A Probabilistic Coastal Inundation Assessment for Australia

O'Grady, JG.; Gregory, RL.; Erwin, TA., and Hemer, MA., 2024. A probabilistic coastal inundation assessment for Australia. In: Phillips, M.R.; Al-Naemi, S., and Duarte, C.M. (eds.), Coastlines under Global Change: Proceedings from the International Coastal Symposium (ICS) 2024 (Doha, Qatar). Journal of Coastal Research, Special Issue No. 113, pp. 185-189. Charlotte (North Carolina), ISSN 0749-0208. Coastal communities face an uncertain future when considering the threat of ocean flooding from catastrophic storms coinciding with high tides and rising mean sea levels. Even with ambitious global Green House Gas (GHG) mitigation targets, we are confident sea levels will continue to rise in excess of 0.28m from 2005 to 2100 (IPCC), which will cause an exponential increase in coastal flooding. However, uncertainties remain in IPCC sea level projections and in the estimation of design storm characteristics, e.g., a 1 in 100 year event, associated with extreme model fits to limited (<100 years) observation records. There are also assumptions that the stochastic properties of the extreme sea level (ESL) storm driven events are stationary and will not undergo a future “tipping point″ step change in weather regimes. These future uncertainties and assumptions in flooding levels should be considered in an assessment of hazards and risks to our coastal assets. This study provides estimates of the likely range (uncertainty) of how high future design storms will reach using tide gauge observations and numerical simulations of historic extreme water levels with future mean sea level projections from the latest IPCC assessment report (AR6). Also provided are details on the input data and methods used to map probabilistic flood zones for individual local government areas (LGA) using spatial model techniques that account for wave action, local beach geomorphology, and ocean hydrological conductivity of flooded areas. The provided LGA probabilistic flood zone maps allow users to identify which low lying land is most likely to be affected and which land is less likely to be affected for a future year, global GHG Shared Socioeconomic Pathway (SSP) and Annual Exceedance Probability (AEP) design storm. A national assessment of buildings potentially exposed is then provided as an example of future flooding to high impact low probability ESL.