BAYESIAN PREDICTION OF EXTREME PRECIPITATION EXCEEDING OVER RETURN LEVEL, IN COMPARISON WITH PREDICTION DISTRIBUTION OF MAXIMUM PRECIPITATION IN THE FUTURE RETURN PERIOD

Abstract

 Bayesian approach now becomes popular by using MCMC method. One of the advantages is that the assumption of the central limit theorem for the estimation errors is not required, thus the estimations of the parameters are distributed and they have the probability densities. But this will show troublesome aspects for engineers. We should choose a reference value for each parameter and our target return value. It is contrasted that maximum likelihood estimation gives us principally a point estimation with the accompanying errors secondary. This research shows the prediction distribution for coming extreme precipitaion in the condition that it exceeds the return level, and it gives also its related point estimation for parameters that will serve for flood design.