Bimodal Summary
Before beach management at Eastoke, beach lowering in front of the seawall was leading to significant over washing, annual flooding and the requirement for several seawall repairs. The consequences of this can be seen in the images below (Figure 1 and 2). Given a well sorted beach is one of the most effective defences against wave attack and overtopping, over 500,000 cubic metres of gravel was placed at Eastoke in 1985 to restore the beach and form the primary defence. Since then, the beach has been maintained through various Beach Management Plans, with the current South Hayling Beach Management Plan (BMP) running from 2024 – 2029. The BMP is funded by the Environment Agency at a cost of £3.3m and reduces the risk of flooding and erosion to over 1500 properties. The funding allocated includes several studies to better understand the coastal processes along the south coast of Hayling Island, one of which considers so called ‘Bimodal Waves’ which are known to be more damaging than standalone swell or wind waves.
Background
A bimodal sea state exists where high energy swell waves generated in the Atlantic Ocean occurs alongside locally generated wind waves (shorter period but higher wave height). The image below explains how the two interact (Figure 3). The result is a high energy environment that can do a lot of damage through increased overtopping of our beaches and sea defences. In recent years, the effect of bimodal seas has been more widely recognised and several research studies have been carried out to investigate the phenomenon as traditional design methods do not fully consider these conditions (e.g. Mason et al., 2009, Bradbury et al., 2007).
Direct observations of beach response at Hayling Island and the measurements from the Hayling Island wave buoy indicate that certain storm events, typically bimodal and extreme long period swell events, also erode the beach more rapidly than would be expected, putting homes at increased risk from flooding. Figure 4 and Figure 5 show the effect that bimodal seas can have on the beach – the crest rolls back and is flattened, increasing the potential for overtopping and flooding.
Since the record 2013-14 winter, we have experienced the highest significant wave height recorded at the Hayling wave buoy, an increase in long period swell events, as well as the highest percentage of bimodal seas recorded in a month and the stormiest season since recording began in 2003 (see SCOPAC Storm Analysis for more information). We are concerned as this shows that the hydrodynamic regime may be changing, towards a trend that is more damaging for the beach.
In response to a lack of design tools for assessing the impact of bimodal waves on shingle beaches, a model called Shingle-B was developed in 2016 by consultant HR Wallingford (Polidoro et al., 2018).
Development Of Bi-Modal Extremes For Hayling Island
To have the SHINGLE-B model available was a big step forward. Our first step was to apply the latest wave buoy records to refresh our extreme wave estimates, and to extend these to include bi-modal waves. Figure 6 shows how return periods are normally extracted from a combined water level and wave height threshold. However when wave period and % swell are added, establishing return periods becomes more complicated. Therefore, in 2020, HR Wallingford were commissioned to produce a new joint probability dataset for Eastoke that incorporated bimodality, resulting in a multivariate analysis, one of the few sites in the UK to have done this.
The new bi-modal extremes were run in SHINGLE-B as a comparison with the older uni-modal extremes at Hayling. As experienced in the field, increased erosion was evident for bi-modal sea states when comparing the same return period for a uni-modal condition. With respect to flooding the picture is less clear, as the peak wave condition for beach erosion might not be the peak condition for wave overtopping and flooding. It is a complex problem that will be investigated further through the South Hayling BMP.
What method was used to calculate the Bi-modal extremes in the work done to date as part of the Hayling BMP?
The approach by HR Wallingford is cutting edge, using a ‘big data method’ and Monte-Carlo simulation tool, from the Hayling wave buoy and the Portsmouth tide gauge for multivariate analyses to ascertain new bi-modal extreme datasets.
The approach by HR Wallingford involved fitting the Heffernan and Tawn (2014) multivariate extreme value distribution to two subsets of extreme values calculated from the Hayling wave buoy and the Portsmouth tide gauge – an unimodal timeseries and a bi-modal timeseries. Unimodal and bi-modal extreme wave conditions were then generated by a Monte Carlo simulation and extreme joint probability conditions extracted and input into Shingle-B to assess the over wash potential and crest retreat. Needless to say, this is a complex and evolving field, we are excited to be at the forefront of. The Application of Artificial Intelligence (AI) and Machine Learning (ML) is being considered in the flood and coastal management sector, but this work is in the early stages of research development.
What Does This Mean?
The 1985 beach recharge and subsequent management have successfully reduced the risk of flooding at Eastoke. Recent monitoring has shown that our wave conditions are becoming more onerous, in particular when bi-modal sea conditions occur. Through our studies, we are now able to better understand the response of Eastoke to these extreme bi-modal seas and therefore improve our management of flood risk under these conditions. The research confirms increased erosion of the beach as a result of these extreme bi-modal events, which requires further testing to optimise beach performance. Alongside further testing as part of the South Hayling BMP, the Hayling Island Coastal Management Strategy will confirm the preferred future management approach for Eastoke.
Acronyms used in the Bi-modal Wave Study
Acronym |
Description |
|---|---|
mOD |
Metres above ordnance datum or ODN (Ordnance Datum Newlyn) is defined as the mean sea level as recorded by the tidal gauge at Newlyn in Cornwall |
Hs |
Significant wave height. This is the average wave height calculated from the top third of wave heights measured |
Tp |
Wave period. This is the time between waves passing. Wind waves are typically less than ~12 seconds and larger swell waves are usually longer than ~12 seconds |
SWL |
Still Water Level |
JP |
Joint Probability. This is the chance of two or more conditions occurring at the same time resulting in a high-impact situation. This could be water level and wave height for example |
Hmo |
Total significant wave height of the combined sea (wind and swell waves) |
Tpswell |
Peak wave period of the swell wave |
Tpwind |
Peak wave period of the wind wave |
RP |
Return Period. The probability that a particular event could occur |
CRI |
Composite Response Index. This is equal to the average of the normalised over wash potential and the normalised crest position |
U1 to U5 |
These summarise five of the model runs under extreme unimodal wave conditions, hence the U |
B12 and B17 |
These summarise two of the model runs under bi-modal conditions, hence the B |
References
- Polidoro, A., Pullen, T., Eade, J., Mason, T, Blanco, B., and Wyncoll, D., 2018, Gravel beach profile response allowing sea-states, Published in the Institution of Civil Engineers
- Bradbury, A.P., Mason, T.E. and Poate, T. (2007). Implications of the spectral shape of wave conditions for engineering design and coastal hazard assessment – evidence from the English Channel
- Bradbury, A. (2010). A Review of regional wave climate and implications for shoreline management – extremes, swell, bimodal conditions
- Mason T, Bradbury A, Poate T, Newman R (2009). Nearshore wave climate of the English Channel evidence for bimodal seas. In: Proceedings of the 31st International Conference on Coastal Engineering, USA. American Society of 832 Civil Engineers. New York. 605–616.
- SCOPAC (2020). SCOPAC Storm Analysis Study https://southerncoastalgroup-scopac.org.uk/scopac-research/scopac-storm-analysis-study/