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<p>Analyzing rainfall patterns over long periods is crucial to understand the impacts of climate change on water resources and agriculture. In this study, monthly, seasonal and annual rainfall trends in mainland agro-climatic zones (ACZs) of India were analyzed using gridded rainfall data for the period 1901–2022. Trend analysis was carried out using a combination of classical statistical methods, including the Mann–Kendall (MK) test, modified Mann–Kendall (m-MK) test, and Sen’s slope estimator, along with innovative graphical approaches such as Innovative Trend Analysis (ITA) and Innovative Polygon Trend Analysis (IPTA). While the classical methods were applied to assess monthly, seasonal and annual trends, IPTA was used to examine monthly transitions in rainfall behavior. Results indicate that winter rainfall shows predominantly decreasing trends across most ACZs, except WHR, where increasing tendencies were observed. Monsoon, post-monsoon, and annual rainfall exhibited significant decline in most of the north (UGP, MGP), central (CPH), and eastern parts (EHR), while in western (GPH, WDR, TGP) and southern parts (ECP, SPH) increasing rainfall trends were observed. The MK and m-MK identified trends in 16.7% of the monthly data and 41% of seasonal rainfall data. The graphical IPTA was able to detect trends in 72% of the monthly rainfall time-series. In contrast, ITA identified significant trends in all analyzed rainfall time series, highlighting its sensitivity in detecting subtle variations. The direction of significant trends was consistent across all the methods. This integrated assessment of rainfall variability across India supports climate-informed agricultural decision making.</p>

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Comparative analysis of spatio-temporal rainfall patterns in the agro-climatic zones of India

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月28日

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  • Sonam Sah,
  • RN Singh,
  • B. Das,
  • Santosha Rathod,
  • Lata Vishnoi,
  • A. K. Singh,
  • Yogeshwar Singh,
  • K. S. Reddy

摘要

Analyzing rainfall patterns over long periods is crucial to understand the impacts of climate change on water resources and agriculture. In this study, monthly, seasonal and annual rainfall trends in mainland agro-climatic zones (ACZs) of India were analyzed using gridded rainfall data for the period 1901–2022. Trend analysis was carried out using a combination of classical statistical methods, including the Mann–Kendall (MK) test, modified Mann–Kendall (m-MK) test, and Sen’s slope estimator, along with innovative graphical approaches such as Innovative Trend Analysis (ITA) and Innovative Polygon Trend Analysis (IPTA). While the classical methods were applied to assess monthly, seasonal and annual trends, IPTA was used to examine monthly transitions in rainfall behavior. Results indicate that winter rainfall shows predominantly decreasing trends across most ACZs, except WHR, where increasing tendencies were observed. Monsoon, post-monsoon, and annual rainfall exhibited significant decline in most of the north (UGP, MGP), central (CPH), and eastern parts (EHR), while in western (GPH, WDR, TGP) and southern parts (ECP, SPH) increasing rainfall trends were observed. The MK and m-MK identified trends in 16.7% of the monthly data and 41% of seasonal rainfall data. The graphical IPTA was able to detect trends in 72% of the monthly rainfall time-series. In contrast, ITA identified significant trends in all analyzed rainfall time series, highlighting its sensitivity in detecting subtle variations. The direction of significant trends was consistent across all the methods. This integrated assessment of rainfall variability across India supports climate-informed agricultural decision making.