Abstract: The present study aims to identify and measure the impact of climate change on rainfall patterns in the Uttar Dinajpur district of West Bengal. The hydro-meteorological time series rainfall data was collected from the IMD and CHRS data portals and subsequently analysed using various statistical methods. Agriculture in this district is the main economic activity, but the rainfall propensity is very unpredictable and sporadic that has a significant impact on agriculture. The rainfall results (1901-2019) were examined and assessed using statistical techniques for Mann-Kendall’s Z-statistic and Sen’s slope estimators. From the estimation, it is understood that the pre-monsoon, monsoon, and winter seasons have positive trends in rainfall, whereas the post-monsoon rainfall shows a negative trend and both Mann-Kendall and Sen’s slope projections depict the same. Likewise, January, February, April, May, June, July, August, and December reflect upward positive change, while a downward trend (decline trend) was recorded in March, September, and October. The winter Kharif crops are more impacted by this negative or decreasing pattern of seasonal rainfall than other crops. The maximum average monthly rainfall in July (892.1 mm) and January showed the lowest average monthly rainfall of 63.3 mm. The results revealed that during the monsoon season the maximum rainfall (75.2%) occurred and the coefficient of variance value is 20.4%. In the winter season, the minimal rainfall (2.87%) with a coefficient of variance (CV) is 72.9%. The rainfall forecast using SMOreg and linear regression methods has been calculated. This research contributes greatly to adopting different strategies by the planners, researchers, numerous government institutions, and NGOs for the overall development of the study area. This study may also be effective in the management of water resources in the study region.
Keywords: Rainfall Variability, M-K Test, SMOreg., Linear regression
