LAUSR

The economy of Uganda depends heavily on rainfed agriculture. In this study, daily observed rainfall datasets from 9 weather stations with length varying within 1955 and 2017 were used to generate the probability of rainfall and dry spells occurrence using a Markov chain approach. The length of the maximum dry spell was obtained using the direct method based on the definition of a dry day that rainfall is less than 0.85 mm ( R  < 0.85 mm) and the length of a dry spell is the sum of the number of dry days in a sequence. Mann–Kendall’s statistics (MK) was used to assess the trends in the length of maximum dry spells and Sen’s slope test to estimate the magnitude of change ( Q 2 ) in days/per month. MK test results show increasing trends in the length of the maximum dry spells in March at 5 stations, while an insignificant decrease in the length of maximum dry spells is revealed for remaining stations. For the month of April and May, the length of a maximum dry spell is observed to be decreasing across most stations although not statistically significant at the 5% significance level during their respective study periods. The probability of 8 days dry spell is high across all the stations (38–69%) in March, April, and August. This could strongly be related to the changing climate in the region. Negative impacts due to increased length of dry spells could be mitigated through well-timed planting of crops, use of irrigation, and growing of heat-/drought-tolerant crop varieties to match the changing weather and climate patterns.