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<p>Water poverty remains a pressing challenge in Nepal, where climate change, population growth, and rapid development exacerbate both scarcity and excess of safe water. Addressing this requires a systematic understanding of the socio-economic and environmental dimensions influencing water access. The present study attempted to study spatial variation in multi-dimensional water poverty employing multi-model approach utilizing multi-dimensional water poverty index (MWPI). Principal Component Analysis (PCA), Analytical Hierarchy Process (AHP), Shannon Entropy, and Equal Weight methods were employed to assess spatial variation in water poverty, while the Getis-Ord Gi* statistic was used to identify hotspots and cold spots. The findings reveal that areas under high to very high water poverty range from 39% to 46%, with PCA estimating 39.88%, Entropy 45.67%, Equal Weight 45.88%, and AHP 43.11%. A major hotspot with 99% confidence was identified in the northwestern region, whereas cold spots appeared in the northeastern region (95% confidence) and in central Nepal (99% confidence under entropy). Influential drivers varied across models, with resource and access dominating in PCA, access and capacity in Entropy, and resource and environment in AHP. Strong correlations (<i>r</i> &gt; 0.70) were observed between PCA &amp; AHP and Entropy &amp; Equal Weight approaches, demonstrating methodological consistency. The findings highlight that despite Nepal’s abundant water resources, accessibility and community capacity remain critical barriers. The study recommends targeted interventions in hotspot regions to strengthen access and capacity, offering valuable insights for sustainable water resource management and policymaking.</p>

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A multi-model approach to analyse multidimensional water poverty index in nepal: implications for sustainable water resource management

  • 期刊论文

  • 发表日期：

    2025年10月27日

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  • Shiva Kant Dube,
  • Lucky Sharma,
  • Narendra Kumar Rana,
  • Srabani Sanyal

摘要

Water poverty remains a pressing challenge in Nepal, where climate change, population growth, and rapid development exacerbate both scarcity and excess of safe water. Addressing this requires a systematic understanding of the socio-economic and environmental dimensions influencing water access. The present study attempted to study spatial variation in multi-dimensional water poverty employing multi-model approach utilizing multi-dimensional water poverty index (MWPI). Principal Component Analysis (PCA), Analytical Hierarchy Process (AHP), Shannon Entropy, and Equal Weight methods were employed to assess spatial variation in water poverty, while the Getis-Ord Gi* statistic was used to identify hotspots and cold spots. The findings reveal that areas under high to very high water poverty range from 39% to 46%, with PCA estimating 39.88%, Entropy 45.67%, Equal Weight 45.88%, and AHP 43.11%. A major hotspot with 99% confidence was identified in the northwestern region, whereas cold spots appeared in the northeastern region (95% confidence) and in central Nepal (99% confidence under entropy). Influential drivers varied across models, with resource and access dominating in PCA, access and capacity in Entropy, and resource and environment in AHP. Strong correlations (r > 0.70) were observed between PCA & AHP and Entropy & Equal Weight approaches, demonstrating methodological consistency. The findings highlight that despite Nepal’s abundant water resources, accessibility and community capacity remain critical barriers. The study recommends targeted interventions in hotspot regions to strengthen access and capacity, offering valuable insights for sustainable water resource management and policymaking.