Floodflow frequency model selection in Australia

Abstract

Uniform flood frequency guidelines in Australia and the United States recommend the use of the log Pearson type 3 (LP3) distribution in flood frequency investigations. Many investigators have suggested alternate models such as the Generalized Extreme Value (GEV) distribution as an improvement over the LP3 distribution. Using floodflow data at 61 sites across Australia, we explore the suitability of various flood frequency models using L-moment diagrams. We also repeat the experiment performed in the original US Water Resource Council report (Bulletin 17B) which led to the LP3 mandate in the United States. Our evaluations reveal that among the models tested, the GEV and Wakeby distributions provide the best approximation to floodflow data in the regions of Australia that are dominated by rainfall during the winter months, such as southwest Western Australia and Tasmania. For the remainder of the continent, the Generalized Pareto (GPA) and Wakeby distributions provide the best approximation to floodflow data. The two- and three-parameter log-normal models and the LP3 distribution performed satisfactorily, yet not as well as either the GEV or GPA distributions. Other models such as the Gumbel, log-normal, normal, Pearson, exponential, and uniform distributions are shown to perform poorly. Recent research indicates that regional index-flood type procedures should be more accurate and more robust than the type of at-site procedures evaluated here. Nevertheless, this study reveals that index-flood procedures should not be restricted to a single distribution such as the GEV distribution because other distributions such as the GPA distribution perform significantly better in the most densely populated regions of Australia.