Soft Cliff Erosion Research Articles

Modeling of Soft Cliff Erosion by Oblique Breaking Waves during a Storm

Abstract Soft cliff (bluff) erosion during a storm is investigated using available wave basin data and a cross-shore numerical model for dune erosion. The measured cliff recession rates under obliq...

Spatial and temporal variations in soft-cliff erosion along the Holderness coast, East Riding of Yorkshire, UK

The Holderness coast is composed largely of ‘soft’ Quaternary sediments, mainly glacial till, which form cliffs up to 38 m high. Cliff erosion rates have shown a complex pattern of spatial and temporal variation over the past 160 years which reflects interaction of natural processes and human interventions, notably building of coastal defences at Bridlington, Hornsea, Withernsea, Mappleton, and Easington. A former single coastal cell, extending between Flamborough Head and the Spurn Peninsula, is breaking down into a series of separate sub-cells defined by sections of defended coast. Between these ‘hard points’ the shoreline is developing as a series of shallow bays which are deepest immediately to the south (downdrift) of the defences. Superimposed on this pattern are smaller-scale variations which reflect the effects of dynamic beach features on wave energy exposure at the cliff toe. Cliff recession rates can exceed 4 m a−1 when beach troughs lie in front of the cliff toe but may fall close to zero as a sand wave passes. Erosion rates on the undefended coast showed an increase in the period 1989–2013 compared with earlier epochs and further increases can be anticipated due to sea level rise over the course of the next century. The effects of climate change on storminess remain uncertain but any increase would further enhance the erosional trend. The implications are future increased rates of cliff top recession and increased risk to infrastructure close to the coast in the medium to longer term. Increased erosion rates will increase the rate of sediment supply to the nearshore system, but it is unclear how much of the fine sediment released will be transported into the Humber estuary to maintain tidal flats and saltmarshes, and how much of the sand and gravel will travel along the beach system to sustain the Spurn Peninsula.

Modelling the response of soft cliffs to climate change: A statistical, process-response model using accumulated excess energy

Cliff retreat poses a threat to coastal communities worldwide. In soft cliff environments, coastal retreat may occur at rapid rates. The environmental significance of soft cliff environments, coupled with the societal impacts of cliff retreat, means that it is important to understand the processes and timings of soft cliff erosion. Here, a new statistical, process-response model of soft cliff erosion is proposed, based on the premise that wave energy delivered to the cliff toe is the key parameter forcing erosion. More specifically, and in contrast to prior studies that have sought to link erosion rates to indices of peak wave energy, we postulate that the Accumulated Excess wave Energy (AEE; the time integrated total wave energy above an erosion threshold), is the key hydraulic control on soft cliff erosion. The new model is calibrated to two UK sites with contrasting (Atlantic versus North Sea) wave energy regimes, before downscaled HadCM3 Global Climate Model outputs are used to assess how future (next ~100year) changes in sea-level and wave height affect retreat rates at the two study sites. We show that the AEE model accounts for between 46% and 89% of the variance in observed coastal erosion; representing an improvement over prior models that use measures only of peak wave energy. The AEE model suggests increases of between 0.5m.a–1 (92%) and 0.3m.a–1 (33%) in mean erosion rate by 2100 for sites in the Atlantic and North Sea, respectively. Furthermore, it is shown that at both sites extreme events, exceeding the 95th percentile value, are projected to become three to four times more likely under scenarios of future climate change, highlighting a need to understand and predict the extreme response of coastal cliff systems to changes in climate.

Meeting report: Soft coastal cliff: understanding and managing retreat

This article reports on a seminar held at the Institution of Civil Engineers in May 2004. This, and a previous meeting in 2002, stemmed from Government-funded research into soft cliff erosion. While the previous meeting dealt with the theory, this one dealt with more practical issues by way of four papers. Dr Neil Dixon described work carried out on landsliding of unprotected London Clay cliffs at Warden Point on the Isle of Sheppey. Dr Alan Clark described practical examples of engineering schemes at Lyme Regis and at Castlehaven, Niton and the Military Road on the Isle of Wight. The final two papers described aspects of work on the Norfolk coast: Dr Mike Walkden presented a process-based regional model of shoreline recession while Peter Frew of North Norfolk District Council described the problems faced by his authority in managing a retreating coastline where property is under threat.

Frequency-Size Statistics of Coastal Soft-Cliff Erosion

Predicting the retreat of a coastal soft cliff is a difficult and uncertain operation, which has both theoretical and practical significance. Recession of soft cliffs occurs through a combination of processes, including slope failures and surface erosion, that are difficult to model jointly. Deterministic models for predicting coastal retreat are hampered by the complex nature of coastal erosion, which is highly nonuniform in space and episodic in time. To overcome these limitations, stochastic approaches have been proposed. These models assume distributions for the size and the time of the recession events. In this paper we investigate the frequency-size statistics of soft-cliff erosion based on two historical datasets of coastal retreat measurements at two sites in England. We find that the two datasets exhibit a similar behavior. The frequency of the recessions decreases with increasing size of the retreat. For small retreats the decrease is slow. For medium to large retreats the decrease is rapid and follows a power law. The frequency-size statistics of soft-cliff erosion is similar to the statistics of medium to large landslide areas, which are also power-law distributed. This is a significant but not conclusive result. More data are needed to confirm this finding.