Abstract

The abrupt rise in local sea level due to storm tide caused by an approaching tropical cyclone could cause severe flooding and devastating influence to low-lying regions of a coastal city. Studies show that many empirical offline modeling techniques are useful tools for storm tide simulation, e.g. the Artificial Neural Network (ANN). However, these techniques are non-adaptive and retraining is necessary when new data are available. The present study introduces an adaptive empirical model for improvement. It is a dynamic linear regression model with the harmonic tidal prediction, wind speed, wind direction and atmospheric pressure as the model input parameters. Application of the model to simulate the storm tide variation of forty tropical cyclone cases in Macau gives values of the root-mean-squared error and the coefficient of determination ranging between 0.08~0.20m and 0.82~0.98, respectively. In addition, the proposed model could capture the storm tide maxima of the seventeen flooding cases among the forty with a root-mean-squared error of 0.15m. Simulation of the corresponding peak arrival for the flooding cases is mostly within one hour of the actual one and at most two hours. Therefore, the proposed adaptive model is a promising tool for storm tide simulation.

Highlights

  • INTRODUCTIONTropical cyclone can cause persistent onshore winds pushing the water body towards inland (wind set-up) as well as the local sucking of water upwards near/within the low pressure center (inverted barometer effect)

  • Tropical cyclone can cause persistent onshore winds pushing the water body towards inland as well as the local sucking of water upwards near/within the low pressure center

  • The proposed Kalman filter based storm tide simulation model of the kth hour is a linear combination of the astronomical tide prediction at the kth hour, the measured atmospheric pressure drop at the kth hour, the measured wind speed (

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Summary

INTRODUCTION

Tropical cyclone can cause persistent onshore winds pushing the water body towards inland (wind set-up) as well as the local sucking of water upwards near/within the low pressure center (inverted barometer effect). Strong positive correlation between the north-south component and the storm surge starts at around k+3th hour and it reaches its maximum when the time difference is seven to eight hours. Through these correlation patterns, it can be concluded that the easterly winds are responsible for the wind setup of first few hours. The proposed Kalman filter based storm tide simulation model of the kth hour is a linear combination of the astronomical tide prediction at the kth hour, the measured atmospheric pressure drop at the kth hour, the measured wind speed

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