Floods are one of the most important natural disasters causing extensive loss of life and properties every year all over the world. Occasional tropical or Mansoon rain can produce floods that are sometimes considered as a lifesaver due to water scarcity in arid and semi-arid regions. By simulating the hydrograph of probable floods in each year, action plans can be implemented to reduce damages and also to better plan for utilizing water resources potential of floods. By simulating future rainfall, and estimating the resulted runoff, it can be determined whether a severe flood will occur or not. The simulated flood hydrograph is affected by uncertainties in future rainfall simulation and runoff modeling that should be considered when flood prevention plans are developed. In this study, a long lead flood simulation model is developed, considering the uncertainties in the simulation process. The SDSM (Statistical Downscaling Model) is used to generate hourly and daily rainfall data, needed for flood simulation, based on General Circulation Models (GCM) outputs. The extreme simulated rainfalls in each year are considered as the probable flood and a rainfall-runoff model developed in HEC-HMS software environment is used for simulation of the corresponding hydrograph. The uncertainties in hydrograph development are considered through variation of curve number (CN) and time of concentration (Tc). The effect of climate change on flooding probability is evaluated by comparing the Cumulative Distribution Function (CDF) of the simulated floods with historical floods. The proposed model for long lead flood simulation has been applied to the Kajoo basin located in the south-eastern part of Iran.