Distribution of individual wave overtopping volumes at rubble mound seawalls

Distribution of individual wave overtopping volumes at rubble mound seawalls

Koosheh, Ali (Griffith University)
Etemad-Shahidi, Amir (Griffith University; Edith Cowan University)
Cartwright, Nick (Griffith University)
Tomlinson, Rodger (Griffith University)
van Gent, M.R.A. (TU Delft Coastal Engineering; Deltares)

2022

For a safe design of a rubble mound seawall, overtopping characteristics such as the mean overtopping discharge (q) and the maximum individual overtopping volume (V_max) should be limited. Unlike q, the estimation of V_max is more complex and requires a wave-by-wave analysis of overtopping as well as a statistical analysis. The present study contributes to the knowledge of the distribution of individual overtopping volumes and the estimation of V_max at rubble mound seawalls. A total of 135, small-scale 2D physical model tests were conducted across a practical range of crest freeboards and considered the slopes of 1:1.5 and 1:2. The well-known 2-parameter Weibull and Exponential distributions were first fitted to the experimental data to estimate the V_max. Different approaches to sample the observed distribution of wave-by-wave overtopping volumes were evaluated including a threshold method using the top 10%, 30%, and 50% of individual overtopping volumes, and a method that applies a greater weighting to the larger events. For both Weibull and Exponential distributions, the weighted method was found to be the best one providing a 23% and 17% decrease in scatter index (SI) values compared to the best of existing methods. To facilitate the estimation of V_max for design purposes, a simple empirical formula was developed as a function of the dimensionless mean overtopping discharge (q*) and the number of overtopping waves (N_ow). This formula with SI = 37% outperformed the distribution-based methods as well as the best of existing formulae for V_max. In the case of the normalised bias (NBIAS), the distribution methods underestimated V_max by −21% (Weibull) and −31% (Exponential) whereas the new formula yielded NBIAS = −6%.

Exponential distribution
Individual wave overtopping volumes distribution
Probability of overtopping
Rubble mound seawall
Weibull distribution

http://resolver.tudelft.nl/uuid:3860289a-f096-49be-a0e8-d44fc4915f2e

https://doi.org/10.1016/j.coastaleng.2022.104173

2023-07-01

0378-3839

Coastal Engineering, 177

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2022 Ali Koosheh, Amir Etemad-Shahidi, Nick Cartwright, Rodger Tomlinson, M.R.A. van Gent