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<p>Climate change poses growing risks to ecologically fragile and socio-economically vulnerable regions such as Meghalaya in the Indian Himalayan Region. This study aims to assess and compare district-level climate vulnerability in Meghalaya using an indicator-based framework aligned with the IPCC’s AR5 conceptualization. The primary objective is to identify key drivers of vulnerability and provide spatially explicit insights to inform adaptation planning. The analysis uses eight indicators representing both biophysical and socio-economic dimensions, slope gradient, forest cover, crop yield variability, population density, female literacy, infant mortality, Multidimensional Poverty Index (MPI), and NREGS man-days, derived from official government sources for the period 2020–2024. Data were normalized according to their functional relationships with vulnerability, and unequal indicator weights were assigned through expert consultation. Composite Vulnerability Indices (CVI) were generated to rank districts, supported by GIS-based spatial analysis and attribution of indicator contributions. Results reveal that West Khasi Hills and East Garo Hills are the most vulnerable districts, primarily due to steep slopes, forest degradation, and high poverty levels. Conversely, East Jaintia Hills and South West Khasi Hills exhibit lower vulnerability owing to stronger adaptive capacities. The study concludes that enhancing forest conservation, livelihood diversification, and social protection mechanisms is critical for reducing vulnerability in high-risk districts. This framework offers a replicable approach for rapid vulnerability assessment in data-scarce mountainous regions.</p>

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District-level climate vulnerability assessment in Meghalaya using an IPCC AR5 framework

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月27日

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  • Vivek Lyngdoh,
  • Marbakor Mary Lynrah,
  • Evenstone Wahlang,
  • Amica L. Nongrang,
  • Nivanaliza Wahlang,
  • Albert Chiang,
  • Joram Beda

摘要

Climate change poses growing risks to ecologically fragile and socio-economically vulnerable regions such as Meghalaya in the Indian Himalayan Region. This study aims to assess and compare district-level climate vulnerability in Meghalaya using an indicator-based framework aligned with the IPCC’s AR5 conceptualization. The primary objective is to identify key drivers of vulnerability and provide spatially explicit insights to inform adaptation planning. The analysis uses eight indicators representing both biophysical and socio-economic dimensions, slope gradient, forest cover, crop yield variability, population density, female literacy, infant mortality, Multidimensional Poverty Index (MPI), and NREGS man-days, derived from official government sources for the period 2020–2024. Data were normalized according to their functional relationships with vulnerability, and unequal indicator weights were assigned through expert consultation. Composite Vulnerability Indices (CVI) were generated to rank districts, supported by GIS-based spatial analysis and attribution of indicator contributions. Results reveal that West Khasi Hills and East Garo Hills are the most vulnerable districts, primarily due to steep slopes, forest degradation, and high poverty levels. Conversely, East Jaintia Hills and South West Khasi Hills exhibit lower vulnerability owing to stronger adaptive capacities. The study concludes that enhancing forest conservation, livelihood diversification, and social protection mechanisms is critical for reducing vulnerability in high-risk districts. This framework offers a replicable approach for rapid vulnerability assessment in data-scarce mountainous regions.