A storm surge projection and disaster risk assessment model for China coastal areas

Abstract

Storm surge is one of the most devastating coastal disasters in China. The average value of the direct economic loss caused by storm surge is 10.7 billion RMB in the last 5 years (2011–2015). There are urgent needs to develop a simple and fast projection and assessment model with less calculation time when facing a storm surge threat and to perform necessary calculation before the storm surge potential risk appears. To achieve that, this paper utilizes the extended Kalman filter (EKF) method to project essential indicators (assessment indicators), i.e., property losses and loss of lives over the process of storm surge risk management based on field observations and measurement indicators. The historical data from 1989 to 2014 are collected and processed according to public data sources. The inherent relationships between the indicators are determined as a preparation of the model establishment, and after that, the EKF storm surge projection model is established. The results of the model in terms of the assessment indicators meet the general trend of the historical data, and the validity of the projection function of the model is verified. A comparable projection by applying artificial neural networks is implemented which shows the results of the EKF model had better accuracy and stability.