HURRICANE RISK ASSESSMENT IN A LONG TEMPORAL SCALE

  • Nguyen, B. M. Delft University of Technology, Delft, the Netherlands
  • Van Gelder, P. H. A. J. M Delft University of Technology, Delft, the Netherlands

Abstract

In coastal areas, hurricane, also referred to as typhoon, is one of the costliest and deadliest natural disasters. While hurricanes are unavoidable, their risk can be considerably lessened by numerous approaches, such as an appropriate system of sea defense structures. The reliability of those solutions depends on the accuracy of key typhoon parameters, which are used as inputs for the analysis processes. Currently, all hurricane estimation methods are based on historical records of typhoon tracks and intensities. However, the most crucial limitation relates to the small sample size because hurricanes are both relatively infrequent and small in terms of the length of coastlines affected by these typhoons each year. Therefore, it is difficult to derive accurate key parameter of the strongest typhoons, on which risk analysis and design of coastal defense structures must be relied. The paper presents an advanced technique that can compensate for the lack of reliable hurricane observations and can be utilized for any simulation period. Although only South China Sea region is examined, the approach can be applied to all other locations. This is because of the unchanged theoretical methodology for all case studies and all the required parameters can be searched and extracted from global databases. In this study, the empirical track model is chosen as the theoretical framework for its potential advantages over other techniques. A large database of synthetic tracks is modeled, starting with their initial point and ending with their landfall location or point of final dissipation over the sea. This approach is validated through comparisons between the hurricane statistics derived from the historical data and the simulated ones over the entire research area (i.e. the South China Sea). The results show an acceptable accuracy, even if the input data are short.

Published
2013-08-01
How to Cite
B. M., Nguyen,; GELDER, P. H. A. J. M, Van. HURRICANE RISK ASSESSMENT IN A LONG TEMPORAL SCALE. EACEF - International Conference of Civil Engineering, [S.l.], v. 1, n. 1, p. 051, aug. 2013. Available at: <http://proceeding.eacef.com/ojs/index.php/EACEF/article/view/300>. Date accessed: 06 aug. 2020.