A predictive model, employing a first order autoregressive structure, which enables estimation of the probability distributions of streamflow volumes in future seasons is developed. The model is applicable to streams that have intraseasonal runoff volumes describable by lognormal probability distributions. A season long observation provides the initial value which is propagated through future seasons by the first order autoregressive streamflow volume structure. For high interseasonal (lag one) correlations application of the model yields valuable forecasts for as many as 10 time periods in the future, while for low correlations such forecasting is of no additional value after four time periods. The method has the greatest utility for streams having high variability and distinct seasonality.