Preprints
https://doi.org/10.5194/esurf-2021-44
https://doi.org/10.5194/esurf-2021-44

  29 Jun 2021

29 Jun 2021

Review status: this preprint is currently under review for the journal ESurf.

Multi-objective optimisation of a rock coast evolution model with cosmogenic 10Be analysis for the quantification of long-term cliff retreat rates

Jennifer R. Shadrick1, Martin D. Hurst2, Matthew D. Piggott1, Bethany G. Hebditch1, Alexander J. Seal1, Klaus M. Wilcken3, and Dylan H. Rood1 Jennifer R. Shadrick et al.
  • 1Earth Science and Engineering, Imperial College London, London, SW7 2AZ, United Kingdom
  • 2School of Geographical and Earth Sciences, University of Glasgow, Glasgow, G12 8QQ, United Kingdom
  • 3Institute for Environmental Research (IER), Australian Nuclear Science and Technology Organization (ANSTO), Lucas Heights, NSW 2234, Australia

Abstract. This paper presents a methodology that uses site-specific topographic and cosmogenic 10Be data to perform multi-objective model optimisation of a coupled coastal evolution and cosmogenic radionuclide production model. Optimal parameter estimation of the coupled model minimises discrepancies between model simulations and measured data to reveal the most likely history of rock coast development. This new capability allows for a time-series of cliff retreat rates to be quantified for rock coast sites over millennial timescales. This is the first study that has 1) applied a process-based coastal evolution model to quantify long-term cliff retreat rates for real, rock coast sites, and 2) coupled cosmogenic radionuclide analysis with a process-based model. The Dakota optimisation software toolkit is used as an interface between the coupled coastal evolution and cosmogenic radionuclide production model and optimisation libraries. This framework enables future applications of datasets associated with a range of rock coast settings to be explored. Process-based coastal evolution models simplify erosional processes and, as a result, often have equifinality properties, for example, that similar topography develops via different evolutionary trajectories. Our results show that coupling modelled topography with modelled 10Be concentrations can reduce equifinality in model outputs. Furthermore, our results reveal that multi-objective optimisation is essential in limiting model equifinality caused by parameter correlation to constrain best-fit model results for real-world sites. Results from two UK sites indicate that the rates of cliff retreat over millennial timescales are primarily driven by the rates of relative sea level rise. These findings provide strong motivation for further studies that investigate the effect of past and future relative sea level rise on cliff retreat at other rock coast sites globally.

Jennifer R. Shadrick et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on esurf-2021-44', Vincent Regard, 13 Jul 2021
    • AC1: 'Reply on RC1', Jennifer Shadrick, 02 Aug 2021
  • RC2: 'Comment on esurf-2021-44', Anonymous Referee #2, 12 Aug 2021
  • EC1: 'Comment on esurf-2021-44', Andreas Baas, 31 Aug 2021

Jennifer R. Shadrick et al.

Jennifer R. Shadrick et al.

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Short summary
Here we use topographic and 10Be concentration data to optimise a coastal evolution model. Cliff retreat rates are calculated for two UK sites for the past 8000 years, and for the first time, highlight a strong link between the rate of sea level rise and long-term cliff retreat rates. This method enables us to study past cliff response to sea level rise, and so, to greatly improve forecasts of future responses to accelerations in sea level rise that will result from climate change.