Storm-surge prediction at the Tanshui estuary: development model for maximum storm surges

Abstract

Abstract. This study applies artificial networks, including both the supervised multilayer perception neural network and the radial basis function neural network to the prediction of storm-surges at the Tanshui estuary in Taiwan. The optimum parameters for the prediction of the maximum storm-surges based on 22 previous sets of data are discussed. Two different neural network methods are adopted to build models for the prediction of storm surges and the importance of each factor is also discussed. The factors relevant to the maximum storm surges, including the pressure difference, maximum wind speed and wind direction at the Tanshui Estuary and the flow rate at the upstream station, are all investigated. These good results can further be applied to build a neural network model for prediction of storm surges with time series data.