but more computationally feasible. By incorporating flood scenarios and weighted indicators, our approach offers more context-driven and practical insights. Our study provides a methodology for the rapid assessment of critical node exposure, functional impact, and optimal recovery strategies for metro network based on various scenarios.
{"title":"Critical node failure, impact and recovery strategy for metro network under extreme flooding in Shanghai","authors":"Deyin Jing , Weijiang Li , Jiahong Wen , Wei Hou , Hangxing Wu , Jianli Liu , Min Zhang , Weijun Zhang , Tongfei Tian , Zixia Ding , Hongcen Guo","doi":"10.1016/j.ijdrr.2025.105414","DOIUrl":"10.1016/j.ijdrr.2025.105414","url":null,"abstract":"<div><div>Extreme flooding can inundate critical nodes in urban metro network, triggering system failures. However, comprehensive indicators for identifying critical nodes and assessing network impacts under disruptions remain underdeveloped. Research also largely relies on hypothetical disruptions rather than flood events with specific intensities and spatial extents. This study replicates the “7·20” extreme rainstorm that occurred in Zhengzhou and applies it to Shanghai through a numerical flood simulation. Using Shanghai's weighted metro network, which includes stations, lines and passenger flow, we employ a complex network method to identify critical nodes and simulate the impact of their failure due to flooding on network functionality. Finally, we discuss the recovery priorities for failed nodes in terms of network functionality. Our results indicate that 54 stations, comprising 14.2 % of the total, may experience water inflow and failure. Stations with high centrality scores, primarily located within the city's inner ring, are particularly prone to flooding. Successive station failures lead to a loss of 1.6 %–76.5 % in the network efficiency (NE) and 0.7 %–82.7 % in the giant connected component (GCC). When the number of failed stations reaches 13, network functionality experiences a dramatic loss of approximately 50 %. Compared to the greedy algorithm (GA), the criticality-based approach is less efficient in restoring network functionality but more computationally feasible. By incorporating flood scenarios and weighted indicators, our approach offers more context-driven and practical insights. Our study provides a methodology for the rapid assessment of critical node exposure, functional impact, and optimal recovery strategies for metro network based on various scenarios.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"121 ","pages":"Article 105414"},"PeriodicalIF":4.2,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bangladesh faces various acute and chronic natural calamities due to its precarious global positioning. Floods are among Bangladesh's leading and most frequent disasters. While much research has been published on the association between flood risk and agricultural losses, significant gaps exist in recognizing the relationship between monsoon flood disasters and agrarian land and production losses. This study aims to investigate the substantial crop losses brought on by monsoon floods, with a particular emphasis on the impacts of floods on crop productivity and strategies to mitigate those effects. It also describes the FAO method for assessing flood damage to the agricultural sector, concentrating mainly on flood damage to rice and jute crops. Both qualitative and quantitative methodologies were employed to collect and analyze the data for this study. Primary data was collected through interviews, structured questionnaires, personal observations, and informal discussions with 250 respondents. Secondary data was obtained from official records such as libraries, journals, yearly reports, statistics yearbooks, newspapers, and other relevant sources.
The combined quantitative and qualitative data revealed that flooding interrupts crop-growing patterns (rice, potato, pepper, and maize), decreases cropping land area, reduces crop production, and affects socio-economic conditions overall. In addition, this study focuses on the barriers and constraints that could obviate flood management. Hence, floods cause production losses of about 2.25 metric tons of rice and 2 metric tons of jute, equivalent to more than 50,000 ($600) and 45,000 ($550) BDT, individually. The study further recommended a monsoon flood management approach that prioritizes resilience and infrastructure development through constant surveillance and evaluation to ensure regional food security utilizing sustainable crop production. The crop damage assessment method described in this paper can also be applied in other areas for flood risk management.
{"title":"Assessing the interrelationship between monsoon flood disasters and major crop production in Bangladesh","authors":"Md Ashikur Rahman , Md Shafiul Alam , Rumana Sultana , Razia Sultana","doi":"10.1016/j.ijdrr.2025.105401","DOIUrl":"10.1016/j.ijdrr.2025.105401","url":null,"abstract":"<div><div>Bangladesh faces various acute and chronic natural calamities due to its precarious global positioning. Floods are among Bangladesh's leading and most frequent disasters. While much research has been published on the association between flood risk and agricultural losses, significant gaps exist in recognizing the relationship between monsoon flood disasters and agrarian land and production losses. This study aims to investigate the substantial crop losses brought on by monsoon floods, with a particular emphasis on the impacts of floods on crop productivity and strategies to mitigate those effects. It also describes the FAO method for assessing flood damage to the agricultural sector, concentrating mainly on flood damage to rice and jute crops. Both qualitative and quantitative methodologies were employed to collect and analyze the data for this study. Primary data was collected through interviews, structured questionnaires, personal observations, and informal discussions with 250 respondents. Secondary data was obtained from official records such as libraries, journals, yearly reports, statistics yearbooks, newspapers, and other relevant sources.</div><div>The combined quantitative and qualitative data revealed that flooding interrupts crop-growing patterns (rice, potato, pepper, and maize), decreases cropping land area, reduces crop production, and affects socio-economic conditions overall. In addition, this study focuses on the barriers and constraints that could obviate flood management. Hence, floods cause production losses of about 2.25 metric tons of rice and 2 metric tons of jute, equivalent to more than 50,000 ($600) and 45,000 ($550) BDT, individually. The study further recommended a monsoon flood management approach that prioritizes resilience and infrastructure development through constant surveillance and evaluation to ensure regional food security utilizing sustainable crop production. The crop damage assessment method described in this paper can also be applied in other areas for flood risk management.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"121 ","pages":"Article 105401"},"PeriodicalIF":4.2,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-18DOI: 10.1016/j.ijdrr.2025.105415
Reina Mae B. Chong , Deborah N. Tangunan , Dexter M. Toyado , Aljon Francis Koji Elegado
The Philippines is consistently one of the world's most at-risk countries due to its location within the Pacific Ring of Fire and the “typhoon belt”. However, resilience at national and regional levels remains understudied, particularly in relation to socio-economic inequalities, gender dynamics, and governance. This study addresses this gap by analyzing resilience trends from the 2021 and 2023 World Risk Poll (WRP) Philippines dataset, focusing on the influence of gender, urbanicity, and income across individuals, households, communities, and society, using statistical and data analysis tools. Results reveal a general decline in scores, with sharp drops in Region 4B (MIMAROPA–highest resilience) and Region 7 (Central Visayas–mid-range). Conversely, Region 13 (Caraga–lowest) and Region 5 (Bicol–mid-range) improved, reflecting the success of community-based disaster risk reduction initiatives and governance. Gender disparities narrowed, with women scoring higher in household and societal resilience, while men excelled in community resilience. Urbanicity showed no significant association, although urban areas had higher individual and household resilience, while rural areas demonstrated stronger societal resilience. Income disparities persisted, with higher-income groups consistently achieving greater resilience, particularly at individual and household levels, due to better access to resources and opportunities. These findings emphasize the need for targeted, evidence-based strategies to build resilience in vulnerable regions in the Philippines, informing inclusive policies, equitable resource distribution, and governance collaboration. While the WRP provides valuable insights, reliance on self-reported perceptions highlights the need for further mixed method and longitudinal studies. Lessons from the Philippines thus offer globally relevant strategies for building resilience in disaster-prone regions.
{"title":"Evolving disaster resilience in the Philippines: Insights from the 2021 and 2023 World Risk Poll on socio-economic, regional, and systemic factors","authors":"Reina Mae B. Chong , Deborah N. Tangunan , Dexter M. Toyado , Aljon Francis Koji Elegado","doi":"10.1016/j.ijdrr.2025.105415","DOIUrl":"10.1016/j.ijdrr.2025.105415","url":null,"abstract":"<div><div>The Philippines is consistently one of the world's most at-risk countries due to its location within the Pacific Ring of Fire and the “typhoon belt”. However, resilience at national and regional levels remains understudied, particularly in relation to socio-economic inequalities, gender dynamics, and governance. This study addresses this gap by analyzing resilience trends from the 2021 and 2023 World Risk Poll (WRP) Philippines dataset, focusing on the influence of gender, urbanicity, and income across individuals, households, communities, and society, using statistical and data analysis tools. Results reveal a general decline in scores, with sharp drops in Region 4B (MIMAROPA–highest resilience) and Region 7 (Central Visayas–mid-range). Conversely, Region 13 (Caraga–lowest) and Region 5 (Bicol–mid-range) improved, reflecting the success of community-based disaster risk reduction initiatives and governance. Gender disparities narrowed, with women scoring higher in household and societal resilience, while men excelled in community resilience. Urbanicity showed no significant association, although urban areas had higher individual and household resilience, while rural areas demonstrated stronger societal resilience. Income disparities persisted, with higher-income groups consistently achieving greater resilience, particularly at individual and household levels, due to better access to resources and opportunities. These findings emphasize the need for targeted, evidence-based strategies to build resilience in vulnerable regions in the Philippines, informing inclusive policies, equitable resource distribution, and governance collaboration. While the WRP provides valuable insights, reliance on self-reported perceptions highlights the need for further mixed method and longitudinal studies. Lessons from the Philippines thus offer globally relevant strategies for building resilience in disaster-prone regions.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"121 ","pages":"Article 105415"},"PeriodicalIF":4.2,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In Kerala, floods are considered as a major and most frequent hazard affecting about 14.8 % of the area and 52 % of the population being vulnerable to flood impacts. There are large differences between men and women in terms of impacts, vulnerabilities, and capacity to adapt to these challenges. Rural women are hard hit by the flood impacts especially due to constraining gender norms and high dependence on agriculture. Hence, the study aims to assess the Flood Vulnerability Index of Rural Women (FVIRW) for the selected Agro-ecological Units (AEUs) of Kerala, using the three dimensions of vulnerability viz, Adaptive capacity, Sensitivity and Exposure, under which 9 major components and 69 indicators were selected. The study was conducted in Pokkali Land and Kuttanadu AEU and was based on the primary data collected from 200 rural women through personal interviews. The developed FVIRW value indicated that rural women in both Pokkali Land (0.562) and Kuttanadu (0.551) are highly vulnerable. Probing into the dimensional values showed that Pokkali Land, had higher index value (0.679) for exposure followed by sensitivity dimension (0.671) and adaptive capacity (0.471). In case of Kuttanadu, the exposure dimension had higher value (0.687) followed by sensitivity (0.640) and adaptive capacity (0.464) dimension. In depth analysis in to the components like socio-demographic profile, livelihood strategies, socio-economic assets, water, health, and food indicated the need of urgent interventions at policy level. Hence to improve the current situation, adaptive interventions like schemes to improve the credit borrowing capacity of the women, linking women organizations to credit cooperative institutions, and mitigation interventions like conducting trainings on flood risk management and technology adoption, and insurance on assets loss can be implemented. The FVIRW developed can also be extended to other prominent flood vulnerable tracts of Kerala and other places with necessary modification.
{"title":"Flood vulnerability of rural women – An indicator-based approach","authors":"Holy Mercy Divina Matla , Christoph Funk , Pratheesh Pradeep Gopinath , Archana Raghavan Sathyan","doi":"10.1016/j.ijdrr.2025.105404","DOIUrl":"10.1016/j.ijdrr.2025.105404","url":null,"abstract":"<div><div>In Kerala, floods are considered as a major and most frequent hazard affecting about 14.8 % of the area and 52 % of the population being vulnerable to flood impacts. There are large differences between men and women in terms of impacts, vulnerabilities, and capacity to adapt to these challenges. Rural women are hard hit by the flood impacts especially due to constraining gender norms and high dependence on agriculture. Hence, the study aims to assess the Flood Vulnerability Index of Rural Women <em>(FVI</em><sup><em>RW</em></sup><em>)</em> for the selected Agro-ecological Units (AEUs) of Kerala, using the three dimensions of vulnerability <em>viz</em>, Adaptive capacity, Sensitivity and Exposure, under which 9 major components and 69 indicators were selected. The study was conducted in Pokkali Land and Kuttanadu AEU and was based on the primary data collected from 200 rural women through personal interviews. The developed <em>FVI</em><sup><em>RW</em></sup> value indicated that rural women in both Pokkali Land (0.562) and Kuttanadu (0.551) are highly vulnerable. Probing into the dimensional values showed that Pokkali Land, had higher index value (0.679) for exposure followed by sensitivity dimension (0.671) and adaptive capacity (0.471). In case of Kuttanadu, the exposure dimension had higher value (0.687) followed by sensitivity (0.640) and adaptive capacity (0.464) dimension. In depth analysis in to the components like socio-demographic profile, livelihood strategies, socio-economic assets, water, health, and food indicated the need of urgent interventions at policy level. Hence to improve the current situation, adaptive interventions like schemes to improve the credit borrowing capacity of the women, linking women organizations to credit cooperative institutions, and mitigation interventions like conducting trainings on flood risk management and technology adoption, and insurance on assets loss can be implemented. The <em>FVI</em><sup><em>RW</em></sup> developed can also be extended to other prominent flood vulnerable tracts of Kerala and other places with necessary modification.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"121 ","pages":"Article 105404"},"PeriodicalIF":4.2,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-17DOI: 10.1016/j.ijdrr.2025.105406
Yun Chen, Qiushan Li
Natural hazards disproportionately affect different regions and social demographics, leading to spatial inequality in disaster exposure. Current assessments of spatial inequality in disaster risks are shaped by the identification of hazard-bearing bodies and risk zoning methods, which are heavily influenced by scale selection and classification approaches. This study investigates the effects of these factors on identifying vulnerable populations in Less Economically Developed Regions(LEDRs), analyzing the correlation between LEDRs exposure and multiple natural hazards, including earthquakes, floods, landslides, and droughts, across provincial, urban-rural, and municipal scales. Using spatial analysis techniques, the exposure of LEDRs to individual hazards and the integrated disaster risk of Sichuan Province was calculated. The vulnerability of impoverished populations in hazard-prone areas is quantified using the Less Economically Developed Regions Exposure Bias (LEDR-EB) index. The findings indicate that: (1) Different risk classification methods significantly influence the delineation of high-risk zones, particularly for impoverished populations; (2) The LEDR-EB index varies across spatial scales. At broader scales (provincial and urban-rural levels), the exposure bias is not uniform, with urban LEDRs exhibiting a 0.24 higher compared to rural areas, indicating greater disaster exposure for impoverished urban populations. At the municipal scale, the variation in the LEDR-EB index is more obvious and shows a significant influence from the risk classification levels. This study contributes to understanding the critical role of spatial scale and hazard risk zoning in assessing disaster exposure in LEDRs, providing insights necessary for the development of equitable disaster risk reduction policies aimed at mitigating vulnerability among impoverished populations.
{"title":"Scale-dependent exposure bias: Assessing disaster risk in less economically developed regions","authors":"Yun Chen, Qiushan Li","doi":"10.1016/j.ijdrr.2025.105406","DOIUrl":"10.1016/j.ijdrr.2025.105406","url":null,"abstract":"<div><div>Natural hazards disproportionately affect different regions and social demographics, leading to spatial inequality in disaster exposure. Current assessments of spatial inequality in disaster risks are shaped by the identification of hazard-bearing bodies and risk zoning methods, which are heavily influenced by scale selection and classification approaches. This study investigates the effects of these factors on identifying vulnerable populations in Less Economically Developed Regions(LEDRs), analyzing the correlation between LEDRs exposure and multiple natural hazards, including earthquakes, floods, landslides, and droughts, across provincial, urban-rural, and municipal scales. Using spatial analysis techniques, the exposure of LEDRs to individual hazards and the integrated disaster risk of Sichuan Province was calculated. The vulnerability of impoverished populations in hazard-prone areas is quantified using the Less Economically Developed Regions Exposure Bias (LEDR-EB) index. The findings indicate that: (1) Different risk classification methods significantly influence the delineation of high-risk zones, particularly for impoverished populations; (2) The LEDR-EB index varies across spatial scales. At broader scales (provincial and urban-rural levels), the exposure bias is not uniform, with urban LEDRs exhibiting a 0.24 higher compared to rural areas, indicating greater disaster exposure for impoverished urban populations. At the municipal scale, the variation in the LEDR-EB index is more obvious and shows a significant influence from the risk classification levels. This study contributes to understanding the critical role of spatial scale and hazard risk zoning in assessing disaster exposure in LEDRs, providing insights necessary for the development of equitable disaster risk reduction policies aimed at mitigating vulnerability among impoverished populations.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"121 ","pages":"Article 105406"},"PeriodicalIF":4.2,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Twenty years after the 2004 Aceh tsunami, Banda Aceh has undergone significant urban recovery, including the development of tsunami evacuation infrastructure. However, shifts in population distribution and evacuation capacity necessitate a reassessment of tsunami evacuation risk. This study evaluates the extent to which the “Build Back Better” strategy has been realized in terms of tsunami evacuation risk reduction, considering long-term population changes and the expansion of evacuation facilities. Using WorldPop Hub data (2000–2020), we analyzed demographic changes within tsunami risk zones in Banda Aceh. While the highest-risk zone (R3) experienced a population reduction to three-quarters of its previous level, the risk-free zone (R0) saw a 6.9 percentage point increase, suggesting relocation from high-risk coastal areas. However, nearly 29 % of Banda Aceh’s population still resides in high-risk zones, highlighting persistent vulnerabilities. To assess evacuation feasibility, we conducted network-based tsunami evacuation simulations in Meuraxa, the most at-risk district, under three scenarios: (A) horizontal evacuation only, (B) using existing tsunami evacuation buildings (TEBs), and (C) using both TEBs and nearby facilities. The evacuation failure rates within the 35-min tsunami arrival time were 84.5 %, 3.1 %, and 1.1 %, respectively, indicating the remaining risks despite recovery efforts. While TEBs reduced evacuation times by over 30 min, facility capacity remained imbalanced, with some exceeding capacity tenfold. These findings highlight the need for improved evacuation facility placement and capacity to enhance future tsunami resilience.
{"title":"Tsunami evacuation risk change associated with urban recovery in Banda Aceh after 2004 Aceh tsunami","authors":"Osamu Murao , Mizuki Sato , Kazuya Sugiyasu , Hiroyuki Miura , Mufidatun Khoiriyah , Ryo Saito , Muzailin Affan","doi":"10.1016/j.ijdrr.2025.105400","DOIUrl":"10.1016/j.ijdrr.2025.105400","url":null,"abstract":"<div><div>Twenty years after the 2004 Aceh tsunami, Banda Aceh has undergone significant urban recovery, including the development of tsunami evacuation infrastructure. However, shifts in population distribution and evacuation capacity necessitate a reassessment of tsunami evacuation risk. This study evaluates the extent to which the “Build Back Better” strategy has been realized in terms of tsunami evacuation risk reduction, considering long-term population changes and the expansion of evacuation facilities. Using WorldPop Hub data (2000–2020), we analyzed demographic changes within tsunami risk zones in Banda Aceh. While the highest-risk zone (R3) experienced a population reduction to three-quarters of its previous level, the risk-free zone (R0) saw a 6.9 percentage point increase, suggesting relocation from high-risk coastal areas. However, nearly 29 % of Banda Aceh’s population still resides in high-risk zones, highlighting persistent vulnerabilities. To assess evacuation feasibility, we conducted network-based tsunami evacuation simulations in Meuraxa, the most at-risk district, under three scenarios: (A) horizontal evacuation only, (B) using existing tsunami evacuation buildings (TEBs), and (C) using both TEBs and nearby facilities. The evacuation failure rates within the 35-min tsunami arrival time were 84.5 %, 3.1 %, and 1.1 %, respectively, indicating the remaining risks despite recovery efforts. While TEBs reduced evacuation times by over 30 min, facility capacity remained imbalanced, with some exceeding capacity tenfold. These findings highlight the need for improved evacuation facility placement and capacity to enhance future tsunami resilience.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"121 ","pages":"Article 105400"},"PeriodicalIF":4.2,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-14DOI: 10.1016/j.ijdrr.2025.105377
Rima Harahap , Gerd Masselink , Sarah J. Boulton
Coastal risk analysis is important for the sustainable development and resilience of small islands. Even though there is an increasing effort to develop risk analysis at the global scale, the integration of multi-hazard, exposure, and vulnerability for outermost small islands is still rare. This study is the first to address the coastal risk on the outermost small islands of Indonesia, located at the country's territorial edge. The methodology quantifies hazard, exposure, and vulnerability variables, and collating the indices into a risk matrix. The results identify the full range of risk levels on outermost small islands represented in the island dataset, providing different approaches of addressing adaptation based on island's risk variables. Rote is identified with a Very High-risk level, while Makalehi has the highest hazard index, Bintan the highest exposure index, and Letti-Kisar the highest vulnerability index. Both coastal and geophysical hazards significantly influence risk, while economic land use impacts exposure. Infrastructure, including connectivity access and protection structures, plays a crucial role in vulnerability. The factors identified in this study, such as the highest hazard potentials, the most exposed variables, or the greatest vulnerability factors, could be used to craft policy recommendation that are designed and implemented to create island-specific adaptation strategies. In general, this study addresses a gap in current research, serving as a foundation for further investigation into coastal risk assessment. This study provides critical insights into the compounded risks faced by similarly outermost regions, offering transferable lessons for other developing archipelagic countries in enhancing their resilience.
{"title":"A coastal risk analysis for the outermost small islands of Indonesia: A multiple natural hazards approach","authors":"Rima Harahap , Gerd Masselink , Sarah J. Boulton","doi":"10.1016/j.ijdrr.2025.105377","DOIUrl":"10.1016/j.ijdrr.2025.105377","url":null,"abstract":"<div><div>Coastal risk analysis is important for the sustainable development and resilience of small islands. Even though there is an increasing effort to develop risk analysis at the global scale, the integration of multi-hazard, exposure, and vulnerability for outermost small islands is still rare. This study is the first to address the coastal risk on the outermost small islands of Indonesia, located at the country's territorial edge. The methodology quantifies hazard, exposure, and vulnerability variables, and collating the indices into a risk matrix. The results identify the full range of risk levels on outermost small islands represented in the island dataset, providing different approaches of addressing adaptation based on island's risk variables. Rote is identified with a Very High-risk level, while Makalehi has the highest hazard index, Bintan the highest exposure index, and Letti-Kisar the highest vulnerability index. Both coastal and geophysical hazards significantly influence risk, while economic land use impacts exposure. Infrastructure, including connectivity access and protection structures, plays a crucial role in vulnerability. The factors identified in this study, such as the highest hazard potentials, the most exposed variables, or the greatest vulnerability factors, could be used to craft policy recommendation that are designed and implemented to create island-specific adaptation strategies. In general, this study addresses a gap in current research, serving as a foundation for further investigation into coastal risk assessment. This study provides critical insights into the compounded risks faced by similarly outermost regions, offering transferable lessons for other developing archipelagic countries in enhancing their resilience.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"121 ","pages":"Article 105377"},"PeriodicalIF":4.2,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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