Comprehensive at-site flood frequency analysis using Monte Carlo Bayesian inference

In flood frequency applications where the design flood is required to have a specified exceedance probability, expected probability should be used. It s computation, however, presents formidable difficulties. This study presen ts a Monte Carlo Bayesian method for computing the expected probability dis tribution as well as quantile confidence limits for any flood frequency dis tribution using data on gauged flows, possibly corrupted by rating curve er ror, and on censored flows. This is achieved by a three-step process: (1) F ormulate the likelihood function for the given data; (2) approximate the li kelihood function using a multinormal distribution; and (3) integrate the e xpected probability integral using importance sampling. The FLIKE software for performing this is described, and an example is given.