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Title: Developing a probabilistic recession model through characterisation and quantification of the erosion of chalk sea cliffs in Brighton
Author: Gilham, Jamie Mark
ISNI:       0000 0004 7425 3932
Awarding Body: University of Sussex
Current Institution: University of Sussex
Date of Award: 2018
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This research has developed a methodology for high precision monitoring of coastal chalk sea cliffs using both terrestrial and unmanned aerial vehicle (UAV) digital photogrammetry. Two contrasting study sites of similar geology at Brighton Marina and Telscombe enabled a comparative assessment of cliff behaviour, for an engineered cliff with toe protection and cliff face stabilisation versus a natural cliff subject to active toe erosion respectively. The site at Brighton Marina was monitored between November 2014 and March 2017, during this period no rockfall was detected above the surface change threshold of 0.07 m. For the Telscombe site, monitored between August 2016 and July 2017, volumetric estimations of rockfalls populated a rockfall inventory. Frequency-magnitude analysis of the monthly inventories demonstrated negative power law scaling over seven orders of magnitude with 10,085 mass wasting events and a total volumetric flux of 3,889.35 m3. Statistically significant correlations were found, for the first time, between significant wave height (Hs) and the power law scaling coefficients, β and s with R2 values of 0.4971 and 0.5793 respectively. The model was an accurate predictor of erosion evidenced by the R2 of 0.9981 between the model predictions and observations over the data collection period. A Monte Carlo simulation of potential erosion scenarios between 2020 and 2089 was established using these relationships based on Hs probabilities and sea level forecasts derived from the UKCP09 medium emission climate model (A1B) to assess the impact of future climate change on cliff recession. For the most likely cliff recession scenario the model predicts an approximate 6% increase in recession between the current and future (UKCP09 medium emission scenario) conditions from 20.45 m to 21.76 m. The model also estimates the probability of recession breaching the A259 coastal road by 2089, this revealed an increase from 0.0778 to 0.1056 due to the influence of future climate. The photogrammetric models were also used to characterise the Newhaven Chalk cliffs and through kinematic analysis found wedge failure to be the most likely mechanism of failure, with 39.97% of mapped intersections favourable to this mode. A limit equilibrium analysis of the observed conjugate joint sets within the defended section of cliffs between Brighton Marina and Telscombe was undertaken to assess the risk of any future failure to infrastructure. This revealed that the coastal road would not be at immediate threat (breach) due to any of the modelled wedge failures occurring, however measures would need to be put in place to maintain the road in its current location were any of these failures to occur. A probabilistic recession model using current industry best practice, in the absence of a rockfall inventory, was used to predict future recession for the defended section of cliffs. Within identified ‘pinch-points' where the distance between the road and cliff edge was less than 10 m the probability of recession reaching the road over the next 100 years did not exceed 0.0014. A comparison between approaches identified the benefits of the scientific method presented in this research. The outputs of this research offer a new approach for the collection and processing of coastal monitoring data which ultimately drives the prediction of future coastal cliff recession and facilitates effective planning and mitigation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: GB0448 Slopes ; GB0450 Coasts