This research investigated the effectiveness of merging the remote sensing satellite precipitation, GSMaP-MVK (Global Satellite Mapping of Precipitation moving vector with Kalman filter), a very high spatial distribution product, with the local rainfall measurements for analysis of quantitative rainfall estimates and run-off prediction capability at basin scale. Three satellite-gauge merging methods stem from the idea of geo-statistical merging techniques were utilized to provide the precipitation input for conceptual hydrological model HBV for run-off simulation in two medium size river basins in different climate regions. The performance trends of three investigated merging approaches were similar in both two different climatic watersheds. The Bias reduction satellite-gauge merging method with good rainfall estimations and excellent stream-flow simulation skills is appropriate satellite-gauge blending method. It depicted the best performances, following by the monthly constant multiple factor and annual constant multiple factor respectively.