Riding the storm: a comparison of uncertainty modelling techniques for storm surge risk management

Abstract

In tropical Australia the risk from tropical cyclone disaster is significant and increasing, since much of the population inhabits low-lying coastal regions, which are experiencing further rapid urbanization. This paper examines GIS methodologies for predicting flood risk to urban communities that are at risk from cyclone-induced storm surge inundation, using as a case study the coastal community of Cairns. The methodologies attempt to account for the uncertainties inherent in risk predictions. Two uncertainty modelling techniques – the grid cell uncertainty model and the standard normal probability model – are implemented and evaluated in the context of improved risk management decision-making. Results show that, spatially, the results are almost identical, and for evacuation decision-making should be treated as such. The results of the methodologies confirm that the low-lying nature of Cairns contributes to the overall risk and that relatively high-frequency and small-magnitude surge events can cause major inundations. However, the techniques have very different computational overheads and implementation efficiencies and these are discussed in detail. The paper concludes by examining the implications of uncertainty modelling for risk management decision-making.