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<p>The Indian Himalayan Region is increasingly affected by flash floods and landslides, posing severe risks to mountain communities. In Gangtok city of Sikkim, evaluating these risks is critical for developing adaptive strategies and informing policy decisions. This study employs the Inherent Vulnerability and Risk Index (IVRI) framework, integrating 25 indicators across four dimensions exposure, hazard, sensitivity, and adaptive capacity using both qualitative and quantitative datasets. Principal Component Analysis (PCA) was applied to derive the Inherent Vulnerability Index (IVI) and Risk Index (RI) at the ward level, enabling spatial assessment of vulnerability and risk distribution. Results indicate that 41.17% of the area falls under very low vulnerability, nearly one-third (29.71%) under high vulnerability, and 1.22% under very high vulnerability. For the risk index (RI), 12.50% of the area remains in the very low category, while 34.48% is classified as very high risk, indicating high susceptibility to landslides and flash floods. In addition, certain hazard-exposed wards demonstrate reduced vulnerability due to stronger adaptive capacity. These findings underscore the importance of targeted mitigation strategies and provide actionable guidance for prioritizing interventions, allocating resources, and enhancing resilience. By adopting a multi-hazard perspective, this study contributes a robust framework for disaster risk reduction in rapidly urbanizing Himalayan cities.</p>

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Evaluating determinants of inherent vulnerability and risk index (IVRI) assessment of Gangtok city using PCA (Principal Component Analysis) approach

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月11日

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  • Srijana Limboo,
  • L. T. Sasang Guite,
  • Adyan Ul Haq,
  • Simran Bharti

摘要

The Indian Himalayan Region is increasingly affected by flash floods and landslides, posing severe risks to mountain communities. In Gangtok city of Sikkim, evaluating these risks is critical for developing adaptive strategies and informing policy decisions. This study employs the Inherent Vulnerability and Risk Index (IVRI) framework, integrating 25 indicators across four dimensions exposure, hazard, sensitivity, and adaptive capacity using both qualitative and quantitative datasets. Principal Component Analysis (PCA) was applied to derive the Inherent Vulnerability Index (IVI) and Risk Index (RI) at the ward level, enabling spatial assessment of vulnerability and risk distribution. Results indicate that 41.17% of the area falls under very low vulnerability, nearly one-third (29.71%) under high vulnerability, and 1.22% under very high vulnerability. For the risk index (RI), 12.50% of the area remains in the very low category, while 34.48% is classified as very high risk, indicating high susceptibility to landslides and flash floods. In addition, certain hazard-exposed wards demonstrate reduced vulnerability due to stronger adaptive capacity. These findings underscore the importance of targeted mitigation strategies and provide actionable guidance for prioritizing interventions, allocating resources, and enhancing resilience. By adopting a multi-hazard perspective, this study contributes a robust framework for disaster risk reduction in rapidly urbanizing Himalayan cities.