Wave overtopping at berm breakwaters: Review and sensitivity analysis of prediction models

Karthika Pillai, Amir Etemad-Shahidi, Charles Lemckert

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

This paper reviews the available models for the estimation of mean wave overtopping rate at berm breakwaters. A sensitivity analysis was conducted on selected models in order to study the influence of input variables on estimated overtopping discharge. The dimensionless crest freeboard is the most significant factor influencing the predicted overtopping rate. The sensitivity of overtopping to wave steepness varies from being insensitive, constant, or a function of dimensionless crest freeboard across the formulae analysed. The berm width and berm level (with respect to the still water level) have lower impact on the predicted overtopping compared to that of the crest freeboard. A case study on the sensitivity of predicted overtopping was carried out on Sirevag and Bakkafjordur berm breakwaters and it illustrated that the existing models are most sensitive to the variables of dimensionless crest freeboard, when it is greater than 1.0; and dimensionless berm width, when it is greater than 2.0. Additionally, the case study demonstrated inconsistencies among the models for predicted overtopping. The sensitivities of the estimated overtopping rates to the governing variables were compared with those obtained from experimental data. Among the models, the sensitivity estimations using the artificial neural network of Van Gent et al. (2007) [58] and the Lykke Andersen (2006) [32] formula were found to be in more reasonable agreement with those of the experimental data. The Van der Meer and Janssen (1994) [56] formula showed oversensitivity to the major governing variables. The results of this study throws light on the disparities in accounting the influence of variables, in the estimated overtopping rate at berm breakwaters, using the existing prediction models.

Original languageEnglish
Pages (from-to)1-21
Number of pages21
JournalCoastal Engineering
Volume120
DOIs
Publication statusPublished - 1 Feb 2017
Externally publishedYes

Fingerprint

Breakwaters
Sensitivity analysis
Water levels
Neural networks

Cite this

@article{e087e3afe59c465ab00070d9ed431eee,
title = "Wave overtopping at berm breakwaters: Review and sensitivity analysis of prediction models",
abstract = "This paper reviews the available models for the estimation of mean wave overtopping rate at berm breakwaters. A sensitivity analysis was conducted on selected models in order to study the influence of input variables on estimated overtopping discharge. The dimensionless crest freeboard is the most significant factor influencing the predicted overtopping rate. The sensitivity of overtopping to wave steepness varies from being insensitive, constant, or a function of dimensionless crest freeboard across the formulae analysed. The berm width and berm level (with respect to the still water level) have lower impact on the predicted overtopping compared to that of the crest freeboard. A case study on the sensitivity of predicted overtopping was carried out on Sirevag and Bakkafjordur berm breakwaters and it illustrated that the existing models are most sensitive to the variables of dimensionless crest freeboard, when it is greater than 1.0; and dimensionless berm width, when it is greater than 2.0. Additionally, the case study demonstrated inconsistencies among the models for predicted overtopping. The sensitivities of the estimated overtopping rates to the governing variables were compared with those obtained from experimental data. Among the models, the sensitivity estimations using the artificial neural network of Van Gent et al. (2007) [58] and the Lykke Andersen (2006) [32] formula were found to be in more reasonable agreement with those of the experimental data. The Van der Meer and Janssen (1994) [56] formula showed oversensitivity to the major governing variables. The results of this study throws light on the disparities in accounting the influence of variables, in the estimated overtopping rate at berm breakwaters, using the existing prediction models.",
keywords = "Artificial neural network, Berm breakwater, CLASH, Classification, Empirical formula, Sensitivity analysis, Wave overtopping",
author = "Karthika Pillai and Amir Etemad-Shahidi and Charles Lemckert",
year = "2017",
month = "2",
day = "1",
doi = "10.1016/j.coastaleng.2016.11.003",
language = "English",
volume = "120",
pages = "1--21",
journal = "Coastal Engineering",
issn = "0378-3839",
publisher = "Elsevier",

}

Wave overtopping at berm breakwaters: Review and sensitivity analysis of prediction models. / Pillai, Karthika; Etemad-Shahidi, Amir; Lemckert, Charles.

In: Coastal Engineering, Vol. 120, 01.02.2017, p. 1-21.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Wave overtopping at berm breakwaters: Review and sensitivity analysis of prediction models

AU - Pillai, Karthika

AU - Etemad-Shahidi, Amir

AU - Lemckert, Charles

PY - 2017/2/1

Y1 - 2017/2/1

N2 - This paper reviews the available models for the estimation of mean wave overtopping rate at berm breakwaters. A sensitivity analysis was conducted on selected models in order to study the influence of input variables on estimated overtopping discharge. The dimensionless crest freeboard is the most significant factor influencing the predicted overtopping rate. The sensitivity of overtopping to wave steepness varies from being insensitive, constant, or a function of dimensionless crest freeboard across the formulae analysed. The berm width and berm level (with respect to the still water level) have lower impact on the predicted overtopping compared to that of the crest freeboard. A case study on the sensitivity of predicted overtopping was carried out on Sirevag and Bakkafjordur berm breakwaters and it illustrated that the existing models are most sensitive to the variables of dimensionless crest freeboard, when it is greater than 1.0; and dimensionless berm width, when it is greater than 2.0. Additionally, the case study demonstrated inconsistencies among the models for predicted overtopping. The sensitivities of the estimated overtopping rates to the governing variables were compared with those obtained from experimental data. Among the models, the sensitivity estimations using the artificial neural network of Van Gent et al. (2007) [58] and the Lykke Andersen (2006) [32] formula were found to be in more reasonable agreement with those of the experimental data. The Van der Meer and Janssen (1994) [56] formula showed oversensitivity to the major governing variables. The results of this study throws light on the disparities in accounting the influence of variables, in the estimated overtopping rate at berm breakwaters, using the existing prediction models.

AB - This paper reviews the available models for the estimation of mean wave overtopping rate at berm breakwaters. A sensitivity analysis was conducted on selected models in order to study the influence of input variables on estimated overtopping discharge. The dimensionless crest freeboard is the most significant factor influencing the predicted overtopping rate. The sensitivity of overtopping to wave steepness varies from being insensitive, constant, or a function of dimensionless crest freeboard across the formulae analysed. The berm width and berm level (with respect to the still water level) have lower impact on the predicted overtopping compared to that of the crest freeboard. A case study on the sensitivity of predicted overtopping was carried out on Sirevag and Bakkafjordur berm breakwaters and it illustrated that the existing models are most sensitive to the variables of dimensionless crest freeboard, when it is greater than 1.0; and dimensionless berm width, when it is greater than 2.0. Additionally, the case study demonstrated inconsistencies among the models for predicted overtopping. The sensitivities of the estimated overtopping rates to the governing variables were compared with those obtained from experimental data. Among the models, the sensitivity estimations using the artificial neural network of Van Gent et al. (2007) [58] and the Lykke Andersen (2006) [32] formula were found to be in more reasonable agreement with those of the experimental data. The Van der Meer and Janssen (1994) [56] formula showed oversensitivity to the major governing variables. The results of this study throws light on the disparities in accounting the influence of variables, in the estimated overtopping rate at berm breakwaters, using the existing prediction models.

KW - Artificial neural network

KW - Berm breakwater

KW - CLASH

KW - Classification

KW - Empirical formula

KW - Sensitivity analysis

KW - Wave overtopping

UR - http://www.scopus.com/inward/record.url?scp=84996922123&partnerID=8YFLogxK

U2 - 10.1016/j.coastaleng.2016.11.003

DO - 10.1016/j.coastaleng.2016.11.003

M3 - Article

VL - 120

SP - 1

EP - 21

JO - Coastal Engineering

JF - Coastal Engineering

SN - 0378-3839

ER -