On the prediction of beach changes by a new 2-D empirical eigenfunction model.

Abstract

A new two-dimensional (2-D) empirical eigenfunction model is developed for the prediction of beach changes due to cross-shore and longshore sediment transports. Beach profile data, measured every two months along six segmented detached breakwaters, were analyzed to generate spatial and temporal orthogonal eigenfunctions. The temporal eigenfunctions are predicted through the use of the Markov process and a linear regression method as a time series to forecast changes in the sea bottom.This model simplifies the complex representation of eigenfunctions presented by Hsu et al. (1986), and takes advantage of this simplication to reduce artificial errors and save computer time for further applications. The predictability of the proposed model is examined through field observations as well as predictions of existing empirical eigenfunction models. The result shows that this 2-D empirical eigenfunction model is efficient and advisable for the prediction of the variability of beach changes around coastal structures.