Estimating the probability of compound floods in estuarine regions

Abstract

The quantification of flood risk in estuarine regions relies on accurate estimation of flood probability, which is often challenging due to the rareness of hazardous flood events and their multi-causal (or "compound") nature. Failure to consider the compounding nature of estuarine floods can lead to significant underestimation of flood risk in these regions. This study provides a comparative review of alternative approaches for estuarine flood estimation-namely, traditional univariate flood frequency analysis applied to both observed historical data and simulated data, as well as multivariate frequency analysis applied to flood events. Three specific implementations of the above approaches are evaluated on a case study-the estuarine portion of Swan River in Western Australia-highlighting the advantages and disadvantages of each approach. The theoretical understanding of the three approaches, combined with findings from the case study, enable the generation of guidance on method selection for estuarine flood probability estimation, recognizing issues such as data availability, the complexity of the application/analysis process, the location of interest within the estuarine region, the computational demands, and whether or not future conditions need to be assessed.