Landslide hazards assessment and uncertainties

Landslides are natural phenomena which are difficult to predict because their initiation depends on many factors and on the interaction between these factors. The annual number of causalities caused by landslides is in the thousands, and infrastructural damage is in the billions of dollars. To satisfy the increasingly urgent societal demand for protection against landslides, it is necessary to systematically assess and manage landslide hazard and risk. This can be done using principles of decision making under uncertainty. We develop an advanced combined hydrologic - stability model that is better capable of assessing landslide hazards than current models used in landslide analyses. This model allows one to evaluate landslide hazards deterministically. We use the model to study landslide failure mechanisms, and classify these according to the manner in which a slope gets saturated during rain. We showed that slopes with great depths to bedrock and shallow depths to the water table, tend to fail by saturation from below, resulting in deep seated landslides, and slopes with deep lying water tables tend to fail by saturation from above, resulting in shallow landslides.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2005

Author dc:creator

• Karam, Karim S. (Karim Semaan), 1977-

Advisor dc:contributor.advisor

• Herbert H. Einstein and Daniele Veneziano.

• Civil and Environmental Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/33690

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/33690