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<p>This study aims to assess the multidimensional vulnerabilities of climate-stressed communities in Khulna and Satkhira districts by integrating the Livelihood Vulnerability Index based on the Intergovernmental Panel on Climate Change framework (<i>LVI-IPCC</i>) and Climate Vulnerability Index (<i>CVI</i>) with empirical climate data and household perceptions. It focuses on how vulnerability components (exposure, sensitivity, and adaptive capacity) vary across communities, and how socioeconomic factors shape household-level vulnerability. Data were collected through a structured household survey (<i>n</i> = 426), complemented by climate trend analysis (1982–2022) and binary logistic regression to identify predictors of climate knowledge. The results show that Protapnagar (LVI-IPCC: 0.256; CVI: 0.682) is the most vulnerable due to poor infrastructure and reliance on climate-sensitive livelihoods, whereas Koyra Sadar (LVI-IPCC: 0.133; CVI: 0.585) has lower vulnerability, supported by diversified income sources. Level of education and income are likely to influence knowledge of climate change. While community perceptions generally align with observed climate trends, notable mismatches were reported in Satkhira. These findings highlight that effective adaptation must address both structural sensitivity and community knowledge gaps. This study offers a robust framework for localized adaptation planning and recommends strategies combining scientific data, social realities, and community insights to build resilience in coastal areas.</p>

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Vulnerability of climate-stressed communities in coastal Bangladesh: a multi-dimensional index-based assessment

  • 期刊论文

  • 发表日期：

    2025年10月17日

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  • Borshon Bhattacharjee,
  • Bivuti Bhushan Sikder,
  • Tasneem Chowdhury Fahim

摘要

This study aims to assess the multidimensional vulnerabilities of climate-stressed communities in Khulna and Satkhira districts by integrating the Livelihood Vulnerability Index based on the Intergovernmental Panel on Climate Change framework (LVI-IPCC) and Climate Vulnerability Index (CVI) with empirical climate data and household perceptions. It focuses on how vulnerability components (exposure, sensitivity, and adaptive capacity) vary across communities, and how socioeconomic factors shape household-level vulnerability. Data were collected through a structured household survey (n = 426), complemented by climate trend analysis (1982–2022) and binary logistic regression to identify predictors of climate knowledge. The results show that Protapnagar (LVI-IPCC: 0.256; CVI: 0.682) is the most vulnerable due to poor infrastructure and reliance on climate-sensitive livelihoods, whereas Koyra Sadar (LVI-IPCC: 0.133; CVI: 0.585) has lower vulnerability, supported by diversified income sources. Level of education and income are likely to influence knowledge of climate change. While community perceptions generally align with observed climate trends, notable mismatches were reported in Satkhira. These findings highlight that effective adaptation must address both structural sensitivity and community knowledge gaps. This study offers a robust framework for localized adaptation planning and recommends strategies combining scientific data, social realities, and community insights to build resilience in coastal areas.