Estimation of longshore sediment transport using video monitoring shoreline data
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Cited 2 time in
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Title
- Estimation of longshore sediment transport using video monitoring shoreline data
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Author(s)
- Oh, Jung-Eun; Chang, Yeon S.; Jeong, Weon Mu; Kim, Ki Hyun; Ryu, Kyong Ho
- KIOST Author(s)
- Chang, Yeon S.(장연식); Jeong, Weon Mu(정원무); Ryu, Kyong Ho(류경호)
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Alternative Author(s)
- 오정은; 장연식; 정원무; 류경호
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Publication Year
- 2020-08
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Abstract
- Video monitoring systems (VMS) have been used for beach status observation but are not effective for examining detailed beach processes as they only measure changes to the shoreline and backshore. Here, we extracted longshore sediment transport (LST) from VMS in order to investigate long- and short-term littoral processes on a pocket beach. LST estimated by applying one-line theory, wave power, and the oblique angle of incident waves were used to understand shoreline changes caused by severe winter storms. The estimated LST showed good agreement with the shoreline changes because the sediments were trapped at one end of the pocket beach and the alongshore direction of transported sediments was corresponded to the direction of LST. The results also showed that the beach that was severely eroded during storms was also rapidly recovered following the evolution of LST, which indicates that the LST may play a role in the recovery process while the erosion was mainly caused by the cross-shore transport due to storm waves. After the beach was nourished, beach changes became more active, even under lower wave energy conditions, owing to the equilibrium process. The analysis presented in this study could be applied to study inhomogeneous beach processes at other sites. © 2020 by the authors.
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ISSN
- 2077-1312
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URI
- https://sciwatch.kiost.ac.kr/handle/2020.kiost/38591
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DOI
- 10.3390/JMSE8080572
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Bibliographic Citation
- Journal of Marine Science and Engineering, v.8, no.8, 2020
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Publisher
- MDPI AG
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Keywords
- Beach nourishment; Beach response; Longshore sediment transport; Storm waves; Video monitoring system
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Type
- Article
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Language
- English
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Document Type
- Article
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