Satellite-based Rainfall products have been playing an immense role and used as an alternativernsource of data in regions where conventional rainfall measurements are not readily available orrninadequate. rnThe objective of this study is to evaluate and compare high-resolution satellite rainfall products suchrnas CHIRPS, PERSIANN-CCS, RFE and TAMSAT with the ground-based observed rainfall datarnover the Omo-Gibe River Basin. For spatial assessment, a point to pixel approach at differentrntemporal scale over the time window of 2003-2017 is used. Moreover, the capabilities, applicability,rnand limitations of satellite rainfall products were also evaluated by forcing the hydrological modelrn(HBV-light) in Wabe Watershed from Omo-Gibe River Basin. Continuous statistics was used tornassess their performance in estimating and reproducing rainfall amounts and categorical statistics wasrnused to evaluate rain detection capabilities while Kling-Gupta Efficiency (KGE) is used for modelrnperformance evaluation. rnAt mean daily scale, a good correlation agreement was observed by Wolkite with TAMSAT, RFE,rnPERSSIAN-CCS, CHRIPS (r=0.769, r=0.686, r=0.627, r=0.543) respectively. While the remainingrnstation with the products show a low correlation and the time step has an important influence. Thisrnshowed when the time step increases the accuracy of satellite rainfall products to predict the rainfallrnevent relative to the station value will increase.rnThe HBV model was simulated using datasets from 2003-2012 considering both satellite rainfallrnproducts and ground-based observed dataset. The model has shown good performance whenrncalibrated with the gauged observed rainfall data. During calibration, the objective function showedrnKGE= 0.42 for daily, and KGE=0.61 for monthly time scale; whereas, the validation period showedrnKGE=0.54 and 0.71 for daily and monthly time scales respectively. The adjusted satellite rainfallrnestimates TAMSAT and RFE showed relatively good performance while adjusted PERSIANN-CCSrnand RFE relatively showed less performance. The adjusted TAMSAT data set perform the best resultrnthan that of the other dataset at daily and monthly time scale with KGE=0.39 and KGE=0.54 forrncalibration and KGE=0.6 KGE=0.72 for validation period respectively. Finally, this study revealsrnthat besides the gauged observed rainfall data the bias-adjusted TAMSAT and RFE dataset can bernused as an alternative dataset for hydrological modeling for the study area.