Spatio‐Temporal Variability of Rainfall and Trend Analysis Using Non‐Parametric Statistical Methods of Jaldhaka‐Torsa Interfluve in sub‐Himalayan North Bengal, India

ABSTRACT The Jaldhaka‐Torsa interfluve in the sub‐Himalayan region of North Bengal, India, is an agriculturally significant zone with a tropical humid climate and high dependency on monsoonal rainfall. This study investigates the spatio‐temporal variability and long‐term trends in rainfall over the period 1901–2023 because documenting the rainfall regime is the soul of agriculture and which makes the need of the work, using data from 15 IMD stations. Statistical measures such as mean, standard deviation, coefficient of variation (CV), skewness, kurtosis, and the Standardised Anomaly Index (SAI) were applied to evaluate rainfall variability. Robust data integrity checks, including normality, homogeneity, and serial correlation tests, were performed to validate the dataset prior to analysis. While Mann‐Kendall and Spearman's rho tests assessed trends, with Sen's slope quantifying trend magnitudes. Pettitt and Buishand U tests were used to identify change points. Results indicate an average annual rainfall of 3769.27 mm, with a CV ranging from 21.37% to 42.3%, reflecting significant spatial variability. The monsoon season accounts for the majority of annual rainfall and exhibits statistically significant increasing trends at several stations, especially after the identified change points (1950s–1990s). In contrast, post‐monsoon rainfall shows a widespread declining trend, while monsoon and winter seasons reveal weak, mostly insignificant increases. Monthly trend analysis highlights significant increases during May, June, and August at key stations, particularly Station E, whereas Stations M, I, and A show decreasing trends. The findings revealed increasing monsoonal variability and shifts in rainfall trends, particularly during the monsoon and post‐monsoon seasons, with implications for water resource planning, rain‐fed agriculture, and regional climate adaptation. These insights support the development of climate‐resilient strategies and interfluve‐based planning models in monsoon‐dependent regions.