Modelling Extreme Wave Overtopping at Aberystwyth Promenade

The work presents a methodology to assess the coastal impacts during a storm event which caused significant damage along the promenade at Aberystwyth, Wales on the 3 January 2014. Overtopping was analysed in detail for a section of promenade by downscaling offshore wave conditions to force a surf zone hydrodynamic model, NEWRANS. Overtopping discharges are computed and were in qualitative agreement with published discharges for the level of damage observed along the promenade. Peak storm conditions were observed to arrive just before and during high tide at Aberystwyth, which in addition to a storm surge and wave-setup, contributed to the damage observed. A high frequency of overtopping occurs during peak high tide, with overtopping also occurring in the hour leading up to and following high tide. Finally, comparisons to design methods for the estimation of overtopping discharge were made. Current empirical formulae underestimated the peak overtopping event at high tide. The methodology applied is generic and applicable to any location

Climate Change Impacts on Future Wave Climate around the UK

Understanding the changes in future storm wave climate is crucial for coastal managers and planners to make informed decisions required for sustainable coastal management and for the renewable energy industry. To investigate potential future changes to storm climate around the UK, global wave model outputs of two time slice experiments were analysed with 1979–2009 representing present conditions and 2075–2100 representing the future climate. Three WaveNet buoy sites around the United Kingdom, which represent diverse site conditions and have long datasets, were chosen for this study. A storm event definition (Dissanayake et al., 2015) was used to separate meteorologically-independent storm events from wave data, which in turn allowed storm wave characteristics to be analysed. Model outputs were validated through a comparison of the modelled storm data with observed storm data for overlapping periods. Although no consistent trends across all future clusters were observed, there were no significant increases in storm wave height, storm count or storm power in the future, at least according to the global wave projection results provided by the chosen model

Analysis of Climate Change Effects on Seawall Reliability

Crown heights of seawalls should be designed to suppress overtopping discharge to a permissible level. The permissible level is determined from viewpoints of the structure types of coastal seawalls and hinterland use. It is usually difficult to design the crown heights of seawalls, especially in the present time where climate change due to global warming is expected. This study analyzes climate change effects such as sea level rise (SLR) and increase of waves and surges on the failure probability of seawalls under various conditions of crown height, toe depth and slope by using a Level III reliability analysis. It was found that the difference of SLR trends (fast, medium or low) has less impact on overtopping rates than the differences in wave height change for a seawall at a target location

Modelling shoreline evolution in the vicinity of a groyne and a river

Analytical solutions to the equations governing shoreline evolution are well-known and have value both as pedagogical tools and for conceptual design. Nevertheless, solutions have been restricted to a fairly narrow class of conditions with limited applicability to real-life situations. We present a new analytical solution for a widely encountered situation where a groyne is constructed close to a river to control sediment movement. The solution, which employs Laplace transforms, has the advantage that a solution for time-varying conditions may be constructed from the solution for constant conditions by means of the Heaviside procedure. Solutions are presented for various combinations of wave conditions and sediment supply/removal by the river. An innovation introduced in this work is the capability to provide an analytical assessment of the accretion or erosion caused near the groyne due to its proximity to the river which may act either as a source or a sink of sediment material

A new approach to analytical modelling of groyne fields

Analytical and computational techniques for finding solutions to the equations describing shoreline evolution are widely known and the advantages and disadvantages of both are well documented. Initial analytical solutions to the 1-line models were restricted to constant wave conditions and simple beach/structure configurations. Recent developments in analytical treatments have allowed solutions to be found for an arbitrary sequence of wave conditions, but again for simple configurations. Here, we propose a method of linking several analytical solutions together in order to describe the unsteady evolution of a beach within a groyne field, allowing for both permability of the groynes and by-passing. The method relies on specifying boundary conditions in each groyne cell that mimic the transmission and by-passing of sediment. The conditions are generalisations of boundary conditions that are well-known. Solutions for groyne fields on straight and convex shorelines are presented to illustrate the method for constant and time varying wave conditions

Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches.

Antimicrobial resistance (AMR) surveillance systems are generally not specifically designed to detect emerging resistances and usually focus primarily on resistance to individual drugs. Evaluating the diversity of resistance, using ecological metrics, allows the assessment of sampling protocols with regard to the detection of rare phenotypes, comprising combinations of resistances. Surveillance data of phenotypic AMR of Canadian poultry Salmonella Heidelberg and swine Salmonella Typhimurium var. 5- were used to contrast active (representative isolates derived from healthy animals) and passive (diagnostic isolates) surveillance and assess their suitability for detecting emerging resistance patterns. Although in both datasets the prevalences of resistance to individual antimicrobials were not significantly different between the two surveillance systems, analysis of the diversity of entire resistance phenotypes demonstrated that passive surveillance of diagnostic isolates detected more unique phenotypes. Whilst the most appropriate surveillance method will depend on the relevant objectives, under the conditions of this study, passive surveillance of diagnostic isolates was more effective for the detection of rare and therefore potentially emerging resistance phenotypes.AEM was supported by the William Stewart Fellowship whilst at the University of Glasgow, and is currently supported by Biotechnology and Biological Sciences Research Council (BBSRC) grant BB/ M014088/1; RR is supported by BBSRC grant BB/ E010326/1 and BB/L004070/1; LM is supported by BB/K01126X/1, BB/L004070/1, BB/F015313/1, National Science Foundation DEB1216040 and an EU-funded Marie Curie Initial Training Network (MCITN) program (NEMATODE SYSTEM HEALTH project (FP7-PEOPLE-2010-ITN- ID:264639)).This is the final version of the article. It first appeared from the Public Library of Science via http://dx.doi.org/10.1371/journal.pone.015851

Simulation of Wave Time Series with a Vector Autoregressive Method

Joint time series of wave height, period and direction are essential input data to computational models which are used to simulate diachronic beach evolution in coastal engineering. However, it is often impractical to collect a large amount of the required input data due to the expense. Based on the nearshore wave records offshore of Littlehampton in Southeast England over the period from 1 September 2003 to 30 June 2016, this paper presents a statistical method to obtain simulated joint time series of wave height, period and direction covering an extended time span of a decade or more. The method is based on a vector auto-regressive moving average algorithm. The simulated times series shows a satisfactory degree of stochastic agreement between original and simulated time series, including average value, marginal distribution, autocorrelation and cross-correlation structure, which are important for Monte Carlo modelling of shoreline evolution, thereby allowing ensemble prediction of shoreline response to a variable wave climate

Characterizing the Marine Energy Test Area (META) in Wales, UK

With lack of convergence on any single wave or tidal technology, test centres have a unique role in the marine renewable energy industry. Test centres facilitate real testing at sea for devices and components at various TRLs (Technology Readiness Level), reducing the time, cost, and risks faced by marine energy developers. META (Marine Energy Test Area) is a £2.7M project managed by Marine Energy Wales (MEW), consisting of eight test areas in the Milford Haven Waterway and surrounding waters (Pembrokeshire, Wales). Although various datasets have been collected from the META test areas over the last decade, and some aspects of these data have been published in various reports, the data has not been gathered together, systematically analysed and critically assessed – the aim of this study. Here, we describe and interpret the various META datasets, including multibeam, ADCP (acoustic Doppler current profiler), and wave buoy data. We report the key parameters of relevance to testing at META, including bathymetry, the nature and magnitude of the tidal currents, turbulence, and wave climates. We make recommendations on future priorities for data collection at META, and discuss the future of the test areas, including expansion into floating wind and other evolving marine energy technologies