MPC
Project Details

Title:	Reliability-Based Assessment of Landslide Risk Along Roadways
Principal Investigators:	John Rice and James Bay
University:	Utah State University
Status:	Active
Year:	2017
Grant #:	69A3551747108 (FAST Act)
Project #:	MPC-561
RiP #:	01656347
RH Display ID:	15665
Keywords:	highways, landslides, monte carlo method, probability, reliability (statistics), risk assessment

Abstract

This research will adapt a procedure that the PIs have previously developed for assessment of underseepage and internal erosion risk for levees (Boulware and Rice 2017, Polanco and Rice 2014, 2012) to the problem of landslide disruption of roadways. Models will be developed for each geologic feature type that can assess the stability of the feature for ranges of geometric parameters (depth of deposit, slope inclination, groundwater level, etc.) and material properties (unit weight, strength, etc.). Depending on the complexity of the analysis, the landslide model may be represented by a closed-form equation or, in the case of a large number of input parameters, a response surface (a multi-dimensional function representing the relationship between input parameters and the failure potential). A Monte Carlo analyses will then be performed for each feature along the stretch of roadway using probability density functions (pdfs) representing the likelihood of a given parameter having a certain value over the range of possible values. The failure probability can be annualized by considering triggering events (such as rainfall events having calculated return frequencies) and assessing the effects of multiple levels of these events. The resulting fragility curve ties the probability of failure to the likelihood of the triggering event. This method will provide a tool for agencies to assess their annual risk due to landslide hazards and will give these agencies a means for optimizing their mitigation efforts.

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