Estimation of Tropical Cyclone–Induced Wind, Rainfall, and Wave Multihazards for Selected Coastal Cities in China

Abstract

The southeastern coast of China experiences severe casualties and economic losses every year due to tropical cyclones (TCs), most of which are attributed to TC-induced wind, rainfall, and wave hazards. Estimating TC-induced multiple hazards through probabilistic hazard analysis is crucial due to the inherent randomness of TCs, facilitating offshore structural design and risk assessment. Most existing research typically focused on bivariate hazards among TC wind, rainfall, and waves, leaving a gap in comprehensive assessments that consider all three hazards. In this study, complete TC-induced multihazard estimations related to wind, rainfall, and waves were conducted, along with a refined analysis considering their asynchronous extrema. Ten-thousand-year synthetic TC tracks on the southeastern coast of China were stochastically generated using the Monte Carlo technique. The TC-induced wind, rainfall, and waves at selected coastal sites were then estimated using a semianalytical wind field model, the Hurricane and Rainfall Rate Distribution Estimator (HuRRDE) model, and the Young model, respectively. Site-specific data were extracted to form the bivariate or trivariate joint annual exceedance probability as well as the joint mean recurrence interval (MRI) between wind speed, maximum wind speed radius, rainfall rate, and significant wave height. The joint annual exceedance probability and MRI were analyzed for three scenarios, accounting for the moment of occurrence of the maximum value for each variable. The effects of duration on wind speed, rainfall rate, and significant wave height were also analyzed. The results of this study can be utilized as a guideline for multihazard structural design and as a reference for decision-makers to formulate typhoon risk assessment measures. The joint probability distributions of TC-induced multihazards, including wind, rainfall, and waves, opens up several potential applications in various fields. These applications leverage the joint behavior of these hazards to improve planning, design, and mitigation strategies. First, these results can be used to predict the combined loads on structures and design more resilient infrastructure, such as bridges, offshore wind turbines and platforms, power plants, transportation networks, communication systems, etc. Understanding the combined effects of heavy rainfall and storm surges induced by typhoons also helps in better flood risk prediction and the design of drainage systems, flood barriers, and levees. Second, the data can be used to model the likelihood of multiple hazards occurring simultaneously for regions prone to TCs, enabling more accurate pricing of insurance policies. Third, more precise predictions of TC-induced multihazard scenarios can inform emergency response protocols, enabling more effective disaster preparedness, evacuation plans, and resource allocation. Finally, knowing the duration of multihazard events can help stakeholders across industries to make more informed decisions about designing resilient systems, managing risks, and planning responses to prolonged exposure to multiple hazards during TCs.