Enhancing Tropical Cyclone Risk Assessments: A Multi-Hazard Approach for Queensland, Australia and Viti Levu, Fiji

Tropical cyclones (TCs) are natural hazards causing extensive damage to society, infrastructure, and the natural environment. Due to the multi-hazardous nature of TCs, comprehensive risk assessments are essential to understanding how to better prepare for potential impacts. This study develops an integrated methodology for TC multi-hazard risk assessment that utilises the following individual assessments of key TC risk components: a variable enhanced bathtub model (VeBTM) for storm surge-driven hazards, a random forest (RF) machine learning model for rainfall-induced flooding, and indicator-based indices for exposure and vulnerability assessments. To evaluate the methodology, the regions affected by TC Debbie (2017) for Queensland and TC Winston (2016) for Fiji's main island of Viti Levu were used as proof-of-concept case studies. The results showed that areas with the highest risk of TC impacts were close to waterbodies, such as at the coastline and along riverine areas. For the Queensland study region, coastal populated areas showed levels of "high", "very high", and "extreme" risk, specifically in Bowen and East Mackay, driven by the social and infrastructural domains of TC risk components. For Viti Levu, areas classified with an "extreme" risk to TCs are primarily areas that experienced coastal inundation, with Lautoka and Vuda found to be especially at risk to TCs. Additionally, the Fiji case study was validated using post-disaster damage data, and a statistically significant correlation of 0.40 between TC Winston-attributed damage and each tikina's overall risk was identified. Ultimately, this study serves as a prospective framework for assessing TC risk, capable of producing results that can assist decision-makers in developing targeted TC risk management and resilience strategies for disaster risk reduction.