Spatiotemporal Trends of Precipitation Analysis in Riverine Agriculture Area of Shabelle River Using Mann–Kendall Family and Innovative Trend Analysis

The trend analysis of hydro‐meteorological time series plays a vital role in water resource management and climate change, particularly in arid and semiarid regions. This study aims to investigate the long‐term spatiotemporal variation in rainfall in four major agricultural cities situated near or on the banks of the Shabelle River. The analysis was conducted on an annual and seasonal basis using NASA Prediction of Worldwide Energy Resource Project (NASAPOWER) rainfall data from 1981 to 2020. Three widely used approaches—Mann–Kendall (MK), Modified Mann–Kendall (MMK), and Innovative Trend analysis (ITA) were employed to detect trends and variations in time series data. The findings indicate that all three methods revealed significant positive trends in annual rainfall for the four stations. Additionally, significant positive trends were observed in the Deyr and Hagaa seasons at significance levels of 0.1, 0.05, and 0.01. Although there were increasing trends in the Gu season across all stations, none of the methods showed a significant trend. The MK and MMK tests indicate an insignificant negative trend in the Jilaal season, which is the main dry season. Conversely, the ITA captured a significant negative trend in the Jilaal season for all four stations. This suggests that ITA is more effective at detecting significant hidden trends than MK and MMK. Based on these findings, the Deyr season, the second rainy season, exhibits an increasing trend at all stations, while the Gu season, the first main rainy season, shows an insignificant increasing trend. Interestingly, the Hagaa season, the second dry season, showed a highly significant increasing trend. The results presented in this study can serve as valuable information for policymakers and planners to make informed decisions related to water resource management, irrigation, and urban water usage.