Uncertainties in shoreline projections to 2100 at Truc Vert beach (France): Unravelling the role of sea-level rise and equilibrium model assumptions
Authors: D'Anna Maurizio , Castelle Bruno , Idier Déborah , Rohmer Jeremy , Le Cozannet Gonéri , Thieblemont Rémi , Bricheno Lucy 
Published: March 2021

&lt;p&gt;Most sandy coasts worldwide are under chronic erosion, which increasingly put at risk coastal communities. In the context of adaptation to climate change and sea-level rise (SLR), predictions of shoreline evolution patterns are critical for decision-making. Sandy shorelines are highly dynamic environments, which respond to multiple complex processes interacting at different spatial and temporal scales, making shoreline predictions challenging, especially on long time scales (decades and centuries). However, modelling shoreline predictions inherit uncertainties in the primary driver boundary conditions (e.g. sea-level rise and wave forcing) as well as uncertainties related to model assumptions and/or misspecifications of the physics. In this work, we analyze the uncertainties associated with shoreline evolution by 2100 of the high-energy, cross-shore transport dominated, sandy beach of Truc Vert (France).&amp;#160; Using&amp;#160; two equilibrium shoreline models based on different disequilibrium principles, and the Bruun Rule, we explicitly resolved wave-driven shoreline change produced continuous probabilistic predictions of the Truc Vert shoreline evolution to 2100 for two carbon emission scenarios (RCP 8.5 and 4.5), incorporating uncertainties related to SLR, depth of closure, and model free parameters. The shoreline models were forced with continuous wave projection time series, issued by the National Oceanography Center (UK) for the RCP 4.5 and 8.5 scenarios, based on a single global climate model. &amp;#160;We assigned a probability distribution to each uncertain input variable. For both shoreline models, an optimization algorithm was used to identify all the realistic combinations of model free parameters leading to a skillful hindcast against 8 years of in situ shoreline data. A Gaussian distribution was assigned to the yearly probabilistic SLR estimates based on SROCC to 2100, and depth of closure. We further addressed the relative impact of each source of uncertainty on the model results performing a Global Sensitivity Analysis (GSA). The results show that, for both RCP scenarios, shoreline response position during the first half of the century is mainly sensitive to the equilibrium model parameters, with the influence of SLR emerging in the second half of the century. The results also reflect the strong relation between the model parameters uncertainties and the interdecadal variability of wave conditions. Using a single wave time series, such variability and related chronology has a much stronger impact on shoreline change with the Splinter model than the Yates model, highlighting that the choice of the modelling approach is critical to future shoreline change estimates in changing wave climates. We also emphasize the need for more continuous wave projections in order to generate ensemble wave time series and include uncertainty in future wave conditions.&lt;/p&gt;