Scholarlink

<p>Droughts in India, a monsoon-dominated country, pose critical threats to water security, agriculture, and livelihoods. This study presents a long-term (1902–2013) assessment of evolving drought characteristics by utilizing Ensemble Empirical Mode Decomposition (EEMD) to extract non-linear trends from both the Non-stationary Standardized Precipitation Index (NSPI) and conventional SPI. NSPI adapts to the changing mean and variance of the Indian Summer Monsoon, offering a dynamic baseline benchmarked against the stationary SPI. While SPI frequently misclassified recent drought events due to its stationary assumption, NSPI demonstrated superior drought detection skill, achieving significantly higher correlations with internal drought signals (e.g., Pearson <i>r</i> = 0.31 versus 0.19 in Tropical Wet and Dry zone) and robust event capture (F1-scores &gt; 0.70 in Semi-Arid zones) where stationary metrics failed. Non-linear trend analysis exposed a statistically significant ~ 61 and ~ 62% post-1950s rise in the intrinsic drought duration and severity, respectively, reflecting a structural reorganization of monsoon dynamics where increasing rainfall variability drives a resurgence in severe, persistent droughts. Spatially, northwestern, western, and eastern India are experiencing shorter but more intense droughts, while central and southern regions face longer, milder episodes. With intensifying extremes in Semi-Arid and Humid Subtropical zones, and rising frequency in Tropical Wet and Tropical Wet and Dry zones, approximately 70% of India’s population is exposed to these intensifying drought hazards, carrying significant socioeconomic risks including cereal yield losses of ~ 9–14%. These divergent regional trajectories thereby supports the consideration of non-stationary frameworks for adaptive planning, illustrating that stationary metrics fail to capture evolving drought regimes and their associated agricultural risks under a changing monsoon system.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Spatiotemporal reorganization of drought characteristics across India under changing monsoon variability

  • 期刊论文

  • 发表日期：

    2026年3月13日

查看全文
  • Debankana Bhattacharjee,
  • Vinnarasi Rajendran,
  • Chandrika Thulaseedharan Dhanya

摘要

Droughts in India, a monsoon-dominated country, pose critical threats to water security, agriculture, and livelihoods. This study presents a long-term (1902–2013) assessment of evolving drought characteristics by utilizing Ensemble Empirical Mode Decomposition (EEMD) to extract non-linear trends from both the Non-stationary Standardized Precipitation Index (NSPI) and conventional SPI. NSPI adapts to the changing mean and variance of the Indian Summer Monsoon, offering a dynamic baseline benchmarked against the stationary SPI. While SPI frequently misclassified recent drought events due to its stationary assumption, NSPI demonstrated superior drought detection skill, achieving significantly higher correlations with internal drought signals (e.g., Pearson r = 0.31 versus 0.19 in Tropical Wet and Dry zone) and robust event capture (F1-scores > 0.70 in Semi-Arid zones) where stationary metrics failed. Non-linear trend analysis exposed a statistically significant ~ 61 and ~ 62% post-1950s rise in the intrinsic drought duration and severity, respectively, reflecting a structural reorganization of monsoon dynamics where increasing rainfall variability drives a resurgence in severe, persistent droughts. Spatially, northwestern, western, and eastern India are experiencing shorter but more intense droughts, while central and southern regions face longer, milder episodes. With intensifying extremes in Semi-Arid and Humid Subtropical zones, and rising frequency in Tropical Wet and Tropical Wet and Dry zones, approximately 70% of India’s population is exposed to these intensifying drought hazards, carrying significant socioeconomic risks including cereal yield losses of ~ 9–14%. These divergent regional trajectories thereby supports the consideration of non-stationary frameworks for adaptive planning, illustrating that stationary metrics fail to capture evolving drought regimes and their associated agricultural risks under a changing monsoon system.