Two statistical estimating procedures are presented for using regression information along with direct observations to obtain estimates of the expected value of peak flood discharge rates exceeding a constant base. The first type of estimate represents the minimum mean squared error linear combination of regression and direct estimates, whereas the second is a Bayesian estimate based on an objective prior distribution associated with the regression model. A comparison of combined estimates to regression and direct estimates used alone indicates that a significant reduction in the mean squared error is obtained by using combined estimates. A comparison of the two methods for obtaining a combined estimate indicates that in many cases they both give essentially the same result.