Determine the best method for analysing long-term (120 years) annual and seasonal rainfall trends in four east India river basins

Studying rainfall patterns is very important because agricultural production and flood conditions depend on proper water management. Therefore, accurately identifying trends in climate scenarios is essential to achieve this goal. This study, therefore, analyses rainfall trends using the Mann–Kendall test (MKT), modified Mann–Kendall test (MMKT), Spearman rank correlation (SRC), Şen slope estimator (SSE), and innovative trend analysis method (ITAM). This investigation analyses annual, monsoon, autumn, summer, and winter rainfall trends using the most extensive hydrometeorological time series from 1901 to 2020. Five such methods of trend analysis use 120 years of gridded meteorological data from the India Meteorological Department for the neighbouring four river basins Kangsabati, Keliaghai, Silabati, and Dwarkeswer in east India. For the winter period, no significant trend is detected using the MKT, MMKT, SRC, and SSE. While the ITAM detects a significant trend at 88% of grid points of the study area. During other seasons, the MKT, MMKT, SRC and SSE notice trends for 76% of grid points with less significance than the ITAM method. Overall results obtained using the ITAM and MMKT methods are proved to be more effective in detecting sensitive trends. This study can serve as scientific support for the identification and strategic mitigation of climatic change impacts on water management to reduce the risk of climate change.