Water resources systems are designed and operated on assumption of stationary hydrology. Existence of trends and other changes in the data invalidates this assumption, and detection of the changes in hydrological time series should help us revise the approaches used in assessing, designing and operating our systems. In addition, trend and step change studies help us understand the impact of man’s activities (e.g. urbanisation, deforestation, dam construction, agricultural activities, etc.) on the hydrological cycle. Trends and step changes in the seasonal and annual total rainfall for 20 stations in the Lake Victoria basin were analysed. The seasonal rainfall for any station in a given year was defined in two ways: (1) fixed time period where the rainy seasons were taken as occurring from March–May (long rains) and from October–December (short rains); and (2) variable periods where the rainy seasons were taken as the three consecutive months with maximum total rainfall covering the period of January–June (long rains) and July–December (short rains), to take into account the fact that the onset of rainy seasons within the basin varies from year to year and from one station to the next. For each station, sub datasets were derived covering different periods (all available data at the station, 1941–1980, 1961–1990, 1971–end of each station’s time series). The trends were analysed using the Mann-Kendall method, while the step changes were analysed using the Worsley Likelihood method. The results show that positive trends predominate, with most stations showing trend being located in the northern part of the basin, though this pattern is not conclusive. In all, 17% of the cases have trends, of which 67% are positive. The 1960s represent a significant upward jump in the basin rainfall. Seasonal rainfall analysis shows that the short rains tend to have more trends than the long rains. The impact of the varying month of onset of the rainy season is that the results from analyzing the fixed-period and variable-period time series are rarely the same, meaning the two series have different characteristics. It may be argued that the variable-period time series are more reliable as a basis for analysing trends and step changes, since these time series reflect more closely the actual variability in rainy seasons from one year to the next. The fixed-period analysis would, on the other hand, find more practical use in planning.