The agricultural sector in India primarily relieson monsoon rains, making it necessary for agricultural water managers to study variations in water availability by analyzing rainfall patterns. This information is critical for deciding cropping patterns and irrigation approaches, managing water resources, and improving crop water productivity. The long-term spatiotemporal variability over the command area, India Meteorological Department (IMD) based selection of thresholds for extremes indices, and thorough analysis of the consequences of extreme on agriculture make the study unique. These aspects collectively enhance the perception of the climate-agriculture relationship, which is essential for promoting agriculture resilience under changing rainfall patterns. This type of research is very limited in the literature. Therefore, the present study focuses on comprehensively analyzing the spatiotemporal variability of rainfall and extreme precipitation indices and their implications on agriculture. The study is carried out in the UpperGanga Command Area (UGCA), India's oldest irrigation canal system, by using long-term (1901-2021) high-resolution (0.25 × 0.25°) daily rainfall gridded data obtained from IMD, Pune. Eight different extreme rainfall indices are used to assess spatiotemporal variations. The Mann-Whitney-Pettitt test identified 1970 as a significant change point. Rainfall trends and extreme indices for pre- and post-1970 periods were examined using the non-parametric modified Mann-Kendall test. The results show significant increases in rainfall trends for the annual, monsoon, and kharif seasons from 1901 to 1970, but significant decreases were observed during 1971-2021. This difference resulted in a noticeable decrease in average precipitation in the latter period, approximately 62mm less than in 1901-1970. Similarly, extreme precipitation indices, including the number of rainy days (NxRainy), consecutive dry days (CWD), simple daily intensity index (SDII), and total precipitation (PRCPTOT), exhibited increasing trends in 1901-1970, but they showed significant decreasing trends in 1971-2021. In addition, there is a strong positive correlation between these indices and total precipitation. The study also found that geographical factors influence these trends, with all indices, except SDII, strongly correlated with latitude and elevation, but not with longitude. The implications of these negative rainfall and extreme rainfall trends were further analyzed, and the results indicate a significant impact on the cropping patterns in the study area. The present research findings will be beneficial for regional water resource managers and policymakers in better understanding the existing trends in rainfall distribution over the UGCA.