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This study aimed at identification of abrupt change points (CPs) and detection of gradual trends in 34-year (1980-2013) annual rainfall at nine stations of an Indian arid region. The CPs were determined by five tests and their significance was examined by two tests. Furthermore, trends were tested by three tests and their magnitudes were quantified by two tests. Novelty of the study lies in investigating significance of trends sequentially over years by applying Mann-Kendall (M-K) test. The identified CPs were similar for standard normal homogeneity test and cumulative deviations test at most stations. In contrast, Pettitt and Bayesian tests detected CP in years 2002 and 2005 at six and three stations, respectively, and their significance was verified. Results of sequential M-K test did not match with other tests’ results. The mean annual rainfall after CP (350-627 mm) increased by 14-80% of the amount before CP (306-444 mm) with 7-42% reduction in coefficient of variation. The box-whisker plots supported these findings. Results of trend tests indicated statistically significant trends at Anjar, Bhachau, Mandvi and Rapar. Trend magnitudes by linear regression prior to CP (-6.2 to 7.1 mm year(-1)) showed an overall increase after CP (4.7-40.8 mm year(-1)) with negative trend at one station. Sen’s slope test, showing good harmony with linear regression, revealed that trend magnitudes after CP were 2-10 times higher than that for 34-year period at six stations. Results of M-K test applied for sequential periods emphasized that rainfall trends are becoming stronger over time. This finding suggests that significance level of increasing rainfall trends may further increase in future. Finally, findings of this study are useful for planners and decision makers for developing policies to meet the challenges of the heightened rainfall in study area. Also, the approach used here may be adopted in other parts of the globe.