Results of numerous evaluation studies indicated that satellite-rainfall products have large systematic and random errors. Therefore these products may require further refinements before being used as input to hydrologic applications. In this study we explore the benefits of applying a simple real-time bias correction scheme to enhance the hydrologic applicability of the CMORPH rainfall product. The study area is the Gilgel Abbay catchment which is situated at the source basin of the Upper Blue Nile basin in Ethiopia. The rain gauge availability in this watershed has poor density and is unevenly distributed. Therefore, rainfall estimation in this catchment can benefit from merging CMORPH and gauge rainfall data as neither gauge-only nor satellite-only data results in accurate rainfall estimates. In this study, we calculate the bias factor (BF) as the ratio between rainfall amounts from CMORPH and gauges. Three modes are tested for the bias estimation: space and time-fixed, time-variable and space-fixed, and time-space-variable bias factors. Time variability in the bias factors is accounted for by estimating the bias over a moving time window of the last 7-days in order to allow sufficient rainfall accumulation for bias calculation. The bias of CMORPH is then adjusted by multiplying its daily rainfall amounts by the corresponding BF values. Applying space-time fixed BFs resulted in only slight improvement (in some cases deterioration) of CMORPH rainfall estimates. However, temporally varying BFs substantial reduced the rainfall bias by up to >50% and therefore enhanced the accuracy of the simulated stream flows. The model calibration compensated for rainfall input error by changing the optimum values of model parameters as the source of the rainfall data changes from gauge only to satellite only or satellite-gauge. Large changes of up to 81% were obtained for those parameters that control the stream flow volume but these values are still with in model allowable ranges.