Characterisation of sandy beach through morphological indicators and long-term modelling

Abstract

<p class="Standard"><span lang="EN-GB">Coasts are hosting most of the human population worldwide and hosts a large part of the economic activities. Among the various types of coastal environments, sandy beaches represent one third of the global shoreline of which a large proportion is eroding (Luijendijk <em>et al.</em>, 2018). This phenomenon is accelerating under the effect of climate change and the understanding and mitigation of the shoreline erosion is a fundamental issue in coastal engineering.</span></p> <p class="Standard"><span lang="EN-GB">In this contribution we analyse survey data from two well-documented Atlantic beaches: Duck (North Carolina, USA), a microtidal East-exposed beach and Truc Vert (Aquitaine, France) a meso/macrotidal West-exposed beach. A statistical analysis of the waves data over 2 to 3 decades provides useful information to evaluate the various possible morphodynamic beach states following Masselink & Short (1993) classification. This classification is based on the Dean number and the relative tidal range. Using the measured bathymetries, it is possible to verify the Masselink and Short classification. For example, using Duck data, a morphological analysis is performed on the 18 available bathymetries from the year 2019. These data illustrate the up-state and down-state sequences between reflective (summer) and dissipative (winter) states. In particular, the variability of the beach morphology increases significantly during intermediate beach states.</span></p> <p class="Standard"><span lang="EN-US">Applied to the two datasets, a modeling approach combining a one-line model, ShoreFor (Splinter<span class="apple-converted-space"> </span><em>et al.</em>, 2014), and 2D depth-averaged process-based model, XBeach (Roelvink<span class="apple-converted-space"> </span><em>et al.</em>, 2009), is envisaged. ShoreFor is run to predict<span class="apple-converted-space"> </span>shoreline and bar location (Splinter<span class="apple-converted-space"> </span><em>et al.</em>, 2018) and<span class="apple-converted-space"> </span>XBeach simulations are used on specific subsets of the entire computational window for intermediate 2D morphological state predictions.</span></p> <p class="Standard"><span lang="EN-GB"> </span><span lang="EN-GB"> </span></p> <p class="Standard"><span lang="EN-GB"> </span></p> <p class="Standard"><span lang="EN-GB"> </span></p> <p class="Standard"><span lang="EN-GB">Luijendijk, A., Hagenaars, G., Ranasinghe, R., Baart, F., Donchyts, G. and Aarninkhof, S. (2018), The State of the World’s Beaches, <em>Scientific Reports</em>, <strong>8</strong>(6641).</span></p> <p class="Standard"><span lang="EN-GB">Masselink, G. and Short, A. (1993), The Effect of Tide Range on Beach Morphodynamics and Morphology: A Conceptual Beach Model, <em>Journal of Coastal Research</em>, <strong>9</strong>(3), 785–800.</span></p> <p class="Standard"><span lang="EN-GB">Splinter, K.D., Turner, I.L., Davidson, M.A., Barnard, P., Castelle, B. and Oltman-Shay, J. (2014), A generalized equilibrium model for predicting daily to interannual shoreline response, <em>Journal of Geophysical Research: Earth Surface</em>, <strong>119</strong>, 1936–1958.</span></p> <p class="Standard"><span lang="EN-GB">Splinter, K.D., Gonzalez, M.V.G., Oltman-Shay, J., Rutten, J., Holman, R. (2018), Observations and modelling of shoreline and multiple sandbar behaviour on a high-energy meso-tidal beach, <em>Continental Shelf Research</em>, <strong>159</strong>, 33—45.</span></p> <p><span lang="EN-GB">Roelvink, D., Reniers, A., van Dongeren, A., van Thiel de Vries, J., McCall, R., and Lescinski, J. (2009), Modelling storm impacts on beaches, dunes and barrier islands, <em>Coastal Engineering</em>, <strong>56</strong>(11–12), 1133–1152.</span></p>