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Assessing vulnerability of fishermen communities in coastal Bangladesh: A “climate vulnerability index”- based study in Assasuni Upazila, Satkhira, Bangladesh 评估孟加拉国沿海渔民社区的脆弱性:基于 "气候脆弱性指数 "的孟加拉国萨特赫拉 Assasuni 乡研究
Pub Date : 2024-12-01 DOI: 10.1016/j.nhres.2023.12.018
Imtiaz Ahmed , Md. Arif Chowdhury , Rashed Uz Zzaman , Syed Labib Ul Islam , Shamsun Nahar , Sujit Kumar Roy
Climate Vulnerability Index (CVI) is developed to measure the susceptibility of communities to climate change using a case study. The index includes factors for each of the three aspects of vulnerability, including ‘Exposure’, ‘Sensitivity’, and ‘Adaptive Capability’. Sensitivity is determined by “Health”, “Food”, and “Water”, Adaptive Capability is characterized by “Socio-demographic profile,” “Livelihood strategies,” and “Social networks”, and Exposure is identified by “Natural Disaster” and “Climate Variability”. A study was conducted to investigate the vulnerability of fishermen in Assasuni Upazila, Satkhira, Bangladesh. The study involved individual surveys of randomly identified 100 fishermen from three groups: Gher-based, Ocean-based, and River-based. The findings indicate that the Gher-based fishing community exhibits higher levels of adaptive capacity (0.39), sensitivity (0.57), and exposure (0.74) in comparison to the other two communities. The sub-indicator about the migration of individuals for Gher-based livelihoods exhibits a relatively higher value of 0.85, in contrast to the relatively lower values of 0.23 and 0.11 for river and ocean-based livelihoods, respectively. The utilization of index-based output observations may aid policymakers from national to local levels in identifying and implementing the appropriate adaptation practices that prioritize the welfare of fishing communities residing in the coastal regions of Bangladesh.
{"title":"Assessing vulnerability of fishermen communities in coastal Bangladesh: A “climate vulnerability index”- based study in Assasuni Upazila, Satkhira, Bangladesh","authors":"Imtiaz Ahmed ,&nbsp;Md. Arif Chowdhury ,&nbsp;Rashed Uz Zzaman ,&nbsp;Syed Labib Ul Islam ,&nbsp;Shamsun Nahar ,&nbsp;Sujit Kumar Roy","doi":"10.1016/j.nhres.2023.12.018","DOIUrl":"10.1016/j.nhres.2023.12.018","url":null,"abstract":"<div><div>Climate Vulnerability Index (CVI) is developed to measure the susceptibility of communities to climate change using a case study. The index includes factors for each of the three aspects of vulnerability, including ‘Exposure’, ‘Sensitivity’, and ‘Adaptive Capability’. Sensitivity is determined by “Health”, “Food”, and “Water”, Adaptive Capability is characterized by “Socio-demographic profile,” “Livelihood strategies,” and “Social networks”, and Exposure is identified by “Natural Disaster” and “Climate Variability”. A study was conducted to investigate the vulnerability of fishermen in Assasuni Upazila, Satkhira, Bangladesh. The study involved individual surveys of randomly identified 100 fishermen from three groups: Gher-based, Ocean-based, and River-based. The findings indicate that the Gher-based fishing community exhibits higher levels of adaptive capacity (0.39), sensitivity (0.57), and exposure (0.74) in comparison to the other two communities. The sub-indicator about the migration of individuals for Gher-based livelihoods exhibits a relatively higher value of 0.85, in contrast to the relatively lower values of 0.23 and 0.11 for river and ocean-based livelihoods, respectively. The utilization of index-based output observations may aid policymakers from national to local levels in identifying and implementing the appropriate adaptation practices that prioritize the welfare of fishing communities residing in the coastal regions of Bangladesh.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"4 4","pages":"Pages 562-572"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139127203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Sustainable flood hazard mapping with GLOF: A Google Earth Engine approach 利用 GLOF 绘制可持续洪水灾害地图:谷歌地球引擎方法
Pub Date : 2024-12-01 DOI: 10.1016/j.nhres.2024.01.002
Subhra Halder, Suddhasil Bose
This study aims to evaluate the efficacy of Google Earth Engine (GEE) in mapping floods and their aftermath, focusing on the recent event caused by cloud burst rainfall and glacial lake outburst flood (GLOF) of Lhonak glacier lake in the Teesta River basin, North Sikkim. The objective is to utilize GEE, coupled with Sentinel-1 Synthetic Aperture Radar (SAR) data and Landsat 9 imagery, for precise remote sensing analysis, flood mapping, and Land Use and Land Cover (LULC) classification. The study employs a comprehensive methodology within the GEE platform, involving the acquisition and preprocessing of Sentinel-1 SAR data to create pre- and post-flood images. The difference between these images is calculated to generate flood maps at five-day intervals, providing a temporal evolution of the flood extent. Additionally, LULC mapping is conducted using Landsat 9 data, contributing to an understanding of pre-flood landscape characteristics. The results and discussion reveal significant impacts on various LULC types, with barren rocks, dense and medium forests, settlements, and agricultural lands experiencing notable effects. This research not only enhances our understanding of GLOFs but also serves as a critical tool for informing disaster management strategies, emphasizing the importance of accurate hazard assessment and the need for holistic approaches to mitigate the cascading effects of such events.
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引用次数: 0
Irshalwadi landslide in Western Ghats of India: Observations from precursory slope movement, rainfall and soil moisture 印度西高止山的 Irshalwadi 滑坡:前坡运动、降雨和土壤湿度观测结果
Pub Date : 2024-12-01 DOI: 10.1016/j.nhres.2024.01.004
Nirmala Jain, Priyom Roy, Punit Jalan, Tapas R. Martha, Iswar C. Das
The Western Ghats of India, a UNESCO world heritage site, is gradually becoming a hotspot for catastrophic landslides. On July 19, 2023, the entire Irshalwadi village in the Raigad district of Maharashtra, India, was obliterated due to a single catastrophic landslide. Of the 228 residents of the village, the landslide killed 27 people and 57 are still reported to be missing. The landslide occurred on a slope which exhibited no visual precedence of disturbance or creep. However, analysis of potential precursory movements prior to slope failure using the Persistent Scatterer Interferometry (PSI) technique reveals active movement near the base of the slope (in order of ∼12 ​mm/y). Sentinel-2 satellite imagery acquired post-event characterises the landslide as a bifurcated debris flow possibly triggered by heavy rainfall in the region. Peak cumulative rainfall, estimated by the Indian Meteorological Department (IMD), was observed in this region on 17, 18 and July 19, 2023 (∼500) mm and was the highest recorded rainfall in the region during the given period. This caused significant water percolation into the porous basaltic soil, leading to increased soil moisture, as supported by the Soil Moisture Active Passive (SMAP) data. The resultant increase in pore pressure caused the slope material to fail and eventually trigger the landslide.
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引用次数: 0
The role of large language models (AI chatbots) in fire engineering: An examination of technical questions against domain knowledge
Pub Date : 2024-12-01 DOI: 10.1016/j.nhres.2024.06.003
Haley Hostetter , M.Z. Naser , Xinyan Huang , John Gales
This communication presents a short review of chatbot technology and preliminary findings from comparing two recent chatbots, OpenAI’s ChatGPT and Google’s Bard, in the context of fire engineering by evaluating their responses in handling fire safety-related queries. A diverse range of fire engineering questions and scenarios were created and examined, including structural fire design, fire prevention strategies, evacuation, building code compliance, and fire suppression systems. The results reveal some key differences in the performance of the chatbots, with ChatGPT demonstrating a relatively superior performance of 88% (vs. 80% for Bard). Then, this communication highlights the potential for chatbot technology to revolutionize fire engineering practices by providing instant access to critical information while outlining areas for further improvement and research. Evidently, and when it matures, this technology will likely be elemental to our engineers’ practice and education.
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引用次数: 0
Disaster, risk and crises in tourism and hospitality field: A pathway toward tourism and hospitality management framework for resilience and recovery process
Pub Date : 2024-12-01 DOI: 10.1016/j.nhres.2024.06.001
Li-Wei Liu , Pahrudin Pahrudin , Cheng-Yu Tsai , Lee Hao
This study aims to review the documents in disasters, risk and crises to produce a generic model for developing a holistic framework in the tourism and hospitality industry. This study uses bibliometric analysis and a systematic narrative review of 795 documents from the Web of Science and Scopus databases to determine the number of publications, top authors, top cited documents, top journals, regional distribution, mapping topic trends, the structure of disasters, risk and crises, and the type of disasters, risk and crises. The results find some issues in the disaster and crises such as crises management, resilience, and recovery from disasters, risk, and crises in the tourism and hospitality industry. This study presents a comprehensive framework for tourism and hospitality resilience and recovery process after a disasters and crises.
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引用次数: 0
Unravelling Bangalore's air quality during the second wave: Multifaceted analysis of COVID-19 lockdown impact 揭开班加罗尔第二波空气质量的神秘面纱:对 COVID-19 封锁影响的多方面分析
Pub Date : 2024-12-01 DOI: 10.1016/j.nhres.2024.01.008
Iranna Gogeri , Krushna Chandra Gouda , Aruna Singanahalli ThippaReddy
This study assesses the impact of the second wave COVID-19 lockdown (March–June 2021) on air pollution levels in Bangalore, India, using real-time data from eight CPCB monitoring stations across the city. This research endeavours to dissect the multifaceted impact of the 2021 ​s wave COVID-19 lockdown on Bangalore's air quality. Leveraging real-time data sourced from eight CPCB monitoring stations across the city, the study meticulously delves into diverse analyses to grasp the nuanced implications of the lockdown measures. It scrutinizes changes in six major pollutants: PM2.5, PM10, CO, NO2, SO2, and O3 during the 2021 lockdown compared to the same period in 2020. The comprehensive studies of different temporal scales were examined such as daily, weekly, and seasonal. The daily and weekly averages were computed to assess the percentage change in air pollutant concentrations during the March to June 2021 lockdown and pre-lockdown phases. The seasonal averages were derived to capture trends in seasonal variations. The examination of air pollution disparities across the city's eight monitoring stations (ST1 to ST8), unravelling localized variations and comprehending the spatial intricacies influencing air quality levels within Bangalore. The comparison of air pollution concentrations between the 2021 and 2020 lockdown periods, offering insights into relative changes in pollutant levels. The concentrations during the 2021 lockdown period (April 27 to June 14) significantly dropped compared to the pre-lockdown phase (March 9 to April 26) by considerable percentages across various pollutants: PM2.5 (45 %), PM10 (49 %), O3 (37 %), NO2 (41 %), SO2 (5 %), and CO (30 %). The comparative evaluation between air pollutant intensity changes during the common lockdown periods of the first wave (2020) and the second wave (2021) of COVID-19. This contiguity illuminates the shifts in pollution levels and underscores the differing dynamics of air quality between these distinct phases. This research provides comprehensive insights into air quality over Bangalore city during the second wave lockdown. The multifaceted analyses offer a detailed understanding of temporal, spatial, and comparative facets of air pollution dynamics, shedding light on the significant impact of COVID-19 restrictions on urban air quality.
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引用次数: 0
Susceptibility analysis of glacier debris flow by investigating glacier changes based on remote sensing imagery and deep learning: A case study 通过调查基于遥感图像和深度学习的冰川变化,分析冰川泥石流的易感性:案例研究
Pub Date : 2024-12-01 DOI: 10.1016/j.nhres.2023.12.013
Shiying Yang , Gang Mei , Yuan Zhang
Glacier debris flow is becoming increasingly severe as global warming intensifies. To minimize the catastrophic losses caused by glacier debris flow, it is essential to analyze the susceptibility of glacier debris flow. In this study, we employed remote sensing with deep learning methods to investigate glaciers changes, evaluating the susceptibility of glacier debris flow in Zelongnong ravine, Southeast Tibet. First, we utilized Landsat optical remote sensing imageries to obtain the semantic segmentation dataset and trained a deep learning model to automatically extract the glacier boundary in Zelongnong ravine. Second, by pre-processing the DEMs (Digital Elevation Model) and integrating them with the glacial boundaries, the volume of glacier ablation was measured. Eventually, according to the glacier ablation, the correction coefficient was determined, which modified the geomorphic information entropy theory, and further analyzed the susceptibility of glacier debris flow in Zelongnong ravine. The research results of the study present that the evaluation indices of the deep learning model that extracted glacier boundaries are over 90%. Moreover, the study results confirm the accuracy of the modified susceptibility evaluation method for glacier debris flows, and the susceptibility of glacier debris flows in Zelongnong ravine generally ranges between high and very high. This study reveals the feasibility and progress of using remote sensing and deep learning in glacier boundary extraction, providing a promising reference for the evaluation of the susceptibility and prediction of glacier debris flow in similar high mountainous areas as well.
{"title":"Susceptibility analysis of glacier debris flow by investigating glacier changes based on remote sensing imagery and deep learning: A case study","authors":"Shiying Yang ,&nbsp;Gang Mei ,&nbsp;Yuan Zhang","doi":"10.1016/j.nhres.2023.12.013","DOIUrl":"10.1016/j.nhres.2023.12.013","url":null,"abstract":"<div><div>Glacier debris flow is becoming increasingly severe as global warming intensifies. To minimize the catastrophic losses caused by glacier debris flow, it is essential to analyze the susceptibility of glacier debris flow. In this study, we employed remote sensing with deep learning methods to investigate glaciers changes, evaluating the susceptibility of glacier debris flow in Zelongnong ravine, Southeast Tibet. First, we utilized Landsat optical remote sensing imageries to obtain the semantic segmentation dataset and trained a deep learning model to automatically extract the glacier boundary in Zelongnong ravine. Second, by pre-processing the DEMs (Digital Elevation Model) and integrating them with the glacial boundaries, the volume of glacier ablation was measured. Eventually, according to the glacier ablation, the correction coefficient was determined, which modified the geomorphic information entropy theory, and further analyzed the susceptibility of glacier debris flow in Zelongnong ravine. The research results of the study present that the evaluation indices of the deep learning model that extracted glacier boundaries are over 90%. Moreover, the study results confirm the accuracy of the modified susceptibility evaluation method for glacier debris flows, and the susceptibility of glacier debris flows in Zelongnong ravine generally ranges between high and very high. This study reveals the feasibility and progress of using remote sensing and deep learning in glacier boundary extraction, providing a promising reference for the evaluation of the susceptibility and prediction of glacier debris flow in similar high mountainous areas as well.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"4 4","pages":"Pages 539-549"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139014988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The aspects of food security and subsistence systems of climate-induced Hazards affected coastal people in the era of the COVID-19 pandemic in Bangladesh 孟加拉国 COVID-19 大流行时期受气候灾害影响的沿海居民的粮食安全和生计系统问题
Pub Date : 2024-12-01 DOI: 10.1016/j.nhres.2024.04.002
Joydeb Garai
Climate change-induced hazards and environmental change pose great threats and vulnerabilities to the livelihoods and food security of forest-dependent coastal people in Bangladesh. Moreover, the recent surge of COVID-19 has aggravated this vulnerability manifold. This paper is an attempt to examine the aspects of food security and subsistence systems of coastal people in dual hazards. It also explores the gender roles and responses of coastal people in food security and subsistence systems in climatic hazards during the period of COVID-19. This project employed participant observation, in-depth interviews (N ​= ​55), and Focus Group Discussions (FGDs) (N ​= ​7) for collecting data. The findings of the research demonstrate that climate-induced hazards severely reduce the resources of the forest and river and threaten the food security of coastal people. Many of the coastal people are forced to change their occupations, diversify their livelihoods, or migrate to other places for subsistence. Moreover, the recent outbreak of COVID-19 restricts them in-house and stops their income-generating activities. In addition, forest departments do not allow them to enter forests to collect forest resources during and after the hazards, which severely affects their food security. In coastal areas, women play a great role in food security and subsistence systems, but dual hazards limit their working opportunities by restricting agricultural inputs, and technological support, disrupting the environment, closing markets, breaking supply chains, and so on. However, coastal people try to overcome these challenges by applying their local strategies. This paper helps policymakers and the government to gain insight into the real situation of coastal people during and after the hazards, which can influence policymakers to formulate effective policies for ensuring food security and creating alternative subsistence systems for coastal people in adversity.
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引用次数: 0
Cultural adaptation in the era of climate change: An ethnographic study on the resilience of indigenous people at Chittagong Hill Tracts area in Bangladesh
Pub Date : 2024-12-01 DOI: 10.1016/j.nhres.2024.05.002
Joydeb Garai , Hok Bun Ku
Climate change has gained global recognition as one of the most urgent challenges in recent decades. Many indigenous people attempt to overcome great challenges in their lives by adhering to their cultural customs and traditional knowledge. This is especially true for those who live in isolated, hilly places and are dependent on natural resources. The aim of the paper is to critically investigate the cultural facets of indigenous people's adaptation to and resilience to climate change in the Chittagong Hill Tracts (CHT), namely in the Rangamati Sadar sub-districts of the Rangamati districts, in Bangladesh. This paper also examines how cultural components in indigenous community are changing and influencing the adaptation process in adverse situations. This study used a critical ethnography technique in conjunction with participant observation, in-depth interviews (N ​= ​55), and focus group discussions (N ​= ​5, 45 participants) during a one-year period (October 2019 to October 2020). According to the study's findings, climate change-related risks have significant adverse effects on indigenous people. However, they develop their strategies to adjust to the adverse environment, like building different kinds of houses, changing cultural customs, relying less on natural resources, and adhering to their indigenous knowledge. They also strengthen their prayers and ceremonial practices, which reinforce their communal ties and allow them to become more resilient against challenges in their community. The popular belief that Indigenous people are stupid, poor, and helpless while they wait for outside help is challenged by this study. It also refutes the discourse that indigenous strategies and knowledge are not undervalued and can be an effective instrument for the adaptation process and combating hazards.
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引用次数: 0
Quantifying the riverbank erosion and accretion rate using DSAS model study from the lower Ganga River, India 利用 DSAS 模型对印度恒河下游河岸侵蚀和增生率进行量化研究
Pub Date : 2024-12-01 DOI: 10.1016/j.nhres.2023.12.015
Md Hasanuzzaman , Aznarul Islam , Biswajit Bera , Pravat Kumar Shit
Assessing the erosion and accretion (EA) rate of the lower Ganga River in India is crucial for scientific planning and implementing development activities in river basin management. The current study utilized the digital shoreline analysis system (DSAS model) to measure the erosion and accretion rate from 1972 to 2022. The objective was to quantify the spatiotemporal variation of erosion vulnerability and project future trends at the village level to support different developmental programs. Satellite images and field survey data were employed to analyze the EA rates. The results indicated a significantly higher average erosion rate of 0.0583 ​km/year on the left banks compared to the right bank in the study area. The net shoreline movement (NSM) analysis demonstrated that erosion on the left bank occurred at an average distance of approximately 2.91 ​km, which was twice as high as the erosion on the right bank. Furthermore, the findings suggested a consistent trend of increasing erosion rates that are projected to continue until 2042. It is noteworthy that the study identified a majority of highly erosional villages (92.86% of the villages) located on the left bank of the river, particularly upstream from the Farakka barrage. The DSAS model underwent validation using RMSE, T-test, ROC, and R2 techniques, confirming its acceptance with satisfactory results. In summary, this research introduces a new technique and framework for accurately measuring EA rates and making future predictions for management projects.
{"title":"Quantifying the riverbank erosion and accretion rate using DSAS model study from the lower Ganga River, India","authors":"Md Hasanuzzaman ,&nbsp;Aznarul Islam ,&nbsp;Biswajit Bera ,&nbsp;Pravat Kumar Shit","doi":"10.1016/j.nhres.2023.12.015","DOIUrl":"10.1016/j.nhres.2023.12.015","url":null,"abstract":"<div><div>Assessing the erosion and accretion (EA) rate of the lower Ganga River in India is crucial for scientific planning and implementing development activities in river basin management. The current study utilized the digital shoreline analysis system (DSAS model) to measure the erosion and accretion rate from 1972 to 2022. The objective was to quantify the spatiotemporal variation of erosion vulnerability and project future trends at the village level to support different developmental programs. Satellite images and field survey data were employed to analyze the EA rates. The results indicated a significantly higher average erosion rate of 0.0583 ​km/year on the left banks compared to the right bank in the study area. The net shoreline movement (NSM) analysis demonstrated that erosion on the left bank occurred at an average distance of approximately 2.91 ​km, which was twice as high as the erosion on the right bank. Furthermore, the findings suggested a consistent trend of increasing erosion rates that are projected to continue until 2042. It is noteworthy that the study identified a majority of highly erosional villages (92.86% of the villages) located on the left bank of the river, particularly upstream from the Farakka barrage. The DSAS model underwent validation using RMSE, T-test, ROC, and R2 techniques, confirming its acceptance with satisfactory results. In summary, this research introduces a new technique and framework for accurately measuring EA rates and making future predictions for management projects.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"4 4","pages":"Pages 550-561"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139192072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
期刊
Natural Hazards Research
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