Analysis of Spatial Variability and Temporal Trends in the Extreme Rainfall of Kagera Sub‐Basin, Tanzania
Analysis of Spatial Variability and Temporal Trends in the Extreme Rainfall of Kagera Sub‐Basin, Tanzania
Nickson Tibangayuka,Deogratias M. M. Mulungu,F. Izdori
Abstract
Understanding the temporal and spatial variability of rainfall extremes is essential for developing effective adaptation strategies and making informed decisions in water resource management, agriculture, and infrastructure development. This study examines the spatial variability and temporal trends of extreme rainfall events in the Kagera sub‐basin, using nine climate indices from the Expert Team on Climate Change Detection and Indices (ETCCDI) and the Standardized Precipitation Index (SPI). The Sen's slope estimator was used to quantify the magnitude of the trend, whereas the Mann‐Kendall (MK) test was applied to evaluate its statistical significance at a significance level of α = 0.1. The findings revealed significant trends in the rainfall regime across both annual and seasonal time scales. Annually, consecutive dry days (CDD) showed predominantly negative trends, ranging from −0.24 to −0.1 days/year, whereas consecutive wet days (CWD) generally exhibited positive trends, ranging from 0.16 to 1.0 days/year. Both heavy and very heavy rainfall events, as well as the highest 1‐ and 5‐day rainfall totals, displayed increasing trends, especially in the eastern and central regions of the sub‐basin. Seasonally, the results show a decreasing trend in consecutive dry days (CDD) ranging from −0.3 to −0.03 days/year, whereas CWD exhibit an increasing trend, ranging between 0.01 and 0.65 days/year. Both heavy and very heavy rainfall events also exhibited a predominant upward trend. The SPI revealed that the sub‐basin experienced periods of severe and extreme drought, particularly between 1991 and 2005. However, there is a notable shift towards wetter conditions, as evidenced by predominantly increasing trends in the 3‐, 6‐, and 12‐month SPI. These findings provide critical insights for developing adaptation strategies to address socio‐environmental challenges which are often exacerbated by extreme rainfall events.
