Conditional Probability Approach of Assessing the Risk of High Ocean Waves

Abstract

The objective of this paper is to develop a framework to assess the potential risk for high ocean waves detected by high frequency radar systems. High ocean waves due to earthquakes, strong wind, and/or other climate conditions have become one of the major natural hazards. Various coastal disasters including beach erosion along the shoreline are also caused by high waves. In order to decrease the damage caused by coastal disasters, it is essential to predict high ocean waves and assess their risk. Using the Bayesian approach, conditional probability of exceeding high ocean wave threshold is estimated with the predicted wave heights, which are calculated based on the measured data from high frequency radar systems. The data used is drawn from two Wellen radar systems that were installed in Samcheok City, Gangwon-do on the East Coast of South Korea. Additionally, Monte Carlo analysis is conducted to estimate conditional probability of exceeding the given threshold against coastal hazards. The preliminary results demonstrate that the proposed framework is effective in estimating vulnerability due to high ocean waves. It is expected that the proposed framework will provide adequate warning for people to evacuate from threatened coastal areas. Hence, this approach will directly contribute to the reduction of injuries and deaths due to natural disasters by supplying near real-time data of the environment around coastal areas.