The uncertainty in forecasted precipitation remains a major source of uncertainty in real time flood

forecasting. Precipitation uncertainty consists of uncertainty in the magnitude, temporal distribution,

and spatial distribution of the precipitation. Due to uncertainty propagation of precipitation in flood

forecasting model of HEC-1, temporal disaggregation method is applied by using the framework of fuzzy

Extension Principle supported by a normal genetic algorithm. The uncertainty due to the unknown temporal

distribution of the precipitation is achieved by randomly disaggregation of the precipitation into subperiods.

Uncertainty in discharge and volume of flood hydrograph due to precipitation with temporal disaggregation

and precipitation without temporal disaggregation is estimated and is compared with each others. The results

show that in all forecasts the uncertainty in discharge and volume of flood hydrograph due to precipitation

with temporal disaggregation is significantly more than uncertainty due to precipitation without temporal

disaggregation. So that for forecast subperiod equal to six and membership function of precipitation

magnitude equal to zero, the uncertainty in peak discharge due to precipitation with temporal disaggregation

and without temporal disaggregation are 33.7% and 16%, respectively. Also the uncertainty in volume of

flood hydrograph due to precipitation with temporal disaggregation and without temporal disaggregation

are 23.5% and 14.8%, respectively. Also the uncertainty in peak discharge due to the uncertainty in the

temporal and spatial distribution can be significantly dominant over the uncertainty due to the uncertainty

in the magnitude of the precipitation. So that for forecast subperiod equal to six and membership function

of precipitation magnitude equal to zero، the uncertainty in peak discharge due to the temporal and spatial

distribution and the magnitude of precipitation are 17.7% and 16%, respectively. Therefore using spaceand

time-averaged precipitation over the basin may lead to erroneous forecasts.