Enhancing Tidal Wave Predictions for the Estuary of the Nakdong River Using a Fixed-Lag Smoother

Abstract

The prediction of tidal waves is essential for improving not only our understanding of the hydrological cycle at the boundary between the land and ocean but also energy production in coastal areas. As tidal waves are affected by various factors, such as astronomical, meteorological, and hydrological effects, the prediction of tidal waves in estuaries remains uncertain. In this study, we present a novel method that can be used to improve short-term tidal wave prediction using a fixed-lag smoother based on sequential data assimilation (DA). The proposed method was implemented for tidal wave predictions of the estuary of the Nakdong River. As a result, the prediction accuracy was improved by 63.9% through DA and calibration using regression. Although the accuracy of the DA diminished with the increasing forecast lead times, the 1 h lead forecast based on DA still showed a 44.4% improvement compared to the open loop without DA. Moreover, the optimal conditions for the fixed-lag smoother were analyzed in terms of the order of the smoothing function and the length of the assimilation window and forecast leads time. It was suggested that the optimal DA configuration could be obtained with the 8th-order polynomial as the smoothing function using past and future DA assimilation windows assimilated 6 h or longer.