Benchmarking of Numerical Models for Wave Overtopping at Dikes with Shallow Mildly Sloping Foreshores: Accuracy versus Speed

TL;DR

This study evaluates the accuracy and computational efficiency of different numerical wave models for predicting overtopping at dikes with shallow foreshores, highlighting the importance of infragravity waves and empirical corrections.

Contribution

It provides a comparative analysis of phase-resolving and phase-averaged models, demonstrating that empirical corrections enable simpler models to achieve accuracy comparable to complex ones.

Findings

Neglecting infragravity waves leads to significant underestimation of overtopping.

More complex models do not necessarily yield more accurate results.

Empirical corrections allow phase-averaged models to match phase-resolving models' accuracy with less computational cost.

Abstract

To accurately predict the consequences of nearshore waves, coastal engineers often employ numerical models. A variety of these models, broadly classified as either phase-resolving or phase-averaged, exist; each with strengths and limitations owing to the physical schematization of processes within them. Models which resolve the vertical flow structure or the full wave spectrum (i.e. sea-swell (SS) and infragravity (IG) waves) are considered more accurate, but also more computationally demanding than those with approximations. Here, we assess the speed-accuracy trade-off of six well-known wave models for overtopping (q), under shallow foreshore conditions. The results demonstrate that: i) q is underestimated by an order of magnitude when IG waves are neglected; ii) using more computationally-demanding models does not guarantee more accurate results; and iii) with empirical corrections to account for IG waves, phase-averaged models like SWAN can perform on par, if not better than, phase-resolving models but with far less computational effort.