Assessing long term rainfall variability and its implications for rain fed agriculture using statistical trend analysis in Nagaland, Northeast India

The application of statistical methods in analysing trends and variability of rainfall to understand the pattern has become pertinent in regions dominated by agriculture practices. This study investigated the annual and seasonal pattern of rainfall among six stations/districts in Nagaland, Northeast India, from 1991 to 2022. The state of Nagaland has an agrarian economy based primarily on rain-fed agriculture practices, emphasizing the importance of understanding weather patterns, particularly rainfall. The rainfall data from Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) having a spatial resolution of 0.05°(5 km) has been analyzed for annual and seasonal trend and variability. The statistical methods, viz. serial correlation (autocorrelation), innovative trend analysis (ITA), Mann-Kendall (MK) test, and Sen’s slope estimator and geospatial analysis have been carried out using R Studio and GIS. MK Z-statistic has a decreasing annual trend of -2.351, while Sen’s slope and ITA slope indicate a decrease of -10.06 mm/year, and − 11.4 mm/year, respectively. The seasonal rainfall pattern likewise indicates a consistent declining tendency across the studied stations/districts, with the exception of the retreating monsoon. The variability and onset of the monsoon rainfall impacts the cropping calendar both in permanent agriculture and shifting cultivation in the state. For which, understanding of the rainfall pattern is crucial for agriculture development. Further, findings of this study will help plan the agricultural calendar and mitigate rainfall-induced challenges in the state.