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dc.contributor.authorSteele, E
dc.contributor.authorMikhalenko, Natalia
dc.contributor.authorSaulter, A
dc.contributor.authorFournier, N
dc.contributor.authorUpton, J
dc.date.accessioned2019-06-24T11:12:11Z
dc.date.available2019-06-24T11:12:11Z
dc.date.issued2019-04-26
dc.identifier.isbn9781613996416
dc.identifier.issn0160-3663
dc.identifier.urihttp://hdl.handle.net/10026.1/14379
dc.description.abstract

<jats:title /> <jats:p>Accurate forecasts of coastal erosion are essential for the effective management (operation and protection) of critical infrastructure such as gas terminals and shallow-buried nearshore pipelines, preventing the costly losses of production associated with storm damage or exposure. Traditionally, these predictions were the preserve of computationally-expensive, morphodynamic simulations of the three-dimensional structure of the beach surface, however recent developments in reduced-complexity ‘equilibrium’ models have been shown to skilfully hindcast coastal change in cross-shore and long-shore transport dominated environments more accurately, over much longer time-scales. The simplicity and stability of these models – expressed as a function of the incident wave power and the relative equilibrium in dimensionless fall velocity – make them particularly appropriate for assessing the current ‘health’ of the coastline in actionable terms, while unlocking their potential use in forecast mode. Here, we present such a system, forced by data from the Met Office Wave Ensemble Prediction System, capable of providing real-time probabilistic forecasts of important coastal indices (e.g. beach volume and shoreline position) out to seven days ahead. The system is calibrated using an extended Kalman Filter and becomes more accurate over time as it assimilates more observational measurements. Once calibrated, tests on unseen data from the University of Plymouth coastal monitoring station at Perranporth, UK, during Winter 2017/18 confirm it can accurately predict the impact of an extreme storm sequence on coastal erosion and subsequent recovery. This promises the potential for a new coastal management tool, able to be applied to other vulnerable locations.</jats:p>

dc.language.isoen
dc.publisherOTC
dc.titleProtection of Critical Oil and Gas Infrastructure via the Skilful Prediction of Coastal Erosion at Short Lead Times
dc.typeconference
dc.typeConference Proceeding
plymouth.date-start2019-05-06
plymouth.date-finish2019-05-09
plymouth.volume2019-May
plymouth.conference-nameOffshore Technology Conference
plymouth.publication-statusPublished
plymouth.journalDay 4 Thu, May 09, 2019
dc.identifier.doi10.4043/29542-ms
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA07 Earth Systems and Environmental Sciences
plymouth.organisational-group/Plymouth/Research Groups
plymouth.organisational-group/Plymouth/Research Groups/Marine Institute
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.4043/29542-ms
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.typeConference Paper/Proceeding/Abstract


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