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Benchmarking of numerical models for wave overtopping at dikes with shallow mildly sloping foreshores: Accuracy versus speed Lashley, C.; Zanuttigh, B.; Bricker, J.; van der Meer, J.; Altomare, C.; Suzuki, T.; Roeber, V.; Oosterlo, P. (2020). Benchmarking of numerical models for wave overtopping at dikes with shallow mildly sloping foreshores: Accuracy versus speed. Environ. Model. Softw. 130: 104740. https://dx.doi.org/10.1016/j.envsoft.2020.104740 In: Environmental Modelling & Software. Elsevier: Oxford. ISSN 1364-8152; e-ISSN 1873-6726, meer

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Beschikbaar in	Auteurs
VLIZ: Open access 360794 [ download pdf ] Waterbouwkundig Laboratorium: Open Repository 345949 [ download pdf ]

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Trefwoorden

Coastal protection > Coastal safety against extreme storms > Sea dikes Numerical modelling Marien/Kust

Author keywords

Infragravity wave; OpenFOAM; BOSZ; XBeach; SWASH; SWAN

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Auteurs		Top
Lashley, C. Zanuttigh, B. Bricker, J.D. Van der Meer, J.	Altomare, C., meer Suzuki, T., meer Roeber, V. Oosterlo, P.

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Abstract

Practitioners often employ diverse, though not always thoroughly validated, numerical models to directly or indirectly estimate wave overtopping (q) at sloping structures. These models, broadly classified as either phase-resolving or phase-averaged, each have 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 more computationally demanding than those with approximations. Here, we assess the speed-accuracy trade-off of six well-known models for estimating (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 improved accuracy; and iii) with empirical corrections to incorporate IG waves, phase-averaged models like SWAN can perform on par, if not better than, phase-resolving models but with far less computational effort.

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