Evaluation of the usefulness of historical and palaeological floods in quantile estimation

The methods of incorporation of historical floods and palaeological information into flood frequency analysis, and the usefulness of doing so, have been evaluated by many hydrologists. These evaluations are not in complete agreement. The results of a Monte Carlo study are presented comparing different simulation procedures and assessing the value of historical floods for at-site flood frequency analysis on the assumption of a Gumbel (EVI) distribution. It is shown that historical floods and palaeological information provide a useful source of information additional to the recorded series, and have great value in flood frequency analysis when floods are drawn from the Gumbel distribution. Simulation procedures based on type II censoring result in the largest bias and root mean square error in quantile estimation. This may be due to their assumption of type II censoring in the production of their simulated samples, an assumption that has some limitations. In the present work it was found that the type I censored-data maximum likelihood estimator is a robust model for the Gumbel distribution and that the type II censored-data maximum likelihood estimator performs poorly when the data are in fact obtained by type I censoring.