We use cookies to ensure that we give you the best experience on our website. By continuing to browse this repository, you give consent for essential cookies to be used. You can read more about our Privacy and Cookie Policy.

Durham e-Theses
You are in:

Regional-scale controls on rockfall occurrence

BENJAMIN, JESSICA (2018) Regional-scale controls on rockfall occurrence. Doctoral thesis, Durham University.

PDF - Accepted Version


Rockfalls exert a first-order control on the rate of rock wall retreat on mountain slopes and on coastal rock cliffs. Their occurrence is conditioned by a combination of intrinsic (resisting) and extrinsic (driving) processes, yet determining the exact effects of these processes on rockfall activity and the resulting cliff erosion remains difficult. Although rockfall activity has been monitored extensively in a variety of settings, high-resolution observations of rockfall occurrence on a regional scale are scarce. This is partly owing to difficulties in adequately quantifying the full range of possible rockfall volumes with sufficient accuracy and completeness, and at a scale that exceeds the influence of localised controls on rockfalls. This lack of insight restricts our ability to abstract patterns, to identify long-term changes in behaviour, and to assess how rock slopes respond to changes in both structural and environmental conditions, without resorting to a space for-time substitution.

This thesis develops a workflow, from novel data collection to analysis, which is tailored to monitoring rockfall activity and the resulting cliff retreat continuously (in space), in 3D, and over large spatial scales $(> 10^4 m)$. The approach is tested by analysing rockfall activity and the resulting erosion recorded along 20.5 km of near-vertical coastal cliffs, in what is considered as the first multi-temporal detection of rockfalls at a regional-scale and in full 3D. The resulting data are then used to derive a quantitative appraisal of along-coast variations in the geometric properties of exposed discontinuity surfaces, to assess the extent to which these drive patterns in the size and shape of the rockfalls observed. High-resolution field monitoring is then undertaken along a subsection of the coastline $(> 10^2 m)$, where cliff lithology and structure are approximately uniform, in order to quantify spatial variations in wave loading characteristics and to relate these to local morphological conditions, which can act as a proxy for wave loading characteristics.

The resulting rockfall inventory is analysed to identify the characteristics of rock slope change that only become apparent when assessed at this scale, placing bounds on data previously collected more locally $(< 10^2 m)$. The data show that spatial consistencies in the distribution of rockfall shape and volume through time approximately follow the geological setting of the coastline, but that variations in the strength of these consistencies are likely to be conditioned by differences in local processes and morphological controls between sites. These results are used to examine the relationships between key metrics of erosion, structural, and morphological controls, which ultimately permits the identification of areas where patterns of erosion are dominated by either intrinsic or extrinsic processes, or a mixture of both. Uniquely, the methodologies and data presented here mark a step-change in our ability to understand the competing effects of different processes in determining the magnitude and frequency of rockfall activity, and the resulting cliff erosion. The findings of this research hold considerable implications for our understanding of rockfalls, and for monitoring, modelling, and managing actively failing rock slopes.

Item Type:Thesis (Doctoral)
Award:Doctor of Philosophy
Keywords:Cliff; Coastal; Rockfalls; Erosion; LiDAR; Ground Motion
Faculty and Department:Faculty of Social Sciences and Health > Geography, Department of
Thesis Date:2018
Copyright:Copyright of this thesis is held by the author
Deposited On:03 Oct 2018 12:45

Social bookmarking: del.icio.usConnoteaBibSonomyCiteULikeFacebookTwitter