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Probabilistic analyses of landslide hazards and risks, bridging theory and practice

by El-Ramly, Hassan Mahmoud

Abstract (Summary)
Slope Engineering is perhaps the geotechnical subject most dominated by uncertainty. The impact of uncertainty on the qudity of slope performance predictions is ofien substantial. Current slope design practice based on the factor of safety canot directly address uncertainty. Probabilistic slope stability analysis is a rational means to incorporate uncertainty in the design process. It is also the most suitable approach for estimating hazard fiequency for site-specific quantitative nsk analyses. Unfortunately, the geotechnical profession has been slow in adopting such techniques. The objective of this work is to integrate probabilistic slope stability analysis into geotechnical practice as a practical design and decision-making tool. A spreadsheet approach for probabilistic slope analysis is developed. The rnethodology is based on Monte Car10 simulation using the commercial software @Risk and Excel. The analysis accounts for the spatial variability of the input variables as well as the various sources of systematic uncertainty. The output of the analysis is presented as the probability of unsatisfactory performance. It is a measure of the likelihood of the slope failing. The methodology is tested through the analysis of 10 case studies. It proved practical and flexible in handling a wide variety of real slope problems including effective and total stress analyses, complex stratigraphy, circular and non-circular slip surfaces and different slope analysis methods. The study indicates that the factor of safety alone can give a misleading sense of sdety and is not a sufficient sdety indicator. The probability of unsatisfactory performance is a more consistent safety measure. Curent slope design practice is calibrated probabilistically through the analysis of case studies of failed and safe slopes. A cornparison of the computed probabilities indicates that acceptable slope design practice is equivalent to a probability of unsatisfactory performance not exceeding 2x1 o-~, which couId be regarded as an upper design threshold. Stability assessments based on the results of both detenninistic and probabilistic andyses provide greater insight into design reliability and enhance the decision-making process. The study also shows that probabilistic slope analyses ignoring spatial variability of input parameters significantly overestirnate the probability of unsatisfactory performance. Other conclusions regarding the irnplementationand practical value of probabilistic slope analyses are also reached. Thanks are due to many people who, over the course of this study, provided me with enormous help and encouragement. This acknowledgment is but a smail appreciation for their pnceless support. The guidance and vision of Professor Norbert Morgenstern, my main supervisor, were instrumental in achieving the goals of this work. 1 thank him for his enthusiastic support, the unique mentoring environment he provided and the invaluable discussions we had. 1 also thank Professor David Cruden, my CO-supervisor, for his help and advice. His ideas, comments and thorough review of the thesis are greatly appreciated. The Geotechnical Engineering Group at the University of Alberta, both staff and colleagues, provided an exceptionaily cooperative and fi-iendly environment. In particular, thanks are due to Professor David Chan and Saily Petaske. 1 aiso thank Tamer El-Kateb, my officernate, for the helpful discussions we had. Appreciation is extended to Dr. Clayton Deutsch, mining group, for his help in geostatistics aspects. Thanks are also due to Syncrude Canada and Geotechnical Engkcering Office of Hong Kong for providing the data and technical reports of many of the case studies analyzed in this work. My brother Mohammad, his wife Aisha and their IittIe boy Mahmoud, have been a very supportive and caring farnily. I thank them for the wonderful times 1had with them. Finally, I am greatly indebted to my parents, Fawzy and Amal, for their continuous support, love and encouragement and to them I dedicate this work.
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Source Type:Master's Thesis

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Date of Publication:01/01/2001

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