Evaluation and Comparison of Satellite-Derived Estimates of Rainfall in the Diverse Climate and Terrain of Central and Northeastern Ethiopia

Understanding rainfall processes as the main driver of hydrological cycle is important for formulating future water management strategies; however, data availability challenging countries such Ethiopia. This study aims to evaluate and compare satellite estimates (SREs) derived from tropical measuring mission (TRMM 3B43v7), estimation remotely sensed information using artificial neural networks—climate record (PERSIANN-CDR), merged satellite-gauge estimate (IMERG), Global Satellite Mapping Precipitation (GSMaP) with ground-observed over varied terrain hydrologically diverse central northeastern parts Ethiopia—Awash River Basin (ARB). Areal comparisons were made between SREs observed various categorical indices statistical evaluation criteria, a non-parametric Mann–Kendall (MK) trend test was analyzed. The monthly weighted exhibited relatively comparable results SREs, except annual peak shifts noted in all SREs. PERSIANN-CDR products showed decreasing at elevations greater than 2250 m above sea level river basin. demonstrates that elevation regimes may affect data. On basis modified Kling–Gupta Efficiency, IMERG v06, TRMM 3B43v7, performed well descending order ARB. However, GSMaP poor performance upland sub-basin. A high frequency bias, which led an overestimation 3B43v7 eastern lower basins. Furthermore, MK none sub-basins monotonic 5% significance GSMap In ARB, GSMaP, can be used alternative options frequency-, flood-, drought-monitoring studies. some require bias corrections improve quality.