TECHNICAL NOTES
Jan 1, 2005

Frequency-Size Statistics of Coastal Soft-Cliff Erosion

Publication: Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 131, Issue 1

Abstract

Predicting the retreat of a coastal soft cliff is a difficult and uncertain operation, which has both theoretical and practical significance. Recession of soft cliffs occurs through a combination of processes, including slope failures and surface erosion, that are difficult to model jointly. Deterministic models for predicting coastal retreat are hampered by the complex nature of coastal erosion, which is highly nonuniform in space and episodic in time. To overcome these limitations, stochastic approaches have been proposed. These models assume distributions for the size and the time of the recession events. In this paper we investigate the frequency-size statistics of soft-cliff erosion based on two historical datasets of coastal retreat measurements at two sites in England. We find that the two datasets exhibit a similar behavior. The frequency of the recessions decreases with increasing size of the retreat. For small retreats the decrease is slow. For medium to large retreats the decrease is rapid and follows a power law. The frequency-size statistics of soft-cliff erosion is similar to the statistics of medium to large landslide areas, which are also power-law distributed. This is a significant but not conclusive result. More data are needed to confirm this finding.

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Acknowledgments

The writers thank Neil Mclachlan of East Riding Council for supplying the Holderness data. The research is supported, in part, by a research grant from the Leverhulme Trust (Grant No. F/00143/D).

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Go to Journal of Waterway, Port, Coastal, and Ocean Engineering
Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 131Issue 1January 2005
Pages: 37 - 42

History

Received: Jun 24, 2004
Accepted: Jul 20, 2004
Published online: Jan 1, 2005
Published in print: Jan 2005

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Senior Lecturer, Div. of Civil Engineering, Faculty of Engineering, Physical Sciences, Univ. of Dundee, Dundee DD1 4HN, U.K. E-mail: [email protected]
Fausto Guzzetti [email protected]
Research Scientist, IRPI CNR, via della Madonna Alta 126, 06128 Perugia, Italy (corresponding author). E-mail: [email protected]

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