Estimating high quantiles of extreme flood heights in the lower Limpopo River basin of Mozambique using model based Bayesian approach

Abstract. In this paper we discuss a comparative analysis of the maximum likelihood (ML) and Bayesian parameter estimates of the generalised extreme value (GEV) distribution. We use a Markov Chain Monte Carlo (MCMC) Bayesian method to estimate the parameters of the GEV distribution in order to estimate extreme flood heights and their return periods in the lower Limpopo River basin of Mozambique. The return periods of extreme flood heights based on the Bayesian approach show an improvement over the frequentist approach based on the maximum likelihood estimation (MLE) method. However, both approaches indicate that the 13 m extreme flood height that occurred at Chokwe in the year 2000 due to cyclone Eline and Gloria had a return period in excess of 200 years, which implies that this event has a very small likelihood of being equalled or exceeded at least once in 200 years.