Hydrological modeling of a basin is necessary for water resources planning and management. To observe the fundamental causes of this privation of hydrological availability and spatial variability of determining water balance components on Abay River Basin were modeled for identifying the most sensitive stream flow parameters, comparing the evapotranspiration, and water balance components. All the input datasets were collected from both governmental and non-governmental organizations. Arithmetic mean method was used for data pre-processing and screening, and also the data quality were checked before modelling the water balance components of the basin. SWAT and SWAT-CUP model was used for water balance component estimation. Evapotranspiration was estimated using multiple methods, with significant variations observed between SWAT, Enku, GLDAS and MODIS. Key sensitive parameters were identified; including runoff curve number (CN2) was the most sensitive parameter, Deep aquifer percolation fraction (RCHRG_DP), Groundwater "revap" coefficient (GW_REVAP), and soil evaporation compensation factor (ESCO) were the second, third, and fourth sensitive parameters. The performance of SWAT model at Burie, Kessie, Beles, Didessa, and Dabus gauging stations showed R2 (0.74) and NSE (0.68) during calibration and the validation result verified R2 (0.76) and NSE (0.72) during validation. The average annual actual and potential ET values of the Abay river basin was 506 mm and 991 mm, 592 mm and 1316 mm, 670 mm and 2475 mm using SWAT, Enku, and GLDAS methods respectively from the year 1997 to 2020 and 633 mm and 2,397 mm using MODIS data from the year 2000 to 2020. Water balance components were quantified precipitation (1425 mm), PET (991 mm), AET (506 mm), surface runoff (376mm), lateral flow (37mm), return flow (459mm), percolation to shallow aquifer (504mm), and revap from shallow aquifer (19mm), recharge to deep aquifer 25mm, and average annual water yield 880 mm. Invest in high-quality hydrological and meteorological data collection networks, utilize more accurate and detailed input data, such as high-resolution digital elevation models and soil maps, promote integrated water resource management approaches to optimize water allocation and utilization, and Strengthen international cooperation to address trans-boundary water issues was some proposed recommendations. Key words: Abay River Basin, ArcSWAT, GLDAS, MODIS, Ethiopia