Tidal wave height estimation on the southern coast of Java Island using Fuzzy Kalman Filter

Abstract

Considering that Indonesia has the second longest coastline in the world, information about tide height plays an important role. So far, tide height is only known at points where tidal station is available. Tide heights in areas without tidal station can be estimated using data assimilation method such as Kalman filter. In this study, the Fuzzy Kalman Filter (FKF) method is applied to a mathematical model of tidal waves to estimate tide height on the southern coast of Java. The estimation will be obtained at points with and without measurement data which are located in the coastal area between Pacitan and Sendang Biru tide stations. The points are determined with the help of a grid. After the grid is created, the depth at all points is obtained using interpolation and the initial and boundary conditions are determined. The FKF simulation results are compared with Ensemble Kalman Filter (EnKF) which has shown good performance in previous study. From the simulation results, it is found that the RMSE values of FKF are greater than those of EnKF which indicates poor estimation results. Therefore, the estimation is then done by combining fuzzy logic with EnKF which is called Fuzzy Ensemble Kalman Filter (FEnKF). Based on the simulation results, FEnKF gives smaller RMSE values than EnKF meaning FEnKF give better estimation of tide height than EnKF.