Water Science and Engineering 2016, 9(1) 14-20 DOI:   http://dx.doi.org/10.1016/j.wse.2015.10.003  ISSN: 1674-2370 CN: 32-1785/TV

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EOF method
coastal morphological change
long-term prediction
process-based numerical model
shore-parallel breakwater
Fernando Alvarez
Shun-qi Pan
Article by Fernando Alvarez
Article by Shun-qi Pan

Predicting coastal morphological changes with empirical orthogonal functionmethod

Fernando Alvarez*, Shun-qi Pan

Hydro-environmental Research Centre, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK


In order to improve the accuracy of prediction when using the empirical orthogonal function (EOF) method, this paper describes a novel approach for two-dimensional (2D) EOF analysis based on extrapolating both the spatial and temporal EOF components for long-term prediction of coastal morphological changes. The approach was investigated with data obtained from a process-based numerical model, COAST2D, which was applied to an idealized study site with a group of shore-parallel breakwaters. The progressive behavior of the spatial and temporal EOF components, related to bathymetric changes over a training period, was demonstrated, and EOF components were extrapolated with combined linear and exponential functions for long-term prediction. The extrapolated EOF components were then used to reconstruct bathymetric changes. The comparison of the reconstructed bathymetric changes with the modeled results from the COAST2D model illustrates that the presented approach can be effective for long-term prediction of coastal morphological changes, and extrapolating both the spatial and temporal EOF components yields better results than extrapolating only the temporal EOF component.

Keywords EOF method   coastal morphological change   long-term prediction   process-based numerical model   shore-parallel breakwater  
Received 2015-06-18 Revised 2015-10-21 Online: 2016-01-31 
DOI: http://dx.doi.org/10.1016/j.wse.2015.10.003
Corresponding Authors:
Email: alvarezmartinezf@cardiff.ac.uk
About author:


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