The need for higher resolution of temporal and spatial distribution of rainfall data was of great importance in most of hydrological analysis. Simulated short-time period rainfall is important for water resource development design and assessment. The aim of this research was developing model to generate synthetic data of higher temporal resolution (hourly) scale from the existing daily rainfall data for the Awash River basin. Fifteen minute rainfall data collected from national meteorological agency for 13 active stations in the basin and daily data collected for 54 out of 99 stations in the basin were analyzed. Stochastic rainfall disaggregation method based on climate similarity to transfer event statistics from neighboring recording station was used. To enable the disaggregation procedure using the stochastic method, stations in the basin were regionalized to create regions with similar climate condition and similar rainfall pattern. In addition the temporal rainfall disaggregation model known as Hyetos was tested using the available data. Three regions with similar climate condition and rainfall pattern were created and tested to be homogeneous. The output stochastic method was validated by initially identified hidden stations in each region. The validation was conducted for selected one month in each region using separate data. Both methods are tested by using statistical comparison of variance, skew-ness, probability of dry period, and Lag-1 ACF. The result of the stochastic method showed very good performance in preserving the probability of zero rainfall and the daily total. But has limitation in disaggregating rainfall magnitudes with high return period. The comparison of the two methods showed that Hyetos is better in preserving the statistical property. Generally the methods are capable in preserving statistical properties and the daily total rainfall depth.