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Prediction of beach morphological changes using a data-based approach

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Prediction of beach morphological changes using a data-based approach. / Gunawardena, Yohama; Ilic, Suzana; Pinkerton, Harry et al.
Proceedings of the 30th Internatinal Conference on Coastal Engineering 2006. World Scientific Publishing, 2006. p. 3168-3177.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Gunawardena, Y, Ilic, S, Pinkerton, H & Romanowicz, R 2006, Prediction of beach morphological changes using a data-based approach. in Proceedings of the 30th Internatinal Conference on Coastal Engineering 2006. World Scientific Publishing, pp. 3168-3177. https://doi.org/10.1142/9789812709554_0266

APA

Gunawardena, Y., Ilic, S., Pinkerton, H., & Romanowicz, R. (2006). Prediction of beach morphological changes using a data-based approach. In Proceedings of the 30th Internatinal Conference on Coastal Engineering 2006 (pp. 3168-3177). World Scientific Publishing. https://doi.org/10.1142/9789812709554_0266

Vancouver

Gunawardena Y, Ilic S, Pinkerton H, Romanowicz R. Prediction of beach morphological changes using a data-based approach. In Proceedings of the 30th Internatinal Conference on Coastal Engineering 2006. World Scientific Publishing. 2006. p. 3168-3177 doi: 10.1142/9789812709554_0266

Author

Gunawardena, Yohama ; Ilic, Suzana ; Pinkerton, Harry et al. / Prediction of beach morphological changes using a data-based approach. Proceedings of the 30th Internatinal Conference on Coastal Engineering 2006. World Scientific Publishing, 2006. pp. 3168-3177

Bibtex

@inproceedings{8b743001f54b44b89b7409d25c5c1775,
title = "Prediction of beach morphological changes using a data-based approach",
abstract = "A data-based approach using linear transfer functions (TF) was adopted to predict the evolution of the nearshore beach profile volume at Duck, North Carolina, using different wave forcing variables. The best TF model relation was found with the squared monthly average direction resolved significant wave heights. This TF model explained 76% of the variance of the data and produced a very good fit of the long-term trend in beach volume. This suggests that the long-term behavior of the bulk morphology of the beach profile is strongly influenced by the monthly average wave conditions. Complimentary long-term patterns in behavior were also observed on comparing the beach morphology and wave data. The fit of this TF model was improved by including the inputs of past alongshore sediment exchanges between adjacent profiles. Here, the TF model reproduced 92% of the variance in the volume data and fitted the long-term trend as well as some short-term behavior. This model gave very good forecasts of beach volume over a 5 year period. Thus, the linear TF modeling approach shows strong potential for predicting beach morphological changes.",
author = "Yohama Gunawardena and Suzana Ilic and Harry Pinkerton and Renata Romanowicz",
year = "2006",
doi = "10.1142/9789812709554_0266",
language = "English",
isbn = "9789812706362 ",
pages = "3168--3177",
booktitle = "Proceedings of the 30th Internatinal Conference on Coastal Engineering 2006",
publisher = "World Scientific Publishing",

}

RIS

TY - GEN

T1 - Prediction of beach morphological changes using a data-based approach

AU - Gunawardena, Yohama

AU - Ilic, Suzana

AU - Pinkerton, Harry

AU - Romanowicz, Renata

PY - 2006

Y1 - 2006

N2 - A data-based approach using linear transfer functions (TF) was adopted to predict the evolution of the nearshore beach profile volume at Duck, North Carolina, using different wave forcing variables. The best TF model relation was found with the squared monthly average direction resolved significant wave heights. This TF model explained 76% of the variance of the data and produced a very good fit of the long-term trend in beach volume. This suggests that the long-term behavior of the bulk morphology of the beach profile is strongly influenced by the monthly average wave conditions. Complimentary long-term patterns in behavior were also observed on comparing the beach morphology and wave data. The fit of this TF model was improved by including the inputs of past alongshore sediment exchanges between adjacent profiles. Here, the TF model reproduced 92% of the variance in the volume data and fitted the long-term trend as well as some short-term behavior. This model gave very good forecasts of beach volume over a 5 year period. Thus, the linear TF modeling approach shows strong potential for predicting beach morphological changes.

AB - A data-based approach using linear transfer functions (TF) was adopted to predict the evolution of the nearshore beach profile volume at Duck, North Carolina, using different wave forcing variables. The best TF model relation was found with the squared monthly average direction resolved significant wave heights. This TF model explained 76% of the variance of the data and produced a very good fit of the long-term trend in beach volume. This suggests that the long-term behavior of the bulk morphology of the beach profile is strongly influenced by the monthly average wave conditions. Complimentary long-term patterns in behavior were also observed on comparing the beach morphology and wave data. The fit of this TF model was improved by including the inputs of past alongshore sediment exchanges between adjacent profiles. Here, the TF model reproduced 92% of the variance in the volume data and fitted the long-term trend as well as some short-term behavior. This model gave very good forecasts of beach volume over a 5 year period. Thus, the linear TF modeling approach shows strong potential for predicting beach morphological changes.

U2 - 10.1142/9789812709554_0266

DO - 10.1142/9789812709554_0266

M3 - Conference contribution/Paper

SN - 9789812706362

SP - 3168

EP - 3177

BT - Proceedings of the 30th Internatinal Conference on Coastal Engineering 2006

PB - World Scientific Publishing

ER -