Spatial-temporal rainfall trend and variability assessment in the Upper Wabe Shebelle River Basin, Ethiopia: Application of innovative trend analysis method

Study region: Upper Wabe Shebelle River Basin (UWSRB), Ethiopia. Study focus: This study investigated the spatio-temporal patterns or trends and spatial distribution and variability of rainfall in seasonal and annual time-series. The rainfall variability was evaluated by the coefficient of variation (CV), precipitation concentration index (PCI), and standardized anomaly index (SAI). The spatio-temporal trends were also analyzed using the Mann-Kendall test (MK), Sen's slope estimators (SSE), and the latest technique of innovative trend analysis (ITA) method was used for analyzing the low, medium and high rainfall clusters. New hydrological insight for the region: In most of the rainfall stations, high amount of annual rainfall happened in the Kiremt (wet) season, and high rainfall variability was during the Bega (dry) season. During the annual rainfall, the MK test and SSE were statistically non-significant in some stations, and heavy rainfall was detected in the Kiremt and Belg (transition) seasons. For the Kiremt and annual period, most rainfall stations showed high rainfall cluster and increasing trends, while low rainfall was observed in Bega season which exhibited decreasing trends. The outcomes of comparison revealed that the ITA method is more robust and surpassed the MK test as it could detect monotonic and non-monotonic trends that cannot be observed by the MK method. The result of this study is helpful for water resources planning and management in UWSRB.

Automated summary

The study investigated the spatio-temporal patterns and variability of rainfall in the Upper Wabe Shebelle River Basin in Ethiopia and found that high rainfall amount occurred in the wet season and high variability in the dry season. The ITA method was shown to be more robust than the MK test in detecting trends, providing valuable insights for water resource planning and management in the region.