A methodology for modelling and prediction of coastal cliffs recession

• Type: Article in International Conference Proceedings Book
• Date: 2001

Authors

Milheiro Oliveira, P (Author) FEUP; Meadowcroft, I (Author) Other

Conference proceedings International

Title: COASTAL DYNAMICS '01: PROCEEDINGS

Pages: 969-978

4th International Conference on Coastal Dynamics

LUND, SWEDEN, JUN 11-15, 2001

Indexing

ISI Web of Knowledge - 0 Citations

ISI Web of Science

Scopus - 3 Citations

Scientific classification

FOS: Engineering and technology > Civil engineering

CORDIS: Physical sciences > Mathematics > Applied mathematics > Engineering mathematics ; Technological sciences > Engineering > Civil engineering > Geotechnics ; Technological sciences > Engineering > Civil engineering > Hydraulic engineering

Other information

Authenticus ID: P-000-WX9

DOI: 10.1061/40566(260)99

Abstract (EN): The present paper treats the problem of modelling the recession of a coastal cliff in order to predict future positions of the top of the cliff, and the occurrence of major failure events. The behaviour of the cliff is predicted based on available data, by applying various probabilistic and statistical tools. The use of some of these methods is believed to be original while others draw on previous work. A first stage comprises building an adequate model for the cliff taking account of the characteristics of the recession process and the available data. In a second stage this model is used to predict the recession in future years. Predicting the probability that a particular cliff-top asset will be lost in a given time enables an assessment of risk., and can provide the basis for economical appraisal of management measures at the site under study. The methodology is applied to a wide variety of cliffs in the UK located at The Naze, Isle of Wight, Herne Bay and Scarborough. The results suggest that uncertainty in cliff predictions can be large due to the typically sparse data and uncertainty in recession processes, The models presented here are able to provide useful predictions of the recession of the top of a cliff or of the number of major landslides in a given period of time, indicating that simple statistical methods have predictive capability. Results are expressed in probabilistic rather than deterministic terms to reflect the uncertainties.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10