A Method to Extract Measurable Indicators of Coastal Cliff Erosion from Topographical Cliff and Beach Profiles: Application to North Norfolk and Suffolk, East England, UK

Muñoz López, Pablo; Payo Garcia, Andres; Ellis, Michael A.; Criado-Aldeanueva, Francisco; Jenkins, Gareth Owen. 2020 A Method to Extract Measurable Indicators of Coastal Cliff Erosion from Topographical Cliff and Beach Profiles: Application to North Norfolk and Suffolk, East England, UK. Journal of Marine Science and Engineering, 8 (1), 20. https://doi.org/10.3390/jmse8010020

Before downloading, please read NORA policies.

Preview

Text (Open Access Paper)
jmse-08-00020-v2-1.pdf - Published Version
Available under License Creative Commons Attribution 4.0.
Download (11MB) | Preview

Official URL: http://dx.doi.org/10.3390/jmse8010020

Abstract/Summary

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.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.3390/jmse8010020
ISSN:	2077-1312
Date made live:	30 Mar 2020 14:49 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/527348

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.3390/jmse8010020

ISSN:

2077-1312

Date made live:

30 Mar 2020 14:49 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/527348