Project Details


The storms experienced in the UK during the winter of 2013/2014 highlighted the vulnerability of the coast to structural damage, flooding and coastal erosion due to extreme waves and water levels, and the economic and societal costs of such events. Predictions indicate that these events will become increasingly common due to rising sea levels and greater storminess, presenting a significant challenge for the sustainable management of the coast, approximately 30% of which is already protected by hard engineering structures on the UK mainland. As nearshore waves are a key cause of coastal flooding and erosion, the goal of this research project is to increase our understanding of their behaviour, providing the basis for improved predictions of wave processes and their effect on our engineered and natural coasts. Sandy beaches account for approximately 75% of the World's ice-free coastlines. As ocean waves approach beaches they undergo rapid transformation as they break in shallow water, propagate through the surf zone as white-water bores and then drive wave runup in the swash zone. Shallow water waves cause forces on coastal structures, drive sediment transport, lead to overtopping of coastal defences and dunes, and cause beach and cliff erosion. Consequently, an understanding of wave transformation is of critical importance for coastal engineers. However, due to the complex nature of waves in the nearshore, theoretical descriptions are limited and numerical modelling approaches typically rely on empirical approximations to describe breaking and broken waves based mainly on laboratory results which are subject to scale effects and do not necessarily reproduce the variability of waves in nature. Shallow water wave processes are key to the numerical models of shoreline change and coastal flooding which are used by engineers to inform coastal management decisions. To improve the predictive capability of these models, high quality field data are required, but existing measurements fail to fully capture the variability and highly non-linear shape of shallow water waves due to their limited coverage across the surf zone and low spatial resolution. To address this internationally relevant research gap, the proposed study will apply a newly developed remote sensing approach using a network of jetty-mounted Lidar at two typical beach sites to obtain measurements of rapidly evolving waves across the complete surf and swash zone at high frequency and a spatial resolution an order of magnitude higher than previously achieved. Uniquely, this capability allows individual waves to be tracked from the break point to the limit of maximum wave runup on the beach, enabling an analysis of wave characteristics on a wave-by-wave basis. The two sites have been selected to obtain a wide range of wave conditions at locations with jetty infrastructure, but the results will inform our fundamental understanding of waves and so be relevant to the majority of sandy coastlines. The new data, combined with beach topography information and measurements of flow velocities will form a valuable field-dataset, which will be analysed to answer fundamental unresolved questions related to wave transformation in the nearshore, and improve the representations of breaking and broken waves used in predictive wave models. Additionally the new dataset will be made available to the research community following project completion. Improvements in our ability to model nearshore waves will reduce uncertainty in predictions of wave forcing on engineered structures and the natural coastal environment. This would enable better assessment of shoreline erosion and coastal hazards, providing the opportunity for more efficient coastal planning and design of coastal defence schemes which would directly or indirectly impact a range of academic, public and industry stakeholders including coastal engineers and scientists, coastal communities, insurers and coastal managers.
Effective start/end date15/02/168/10/17

Collaborative partners


  • Engineering and Physical Sciences Research Council

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 13 - Climate Action


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