Numerical simulation of wave-induced morphology evolution

Abstract

This paper presents an integrated coastal engineering numerical model. The model simulates the linear wave propagation, wave-induced circulation, sediment transport and bed morphology evolution. The model consists of three main modules:Wave-LS, Wave-L and Coast. The large-scale module Wave-LS is based on the numerical solution of the directional wave energy balance equation. The near-shore wave transformation module Wave-L is based on the hyperbolic-type mild slope equation and is valid for a compound wave field near coastal structures where the waves are subjected to the combined effects of shoaling, refraction, diffraction, reflection (total and partial) and breaking. Radiation stress components (estimated from the large-scale module as well as from the hyperbolic wave module) drive the depth-averaged circulation module Coast for the description of the near-shore currents and sediment transport in the surf and swash zone. The module Coast is coupled with a three-dimensional bed evolution module to predict coastal bathymetry changes.

Accelerating Predictions of Morphological Bed Evolution by Combining Numerical Modelling and Artificial Neural Networks

“…e T e cos a e sin a e,b = ∑ f i H 2 i T i cos a i sin a i,b (11) with H e [m] being the annual equivalent wave height, T e [s] the annual equivalent wave period, and a e [rad] denotes the yearly equivalent incidence wave angle, with the subscript "b" denoting the value at the breaker line. In the right-hand side of Equation (11) the subscript "i" denotes individual wave events, with f i being the frequency of occurrence of each sea-state.…”

“…Considering that the wave angles are identical on the right and left-hand side of Equation (11), it can be rewritten as:…”

“…Out of these techniques, the one commonly employed by coastal engineers is wave input reduction [5][6][7][8][9], a procedure aiming to reduce the sheer amount of forcing input of the coastal area models by smartly selecting wave representatives able to reproduce the morphological changes induced by the full set of conditions. In the past decades, several studies have been carried out implementing various methods of wave input reduction enabling the simulation of the morphological evolution of coastal features from years to decades [8][9][10][11][12] and thoroughly investigating their performance.…”

“…The authors in [12] evaluated the performance of the K-Means clustering algorithm as a viable alternative to the binning input reduction methods and examined various enhancements to improve model results. An older, but still widely implemented branch of input reduction considers the estimation of representative or "equivalent" wave characteristics [5,10,11,13] by considering directional bins of fixed size and selecting the representatives by conserving the longshore sediment transport rate over each bin.…”

Editorial

“…The authors describe how they have taken account of best practice from both within their own country, and that applied elsewhere in the world, to develop a shoreline management approach for the Galicia region. Karambas et al (2013) look at the issue of coastal change from a different perspective, providing details of further advances in the numerical modelling of morphological evolution. This describes the simulation of wave propagation, wave-induced circulation, sediment transport and bed morphological evolution in the vicinity of coastal structures -an area that numerical models have in the past struggled to reproduce accurately.…”