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<p>Rainfall variability has a significant influence on agricultural production and water-resource management in Bihar, one of India's most climate-sensitive regions. This study evaluated the spatial and temporal behaviour of seasonal and annual rainfall across 38 districts of Bihar during 1990–2019 and observed rainfall trends, spatial regionalization, and large-scale climatic teleconnections. The results discovered considerable spatial variability in rainfall distribution across the state. Rainfall anomalies showed progressively recurrent below-normal circumstances during winter, monsoon, post-monsoon, and annual periods, predominantly during 2000–2009 and 2010–2019, however, pre-monsoon rainfall unveiled increasing tendencies. This was further confirmed by identifying significant (<i>p</i> &lt; 0.05) decreasing or increasing trends in the aforementioned seasons using Mann–Kendall (MK), modified MK test (mMK), Sen’s slope estimator, and innovative trend analysis (ITA) methods. The strongest declines were detected in eastern, northeastern, and southeastern districts, mostly within Agro-Climatic Zones I, II, and IIIa. Spatial regionalization recognized five distinct clusters of districts showing alike rainfall-trend behaviour, displaying coherent hydroclimatic patterns across Bihar. Assessment of trend detection methods showed that ITA detected additional (72%) hidden time series trends that were not consistently identified by traditional methods, particularly in rainfall series showing non-monotonic characteristics. Teleconnection analysis using large scale oceanic indices, particularly Niño 3.4, ONI, ENSO, and DMI, further confirmed season-specific association between seasonal/annual rainfall and large-scale ocean–atmosphere variability, employing notable stimuli on monsoon and annual rainfall variability. In general, the study delivers an integrated evaluation of changes in rainfall climatology, trend behaviour, spatial clustering, and climatic drivers across Bihar. The findings improve understanding of regional hydroclimatic change and offer a scientific base for preparing water-resource management and climate-resilient agricultural adaptation policies in vulnerable districts.</p>

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Assessing spatio-temporal trends, teleconnections and clustering of long-term seasonal rainfall of Bihar using innovative trend analysis & multivariate techniques

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月29日

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  • Koushik Banerjee,
  • K. G. Mandal,
  • Bappa Das,
  • S. K. Purbey,
  • V. S. Meena,
  • Shreya Nivesh,
  • Vikas Paradkar,
  • Ravi Kumar,
  • S. K. Samal

摘要

Rainfall variability has a significant influence on agricultural production and water-resource management in Bihar, one of India's most climate-sensitive regions. This study evaluated the spatial and temporal behaviour of seasonal and annual rainfall across 38 districts of Bihar during 1990–2019 and observed rainfall trends, spatial regionalization, and large-scale climatic teleconnections. The results discovered considerable spatial variability in rainfall distribution across the state. Rainfall anomalies showed progressively recurrent below-normal circumstances during winter, monsoon, post-monsoon, and annual periods, predominantly during 2000–2009 and 2010–2019, however, pre-monsoon rainfall unveiled increasing tendencies. This was further confirmed by identifying significant (p < 0.05) decreasing or increasing trends in the aforementioned seasons using Mann–Kendall (MK), modified MK test (mMK), Sen’s slope estimator, and innovative trend analysis (ITA) methods. The strongest declines were detected in eastern, northeastern, and southeastern districts, mostly within Agro-Climatic Zones I, II, and IIIa. Spatial regionalization recognized five distinct clusters of districts showing alike rainfall-trend behaviour, displaying coherent hydroclimatic patterns across Bihar. Assessment of trend detection methods showed that ITA detected additional (72%) hidden time series trends that were not consistently identified by traditional methods, particularly in rainfall series showing non-monotonic characteristics. Teleconnection analysis using large scale oceanic indices, particularly Niño 3.4, ONI, ENSO, and DMI, further confirmed season-specific association between seasonal/annual rainfall and large-scale ocean–atmosphere variability, employing notable stimuli on monsoon and annual rainfall variability. In general, the study delivers an integrated evaluation of changes in rainfall climatology, trend behaviour, spatial clustering, and climatic drivers across Bihar. The findings improve understanding of regional hydroclimatic change and offer a scientific base for preparing water-resource management and climate-resilient agricultural adaptation policies in vulnerable districts.