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Prediction of time to slope failure: a general framework

Lookup NU author(s): Dr Gaetano EliaORCiD


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The prediction of time to slope failure (TSF) is a goal of major importance for both landslide researchers and practitioners. A reasonably accurate prediction of TSF allows human losses to be avoided, damages to property to be reduced and adequate countermeasures to be designed. A pure “phenomenological” approach based on the observation and interpretation of the monitored data is generally employed in TSF prediction. Such an approach infers TSF mainly from the ground surface displacements using regression techniques based on empirical functions. These functions neglect the rheological soil parameters in order to reduce the prediction uncertainties. The paper gives an overlook of the methods associated with this approach and proposes a unique expression encompassing most of the previously proposed equations for TSF prediction, thus offering a general framework useful for comparisons between different methods. The methods discussed in the paper provide an effective tool, and sometimes the only tool, for TSF prediction. The fundamental problem is always one of data quality. A position of total confidence in all assumptions and parameters used in the prediction model is rarely if ever achieved. Therefore TSF prediction models should be applied with care and the results interpreted with caution. Observation of natural phenomena and documented case studies represent a most useful source of information to calibrate the TSF prediction models.

Publication metadata

Author(s): Federico A, Popescu M, Elia G, Fidelibus C, Internò G, Murianni A

Publication type: Article

Publication status: Published

Journal: Environmental Earth Sciences

Year: 2012

Volume: 66

Issue: 1

Pages: 245-256

Print publication date: 01/05/2012

ISSN (print): 1866-6280

ISSN (electronic): 1866-6299

Publisher: Springer


DOI: 10.1007/s12665-011-1231-5


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Funder referenceFunder name
"Fondazione Cassa di Risparmio di Puglia" (Progetto Integrato sulla Difesa Ambientale)
PS_119"Agenzia Regionale per la Tecnologia e l'Innovazione" of Puglia Region