<?xml version="1.0"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Modelling cross-shore shoreline change on multiple timescales and their interactions</dc:title>
  <dc:creator>Schepper, R.</dc:creator>
  <dc:creator>/Almar, Rafa&#xEB;l</dc:creator>
  <dc:creator>Bergsma, E.</dc:creator>
  <dc:creator>de Vries, S.</dc:creator>
  <dc:creator>Reniers, A.</dc:creator>
  <dc:creator>Davidson, M.</dc:creator>
  <dc:creator>Splinter, K.</dc:creator>
  <dc:subject>equilibrium shoreline modelling</dc:subject>
  <dc:subject>ShoreFor</dc:subject>
  <dc:subject>cross-shore sediment</dc:subject>
  <dc:subject>transport</dc:subject>
  <dc:subject>multiple timescales</dc:subject>
  <dc:description>In this paper, a new approach to model wave-driven, cross-shore shoreline change incorporating multiple timescales is introduced. As a base, we use the equilibrium shoreline prediction model ShoreFor that accounts for a single timescale only. High-resolution shoreline data collected at three distinctly different study sites is used to train the new data-driven model. In addition to the direct forcing approach used in most models, here two additional terms are introduced: a time-upscaling and a time-downscaling term. The upscaling term accounts for the persistent effect of short-term events, such as storms, on the shoreline position. The downscaling term accounts for the effect of long-term shoreline modulations, caused by, for example, climate variability, on shorter event impacts. The multi-timescale model shows improvement compared to the original ShoreFor model (a normalized mean square error improvement during validation of 18 to 59%) at the three contrasted sandy beaches. Moreover, it gains insight in the various timescales (storms to inter-annual) and reveals their interactions that cause shoreline change. We find that extreme forcing events have a persistent shoreline impact and cause 57-73% of the shoreline variability at the three sites. Moreover, long-term shoreline trends affect short-term forcing event impacts and determine 20-27% of the shoreline variability.</dc:description>
  <dc:date>2021</dc:date>
  <dc:type>text</dc:type>
  <dc:identifier>https://www.documentation.ird.fr/hor/fdi:010082246</dc:identifier>
  <dc:identifier>fdi:010082246</dc:identifier>
  <dc:identifier>Schepper R., Almar Rafa&#xEB;l, Bergsma E., de Vries S., Reniers A., Davidson M., Splinter K.. Modelling cross-shore shoreline change on multiple timescales and their interactions. 2021, 9 (6),  582 [27 p.]</dc:identifier>
  <dc:language>EN</dc:language>
  <dc:coverage>AUSTRALIE</dc:coverage>
  <dc:coverage>VIET NAM</dc:coverage>
  <dc:coverage>NOUVELLE ZELANDE</dc:coverage>
</oai_dc:dc>
