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Annual prediction of shoreline erosion and subsequent recovery

Title: Annual prediction of shoreline erosion and subsequent recovery
Authors: Davidson, MA; Turner, IL; Splinter, KD; Harley, MD
Source: urn:ISSN:0378-3839 ; urn:ISSN:1872-7379 ; Coastal Engineering, 130, 14-25
Publisher Information: Elsevier
Publication Year: 2017
Collection: UNSW Sydney (The University of New South Wales): UNSWorks
Subject Terms: 37 Earth Sciences; 4015 Maritime Engineering; 40 Engineering; 13 Climate Action; anzsrc-for: 37 Earth Sciences; anzsrc-for: 4015 Maritime Engineering; anzsrc-for: 40 Engineering; anzsrc-for: 0403 Geology; anzsrc-for: 0405 Oceanography; anzsrc-for: 0905 Civil Engineering; anzsrc-for: 3705 Geology; anzsrc-for: 4005 Civil engineering
Description: Prediction of the potential impact of an extreme storm-sequence on coastal resilience and the subsequent rate of post-storm recovery is a fundamental goal for coastal scientists, engineers and managers alike. This paper presents a methodology for forecasting shoreline change over annual time-scales, including the prediction of the potential impact of storm sequences and the subsequent post-storm recovery. The methodology utilises an archive of measured or modelled wave data to produce multiple (≈10 3 ) synthetic hydrodynamic forcing time-series to drive an equilibrium shoreline model in a Monte Carlo simulation. A Generalised Extreme Value (GEV) analysis is conducted on the resulting shoreline predictions in order to extrapolate the magnitude of shoreline displacements for predefined return periods. Three shoreline displacement bands are defined in a ‘traffic light’ system, to aid the interpretation of results; a green (normal) band characterising shoreline displacements expected within the typical decade, an amber (high) band defining events with return periods outside the decadal recurrence threshold but within return periods
Document Type: article in journal/newspaper
Language: unknown
Relation: http://purl.org/au-research/grants/arc/DP150101339; https://hdl.handle.net/1959.4/unsworks_47327; https://doi.org/10.1016/j.coastaleng.2017.09.008
DOI: 10.1016/j.coastaleng.2017.09.008
Availability: https://hdl.handle.net/1959.4/unsworks_47327; https://doi.org/10.1016/j.coastaleng.2017.09.008
Rights: metadata only access ; http://purl.org/coar/access_right/c_14cb ; CC-BY-NC-ND ; https://creativecommons.org/licenses/by-nc-nd/4.0/
Accession Number: edsbas.CBB81D
Database: BASE