Geometrical analysis of the inland topography to assess the likely response of wave-dominated coastline to sea level: application to Great Britain

Autor: Jonathan R. Lee, Andres Payo, Chris Williams, Kathryn Lee, Rowan Vernon, Andrew G. Hulbert
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of Marine Science and Engineering; Volume 8; Issue 11; Pages: 866
Journal of Marine Science and Engineering, Vol 8, Iss 866, p 866 (2020)
DOI: 10.3390/jmse8110866
Popis: The need for quantitative assessments at a large spatial scale (103 km) and over time horizons of the order 101 to 102 years have been reinforced by the 2019 Special Report on the Ocean and Cryosphere in a Changing Climate, which concluded that adaptation to a sea-level rise will be needed no matter what emission scenario is followed. Here, we used a simple geometrical analysis of the backshore topography to assess the likely response of any wave-dominated coastline to a sea-level rise, and we applied it along the entire Great Britain (GB) coastline, which is ca. 17,820 km long. We illustrated how the backshore geometry can be linked to the shoreline response (rate of change and net response: erosion or accretion) to a sea-level rise by using a generalized shoreline Exner equation, which includes the effect of the backshore slope and differences in sediment fractions within the nearshore. To apply this to the whole of GB, we developed an automated delineation approach to extract the main geometrical attributes. Our analysis suggests that 71% of the coast of GB is best described as gentle coast, including estuarine coastline or open coasts where back-barrier beaches can form. The remaining 39% is best described as cliff-type coastlines, for which the majority (57%) of the backshore slope values are negative, suggesting that a non-equilibrium trajectory will most likely be followed as a response to a rise in sea level. For the remaining 43% of the cliffed coast, we have provided regional statistics showing where the potential sinks and sources of sediment are likely to be.
Databáze: OpenAIRE