The south coast of the UK is identified as a location where significant wave swell components are present within the regional wave climate. During the winters of 2006 and 2014, several sites along the south coast of the UK were subject to significant damages where flood events were recorded. These sea states were characterised by having a double-peaked wave spectra, observing a connection between wave spectrum shape and beach response. A two-dimensional (2D) physical model study was carried out to investigate the effect of gravel beach profile response under wave spectra characterised by swell-wave and wind-wave periods in various combinations. The physical model results showed the effect of bimodal wave spectrum on beach crest erosion and were compared with the parametric model Shingle and the numerical model XBeach-G. Based on this 2D physical model study, a new parametric model, Shingle-B, was derived and an online tool developed and made available on the website for the National Network of Regional Coastal Monitoring Programmes of England. This new tool has been validated at two sites in the south of England where field data of both waves and profiles were available.
Rapid deterministic modelling of shoreline evolution at regional and coastal-scheme scale enables Monte-Carlo simulations by which long-term shoreline statistics can be estimated. This paper describes UnaLinea, a fast, accurate finite difference solver of 1 Corresponding author the one-line sediment continuity equation. The model is verified for the evolution of an initially straight shoreline of a plane beach subject to regular breaking waves at constant angle of incidence in the presence of either a groyne or a continuous singlepoint feed of sediment. Grid convergence and stability tests are used to obtain accurate, stable results, with satisfactory computational efficiency. Influences of wave input filtering and event-based sediment loading are considered. The rapid deterministic model is applied to Monte-Carlo simulations of the evolution of the west coast of Calabria, Italy for different scenarios including increased sediment load from a river and selected beach nourishment. The potential role of probabilistic shoreline evolution in regional coastal flood-risk assessment is explored through application to an idealised stretch of the Holderness coastline, U.K., where flood depths and expected damage are estimated for a 1000 year return period event.
2 3This paper describes the extension of a state-of-the-art one-line model in terms of alongshore sediment transport rate by linking with a cross-shore profile model through the OpenMI-based Pipistrelle interface. In order to combine these two models, three additional modules (Drift Interpolation module, Vector-to-Scalar module and Orientation Updating module) need to be developed, so that the two models which are based on different assumptions, coordinate systems and set-ups can be linked seamlessly. The existing two models and the three new modules are able to work together as a whole composition (i.e. the combined model) based on the OpenMI standard. This combined model aims to improve the one-line model in terms of alongshore sediment transport and beach morphological response predictability. It adopts both the modified Coastal Engineering Research Centre, USA (CERC) formula and the Energetics approach to calculate the alongshore sediment transport. Tests at a real curved coast demonstrate that the model is numerically stable, effective in computing and able to give reasonable predictions of shoreline change. It demonstrates that further research on linking existing models is promising. Notationbreaking wave energy density (J/m 2 ) e b prescribed efficiencies of bed load e s prescribed efficiencies of suspended load g gravitational acceleration (m/s 2 ) H b breaking wave height (m) I t total immersed weight sediment transport (kg/m per s) K 1 dimensionless calibration coefficient K 2 dimensionless calibration coefficient p porosity of sediment Q alongshore sediment transport rate (m 3 /s) Q b (i) drift values calculated by one-line model for grid point i (m 3 /s) Q c (i) drift values by the combined model for grid point i (m 3 /s) Q9 b (i) linearly-interpolated drift values of one-line model for grid point i (m 3 /s) Q9 c (i) linearly-interpolated drift values of profile model for grid point i (m 3 /s) Q k i alongshore transport at grid point i after k time steps (m 3 /s) q line sources and/or sinks along the shore (m 3 /s per m) r ratio between DQ c (i) and DQ b (i) (introduced above) t time (s) u near-bed water velocity (m/s) w s sediment settling velocity (m/s) x alongshore coordinate (m) y offshore coordinate (m) Maritime Engineering Volume 166 Issue MA4 An OpenMI-based combined model for alongshore sediment transport and shoreline change ICE Publishing: All rights reserved 175 y k i shoreline position at grid point i after k time steps (m) y m i shoreline position predicted by the model at point i (m) y s i shoreline position from survey measurements at point i (m) a b wave breaking angle (˚) bmean slope of the beach face (˚) c s submerged weight of beach material (kg/ m 2 s 2 ) DQ b (i) difference between Q9 b (i) and Q b (i) (introduced below) DQ c (i) difference between Q9 c (i) and Q c (i) (introduced below) r density of water (kg/m 3 ) r s density of sediment (kg/m 3 ) s averaged absolute deviation between model results and survey measurements (m) w angle of internal friction (˚)
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