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Performance of a data-driven technique applied to changes in wave height and its effect on beach response

Horrillo-Caraballo, José M., Karunarathna, Harshinie, Pan, Shunqi ORCID: and Reeve, Dominic 2016. Performance of a data-driven technique applied to changes in wave height and its effect on beach response. Water Science and Engineering 9 (1) , pp. 42-51. 10.1016/j.wse.2016.02.006

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In this study the medium-term response of beach profiles was investigated at two sites: a gently sloping sandy beach and a steeper mixed sand and gravel beach. The former is the Duck site in North Carolina, on the east coast of the USA, which is exposed to Atlantic Ocean swells and storm waves, and the latter is the Milford-on-Sea site at Christchurch Bay, on the south coast of England, which is partially sheltered from Atlantic swells but has a directionally bimodal wave exposure. The data sets comprise detailed bathymetric surveys of beach profiles covering a period of more than 25 years for the Duck site and over 18 years for the Milford-on-Sea site. The structure of the data sets and the data-driven methods are described. Canonical correlation analysis (CCA) was used to find linkages between the wave characteristics and beach profiles. The sensitivity of the linkages was investigated by deploying a wave height threshold to filter out the smaller waves incrementally. The results of the analysis indicate that, for the gently sloping sandy beach, waves of all heights are important to the morphological response. For the mixed sand and gravel beach, filtering the smaller waves improves the statistical fit and it suggests that low-height waves do not play a primary role in the medium-term morphological response, which is primarily driven by the intermittent larger storm waves.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Subjects: T Technology > TC Hydraulic engineering. Ocean engineering
Uncontrolled Keywords: Beach profile; Canonical correlation analysis; Data-driven technique; Empirical orthogonal function; Forecast; Statistical model; Wave height threshold
Publisher: Elsevier
ISSN: 1674-2370
Date of First Compliant Deposit: 13 April 2016
Date of Acceptance: 6 January 2016
Last Modified: 01 Nov 2022 09:44

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