Spatio-temporal trends of rainfall during the last 119 years (1901 to 2019) in different meteorological sub-divisions of India were analyzed using gridded rainfall data. Innovative trend analysis (ITA) was performed for detecting the trends in seasonal and annual rainfall. The results of long-term trends and their magnitudes obtained from the ITA method were compared with traditional Mann-Kendall (M-K), modified Mann-Kendall (mM-K), and linear regression analysis (LRA) methods. Significant trends in seasonal and annual rainfall were detected in almost all the sub-divisions of India. The monsoon and annual rainfall showed increasing trends in most sub-divisions of the peninsular and northwest India, whereas decreasing trends were observed in the central northeast part of the country. Winter rainfall showed decreasing trends in most of the sub-divisions of the country. Results of M-K/mM-K and LRA concurred with the trends detected by ITA. However, the ITA is more sensitive in detecting hidden trends missed out by the traditional M-K/mM-K and LRA tests. This study will provide scientific reference for assessment and proactive mitigation of climate change impacts on water resources to manage the risk of climate variability.

使用网格降雨数据分析了印度不同气象分区过去 119 年（1901 至 2019 年）降雨的时空趋势。进行了创新趋势分析 (ITA) 以检测季节性和年降雨量的趋势。将通过 ITA 方法获得的长期趋势结果及其幅度与传统的 Mann-Kendall (MK)、改进的 Mann-Kendall (mM-K) 和线性回归分析 (LRA) 方法进行比较。在印度几乎所有的分区中都发现了季节性和年降雨量的显着趋势。季风和年降雨量在半岛和印度西北部的大多数分区显示出增加趋势，而在该国东北部中部观察到减少趋势。该国大部分地区的冬季降雨量呈下降趋势。MK/mM-K 和 LRA 的结果与 ITA 检测到的趋势一致。然而，ITA 在检测传统 MK/mM-K 和 LRA 测试遗漏的隐藏趋势方面更为敏感。本研究将为评估和主动缓解气候变化对水资源的影响，管理气候变率风险提供科学参考。