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Mechanism Modeling and Forecasting of Landslide Displacements

Landslides cause significant damage and loss of life throughout the world. There is an increase in landslide activity as a result of continued deforestation, increased construction in landslide-prone areas, and increased regional... ver más

03/01/2013

METU

75K€

Presupuesto del proyecto: 75K€

Líder del proyecto

MIDDLE EAST TECHNICAL UNIVERSITY No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2013-01-03 No tenemos la información de la convocatoria

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Líder del proyecto

MIDDLE EAST TECHNICAL UNIVERSITY No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 75K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Landslides cause significant damage and loss of life throughout the world. There is an increase in landslide activity as a result of continued deforestation, increased construction in landslide-prone areas, and increased regional precipitation by changing climate patterns, which is a primary trigger for landslides. One of the four priorities areas in FP7 have been identified as triggering factors and forecasting, and mitigation strategies for natural hazards. The overall goal of this research is to reduce damage caused by landslides, by increasing our understanding of the mechanism of slow-moving landslides. The specific objectives are: (1) to identify the triggering factors and failure mechanisms in landslides composed mainly of (or dominated by) cohesive soils, (2) to investigate application of numerical models in slope displacement analyses and calibration of model parameters by observed deformations in well-documented case histories. (3) to establish threshold slope displacement rates that can be used in setting up alarm levels and early warning, and to improve forecasting methods that would help predict the failure time, (4) to transfer the knowledge to end-users by preparing handbooks/guidelines and training courses. The proposed research will generate (a) a large database of well-documented landslide case histories and correlations to predict certain type of movements from slopes with certain properties (material type, slope angle, etc.), (b) a numerical methodology for the evaluation of slope stability and slope deformations including validation and calibration of model parameters with the measured deformations, (c) enhanced forecasting tools for failure time prediction in landslides, (d) the range of values of threshold displacement rates for different degrees of alert levels that can be used by decision makers, (e) guidelines and manuals covering all aspects.

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