Scale model testing in wave basins is a necessary part of the development of marine structures and marine renewable energy devices. Whilst many guidelines exist for the quality of experimentation and data acquisition, there are no standards for the basins themselves. We propose methodologies for assessing the quality of a wave field generated in a basin: a clustering parameter based on the variance of surface elevation at multiple gauges is used to score homogeneity and extended to a skill score for relative quality benchmarking. We use historic and recent data from the University of Plymouth's Ocean Basin as a case study for the methods. The quality metrics indicate that physical aspects of the basin itself, such as water depth, contribute the most to the accuracy and homogeneity with wave period performing better than height. Recommendations for experimentalists, such as using basins when operating in steady state, are presented and discussed.
Traditional flood-risk assessment considers coastal defences to be static features with foreshores represented simply with an assigned elevation and slope. However, beach elevations can vary rapidly over time, perhaps fluctuating seasonally, and often losing or gaining volume over a longer time period. Their dynamic nature ultimately influences the risk of coastal erosion and flooding. In a regional flood-risk assessment, in which beaches offer protection to a variety of backshore features such as seawalls, soft cliffs, and dunes, the ability to represent the beach dynamics fronting these defences is important. At regional scale, it is also necessary to consider the various backshore environments that may be encountered over a long stretch of coastline, and how their individual processes affect flood risk, particularly if they are erodible. An integrated framework of dynamically linked numerical models of coastal processes and statistical analysis methods is being developed to enhance regional flood-risk assessment via consideration of coastal evolution and foreshore morphodynamics. The framework is run entirely from within commercially available geographical information system software where model operation and numerical output is managed; standard geographical information system analysis and database capabilities are therefore also available within the modelling system. This paper outlines the basis of the modular framework, and demonstrates how flood-risk assessment is enhanced.
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.
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