Context: Water, a vital source for agriculture, relies significantly on rainfall. The change in the distribution of rainfall response is an alarming situation to managers of water resources, because they are changing the quantity and frequency of rainfall, which is affecting soil moisture, groundwater reserves, and stream flows and demands. Guntur district in Andhra Pradesh, heavily depends on rainfall for agricultural production. The variability in rainfall has significant implications for major crop productivity, emphasizing the need for a detailed rainfall analysis to devise strategies addressing changing weather patterns and mitigating risks of crop failure and water scarcity. Objective: The study was taken up with an aim to understand the long term and seasonal trends in the rainfall pattern. Method: To understand the pattern existing in the rainfall data of Guntur, parametric like linear regression and non-parametric tests such as the Mann-Kendall test, Modified-Mann Kendall tests were applied. Wallis and Moore test was employed to look into the randomness of the rainfall data under consideration. The seasonal rainfall data of Guntur district acquired from the NASA power website which ranged from January 1981 to December 2021 for this study. Results & Discussion: An increasing and declining trend was seen in linear regression trend method. The significant result was found in the months of April and June which showed an increasing trend, whereas remaining months showed non-significant trend in modified Mann Kendall test. The Monsoon season showed a significant trend whereas pre-monsoon and post-monsoon periods presented a non-significant trend in the rainfall pattern of Guntur district. The yearly rainfall of Guntur district showed a non-significant trend pattern by Modified Mann-Kendall test. Significance: This study helps the farmers aware of variations in monthly and seasonal rainfall, they can better allocate resources and prepare for predicted water shortages during non-monsoon months.

Keyword: Trend Analysis, Rainfall, Mann-Kendall test, Modified Mann-Kendall Test, Sen’s Slope, Wallis-Moore test.