COMPARATIVE EVALUATION OF ARTIFICIAL NEURAL NETWORK AND MIKE 21 IN ESTIMATING STORM SURGE LEVEL

Abstract

Tropical cyclone or storm near the coast generates a local rise in sea level, called storm surge. There are two general approaches that have been used to estimate sea level in storm conditions; statistical modeling and numerical modeling. The aim of this paper is to find an effective model between MIKE 21 - numerical model and an Artificial Neural Network (ANN) model in predicting sea level height in Qui Nhon, Vietnam during four storm events: Ketsana-2009, SonTinh- 2012, Nari-2013 and Wutip – 2013. The results from the two models were compared with observed sea level data in order to evaluate their respective performances. The results further indicate that the predictions from ANN and MIKE 21 model match well with the observed data. The verification shows that the neural network models have the potential for successful application in local water level forecasting systems.