Lagrangian particle methods such as smoothed particle hydrodynamics (SPH) are very demanding in terms of computing time for large domains. Since the numerical integration of the governing equations is only carried out for each particle on a restricted number of neighbouring ones located inside a cut-off radius rc, a substantial part of the computational burden depends on the actual search procedure; it is therefore vital that efficient methods are adopted for such a search. The cut-off radius is indeed much lower than the typical domain's size; hence, the number of neighbouring particles is only a little fraction of the total number. Straightforward determination of which particles are inside the interaction range requires the computation of all pair-wise distances, a procedure whose computational time would be unpractical or totally impossible for large problems. Two main strategies have been developed in the past in order to reduce the unnecessary computation of distances: the first based on dynamically storing each particle's neighbourhood list (Verlet list) and the second based on a framework of fixed cells. The paper presents the results of a numerical sensitivity study on the efficiency of the two procedures as a function of such parameters as the Verlet size and the cell dimensions. An insight is given into the relative computational burden; a discussion of the relative merits of the different approaches is also given and some suggestions are provided on the computational and data structure of the neighbourhood search part of SPH codes

Marine X-band radar based systems are well tested to provide information about sea state and bathymetry. It is also well known that complex geometries and non-uniform bathymetries provide a much bigger challenge than offshore scenarios. In order to tackle this issue a retrieval method is proposed, based on spatial partitioning of the data and the application of the Normalized Scalar Product (NSP), which is an innovative procedure for the joint estimation of bathymetry and surface currents. The strategy is then applied to radar data acquired around a harbour entrance, and results show that the reconstructed bathymetry compares well with ground truth data obtained by an echo-sounder campaign, thus proving the reliability of the whole procedure. The spectrum thus retrieved is then analysed to show the evidence of reflected waves from the harbour jetties, as confirmed by chain of hydrodynamic models of the sea wave field. The possibility of using a land based radar to reveal sea wave reflection is entirely new and may open up new operational applications of the system.

Abstract:Estimating the extreme values of significant wave height (H S ), generally described by the H S return period T R function H S (T R ) and by its confidence intervals, is a necessity in many branches of coastal science and engineering. The availability of indirect wave data generated by global and regional wind and wave model chains have brought radical changes to the estimation procedures of such probability distribution-weather and wave modeling systems are routinely run all over the world, and H S time series for each grid point are produced and published after assimilation (analysis) of the ground truth. However, while the sources of such indirect data are numerous, and generally of good quality, many aspects of their procedures are hidden to the users, who cannot evaluate the reliability and the limits of the H S (T R ) deriving from such data. In order to provide a simple engineering tool to evaluate the probability of extreme sea-states as well as the quality of such estimates, we propose here a procedure based on integrating H S time series generated by model chains with those recorded by wave buoys in the same area.

Abstract. Extreme weather events bear a significant impact on coastal human activities and on the related economy. Forecasting and hindcasting the action of sea storms on piers, coastal structures and beaches is an important tool to mitigate their effects. To this end, with particular regard to low coasts and beaches, we have developed a computational model chain based partly on open-access models and partly on an ad-hoc-developed numerical calculator to evaluate beach wave run-up levels and flooding. The offshore wave simulations are carried out with a version of the WaveWatch III model, implemented by CCMMMA (Campania Centre for Marine and Atmospheric Monitoring and Modelling – University of Naples Parthenope), validated with remote-sensing data. The waves thus computed are in turn used as initial conditions for the run-up calculations, carried out with various empirical formulations; the results were finally validated by a set of specially conceived video-camera-based experiments on a micro-tidal beach located on the Ligurian Sea. Statistical parameters are provided on the agreement between the computed and observed values. It appears that, while the system is a useful tool to properly simulate beach flooding during a storm, empirical run-up formulas, when used in a coastal vulnerability context, have to be carefully chosen, applied and managed, particularly on gravel beaches.