Statistic and probability plays an important role in scientific and engineering community (Ayyub 2011) because statistical tools help to detect spatial and temporal trends for hydrological and environmental studies. Major schemes or projects are formulated based on the historical behavior of environment under uncertain climatic conditions. Therefore, a study of trend assists to investigate the overall pattern of change over time in hydro-meteorological variables especially for water resources project on temporal and spatial scales. Rainfall has been widely considered as one of the starting point towards the apprehension of climate change courses. Various studies have indicated due to climate change, rainfall pattern is most likely to change which would have adverse impacts on lives and livelihoods of millions of people. Analysis of the general rainfall trend is vital in understanding the underlying features, for the purpose of forecasting and in identifying the changes and impacts that are very crucial for an agro-based economy like the one of India. Trends in data can be identified by using either parametric or non-parametric methods, and both the methods are extensively used. Testing the significance of observed trends in hydro meteorological time series has received a great attention recently, especially in connection with climate change. The changing pattern of rainfall deserves urgent and systematic attention for planning, development, utilization and management of water resources. In the present study, to analyze the trends of the rainfall series of each individual station, the popular statistical methods; simple regression method (parametric), Mann-Kendall test and Sen’s estimator of slope method (non-parametric) have been applied. Among which Mann Kendall test has been used to detect significance of the trends in the time series of the precipitation & Sen’s slope estimator has been used to find out the magnitude of the detected trend.