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This study focuses on a key element of climate i.e rainfall. Accurately predicting rainfall or precipitation trends is vital for economic growth and development of a country. The research studied the precipitation variability across the state of Maharashtra using ”Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS” over a period time of 36 years (1982-2018). The data was processed to find out seasonal and Annual trends by using nonparametric analysis. The Mann-Kendall (MK) Test was used for analysis of increasing & decreasing (monotonic) trend together with nonparametric Sen’s Slope Estimator to estimate the magnitude of trend over time series data. The statistical analysis of whole reference time series data highlights that (1) the trend looks predominantly positive (increasing), both at the annual and seasonal scales except for the pre-monsoon season. (2) Pre-Monsoon season (MAM) showed a negative trend for few districts. A total of 26 districts consisting of 130 Sub districts covering 148086.45 sq km of Area or 48.1% of the area of Maharashtra showed positive trend when p value> 0.05. In pre monsoon season 8 sub districts showed negative trend whereas 21 districts showed positive trends.
Keywords: Rainfall trend; Mann-Kendall test; Sen’s Slope Estimates; Trend Analysis
