A Bayesian framework for updating model parameters while considering spatial variability. Issue 4 (2nd October 2017)

• Record Type: Journal Article
• Authors: Ering, Pinom; Sivakumar Babu, G. L.
• Is Part Of: Georisk. Volume 11:Issue 4(2017)
• Page Start: 285
• Page End: 298
• Publication Date: 2017-10-02
• Subjects: Back analysis -- spatial variability -- probability -- Bayesian analysis -- random field -- slope remedial design; Environmental risk assessment -- Periodicals; Hazardous geographic environments -- Risk assessment -- Periodicals; Reliability (Engineering) -- Periodicals; Risk management -- Periodicals; 624.151
• DOI: 10.1080/17499518.2016.1255760
• Languages: English
• ISSNs: 1749-9518

Abstract

ABSTRACT: The study presents a recent slope failure in India which resulted in the burial of a village and claimed large number of lives. Current methods of probabilistic back analysis incorporate uncertainty in the analysis but do not consider spatial variability. In this study, back analysis is performed using Bayesian analysis in conjunction with random field theory. The probabilistic method is shown to be efficient in back-analysing a slope failure. It also provides confidence in parameter values to be used for post-failure slope design. The back analysis method which does not consider spatial variability overestimates the uncertainty in analysis, which can lead to uneconomical slope remediation design and measures.