Storm Surge Prediction Based on Long Short-Term Memory Neural Network in the East China Sea

Kuo Chen,Ke Chen,Lei Wang,Jiadong Fan,Cuiping Kuang,Xuejian Han

doi:10.3390/app12010181

Abstract

As an area frequently suffering from storm surge, the Yangtze River Estuary in the East China Sea requires fast and accurate prediction of water level for disaster prevention and mitigation. Due to storm surge process being affected by the long-term and short-term correlation of multiple factors, this study attempts to introduce a data-driven idea into the water level prediction during storm surge. By collecting the observed meteorological data and water level data of 12 typhoons from 1986 to 2016 at the Lusi tidal station of Jiangsu Province, China near the north branch of the Yangtze River Estuary, a Long Short-Term Memory (LSTM) neural network model was constructed by using multi-factor time series to predict the water level during the storm surge period. This study concludes that the LSTM model performs precisely for 1 h prediction of water level during the storm surge period and it can provide a 15 h prediction of water level within a limited error, and the prediction performance of the LSTM model is visibly superior to the four traditional ML models by 41% in terms of Accuracy Coefficient.

Highlights

Storm surge is a complex atmosphere-ocean coupled process which is characterized by the sudden occurrence of rising water and waves
The 12 processes of storm surge with the meteorological data and the water level data which were recorded at Lusi tidal station in Jiangsu Province, China from 1986 to 2016 are used to train the hyperparameters of the Long Short-Term Memory (LSTM) model
Some scholars used neural network to predict the time-varying storm surge which is calculated by subtracting the astronomical tidal level from the total water level [57], the data used in this study is the total water level including the pure astronomical tidal level and the typhoon-induced water level due to that the key criterion usually considered by the marine management departments is the total water level, especially the peak water level prone to exceed the warning limit

Summary

Introduction

Storm surge is a complex atmosphere-ocean coupled process which is characterized by the sudden occurrence of rising water and waves. Typhoons or hurricanes are the most energetic atmospheric force acting on coastal and estuarine waters and are the most serious natural disaster among marine disasters, which would cause significant changes in hydrodynamics like water level or storm surge [5,6,7,8]. Sea level rise is considered as an important factor of storm surge. The sea level rise projected in this century by many researchers [13,14] will aggravate the threat from storm surge flooding, and the effects of sea level rise need to be considered to deal with the influence of climate changes on coastal areas. Irish et al (2008) analyzed the observed historical storm data along with the idealized numerical simulation data to find that storm surge increases with storm size, especially for the case of intense storms on very shallow slopes [15]

Methods

Results

Conclusion