Abstract
Recession of coastal cliffs (bluffs) is a significant problem globally, as around 80% of Earth’s coastlines are classified as sea cliffs. It has long been recognised that beaches control wave energy dissipation on the foreshore and, as a result, can provide protection from shoreline and cliff erosion. However, there have been few studies that have quantified the relationship between beach levels and cliff recession rates. One of the few quantitative studies has shown that there is a measurable relationship between the beach thickness (or beach wedge area (BWA) as a proxy for beach thickness) and the annual cliff top recession rate along the undefended coast of North Norfolk and Suffolk in eastern England, United Kingdom (UK). Additionally, previous studies also found that for profiles with low BWA, the annual cliff top recession rate frequency distribution follows a bimodal distribution. This observation suggests that as BWA increases, not only does cliff top recession rate become lower, but also more predictable, which has important implications for coastal stakeholders particularly for planning purposes at decadal and longer time scales. In this study, we have addressed some of the limitations of the previous analysis to make it more transferable to other study sites and applicable to longer time scales. In particular, we have automatised the extraction of cliff tops, toe locations, and BWA from elevation profiles. Most importantly, we have verified the basic assumption of space-for-time substitution in three different ways: (1) Extending the number or years analysed in a previous study from 11 to 24 years, (2) extending the number of locations at which cliff top recession rate and BWA are calculated, and (3) exploring the assumption of surface material remaining unchanged over time by using innovative 3D subsurface modelling. The present study contributes to our understanding of a poorly known aspect of cliff–beach interaction and outlines a quantitative approach that allows for simple analysis of widely available topographical elevation profiles, enabling the extraction of measurable indicators of coastal erosion.
Highlights
Recession of coastal cliffs is a significant problem globally, as around 80% of Earth’s coastlines are classified as sea cliffs [1]
It has long been recognised that beaches control wave energy dissipation on the foreshore and, as a result, can provide protection from shoreline erosion
There have been few studies that have quantified the relationship between beach levels and cliff recession rates
Summary
Recession of coastal cliffs (bluffs) is a significant problem globally, as around 80% of Earth’s coastlines are classified as sea cliffs [1]. Lee found that for profiles with low BWA (i.e., less than 5 m2 for North Norfolk profiles and less than 15 m2 for Suffolk profiles), the annual cliff top recession rate frequency distribution follows a bimodal distribution (Figures 10 and 11 in Lee, 2008). This bimodality indicates that, for any given year, the cliff top recession rate could range from less than 1 m/year to as high as 20 m/year. As BWA increases, this bimodality in the cliff top recession rate frequency distribution disappears to become unimodal, with mean values decreasing as BWA increases. A cliff section with initially large BWA and historical unimodal cliff recession rates could become bimodal if the BWA decreases over time and becomes more unpredictable
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