Application of the design variable method to estimate coastal flood risk

Abstract

Coastal floods can result from multiple forcing variables, such as rainfall and storm tides, that are simultaneously extreme. In these situations, flood risk estimation methods must account for the joint dependence between the forcing variables. The design variable method is a statistically rigorous, flexible and efficient approach for evaluating the joint probability distribution. However, in practice, a number of factors need to be considered in order to produce accurate estimates of flood risk; these include data selection and pairing, temporal variability of dependence, dependence parameter inference and bias, the estimation of confidence intervals, and the incorporation of possible time-varying changes to each of the forcing variables due to climate change. This paper addresses these factors using a case study fromPerth, Western Australia, to show how the design variable method can be applied to coastal flood risk under historical and future climates.