Impact of climate change on major floods flowing into the Georges River estuary, Australia

Abstract Coastal flooding induced by storm surges and heavy rainfall is one of the most frequent climate-related natural hazards along the southeast Australian coast, home to more than 55% of the Australian population. Flooding in this densely populated region is a threat to public safety, coastal infrastructure, ecological systems and the economy. Although climate change is expected to cause an increase in major floods, few studies have quantified the potential changes in flood severity. This study quantifies the changes in flood peak discharge flowing to the Georges River estuary in Australia due to climate-change. An event-based hydrological model, Watershed Bounded Network Model (WBNM), was used to predict flood discharge. This hydrological model was forced by rainfall data obtained from the New South Wales and Australian Capital Territory Regional Climate Modelling Project version 1.5 (NARCliM1.5) for both historical and the Representative Concentration Pathway 8.5 (RCP8.5) conditions. Model calibration for the floods of March 1978 and March 2022 achieved a general agreement between the predicted and observed hydrographs, with an overall average 14% error in the peak values, further demonstrating that the modelling approach is generally reliable in projections of flood severity. Using high resolution climate model projections, the present study observed an increase of 22% in the model ensemble average from historical conditions to the RCP8.5 scenario for the 20-year average recurrence interval (ARI) 24 h extreme rainfall. This heightened extreme rainfall consequently resulted in the changes in flood discharge with an average rise of 55%. This study provides specific assessment of climate-generated risks for densely-populated regions, especially those on Australian east coast. Global studies have suggested that extreme precipitation events will increase under climate change. This study supports and enhances these assertions by using high resolution downscaling to quantify the specific changes within a large catchment.