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Accurate and precise characterization of the subsurface stratigraphic configuration (geological model) at a given site is crucial to geotechnical engineering work. The uncertainty in the derived stratigraphic configuration can be significant, due to the strata's complexity and inherent spatial variability coupled with the limited availability of borehole data. The characterization and reduction of this uncertainty should be part of any site characterization project. This paper presents a method for characterization of the subsurface stratigraphic configuration with limited borehole data. Within the framework of the proposed method, the spatial correlation between the existence of a stratum in one subsurface zone and that in the other subsurface zone (or the spatial correlation of the existence of the stratum) is captured by an autocorrelation function determined with the maximum likelihood principle. The initial stratigraphic configurations are first sampled with the conditional random field theory. Next, the maximum-a-posteriori (MAP) estimates of the initial stratigraphic configurations are derived using Markov Chain Monte Carlo (MCMC) and taken as the final stratigraphic realizations. The effectiveness of the proposed method and its advantages over the existing stratigraphic characterization methods are demonstrated through a series of comparative analyses. The versatility of the new approach in modeling the 3-D stratigraphic configuration is further revealed through a case study of a site in Western Australia. This paper adds to the literature on stratigraphic uncertainty characterization and provides a basis for a risk-based geotechnical assessment that considers geological and geotechnical uncertainties. • A probabilistic method for characterizing stratigraphic configuration is proposed. • The spatial correlation of strata is estimated with maximum likelihood principle. • Conditional random field theory and MCMC method are included in this method. • Versatility of this method in modeling 3-D stratigraphic configurations is studied. [ABSTRACT FROM AUTHOR]

The construction of the huge Three Gorges reservoir affected a large region, and the resultant geological and environmental impacts have caused global concern. The remarkable, 30-m annual fluctuation in the reservoir water level poses a significant threat to slope stability in this area. Four hundred sixty-two landslides were identified in the Zigui basin using historical records, satellite images, field investigations and unmanned aerial vehicle (UAV) observations, enabling the construction of a complete landslide database and distribution map. Three failure modes of landslides in the Zigui basin are used to illustrate the major factors that govern reservoir-induced landslides. The results show that (1) > 99% of identified landslides occur on slopes angle <47°, while >80% occur at elevations below 600 m; (2) Jurassic Niejiashan Formation is highly prone to landslides; (3) Low reservoir levels of 145 m to 155 m greatly reduce slope stability. Based on the information entropy method that use the conditional probability of different influencing factors and principal component analysis as inputs, the relative contributions of various influencing factors are quantified and a landslide susceptibility map was drawn. This susceptibility map helps define the countermeasures that will best reduce fatalities and property losses for areas having different landslide conditions and susceptibilities. • Database of 462 reservoir-induced landslides in Zigui basin, TGR was created. • Identifying failure modes and quantifying contributions of influential factors. • Conditional probability and information entropy model yields landslide susceptibility. • Susceptibility map, failure modes, and strategies suppressing the slope instability. [ABSTRACT FROM AUTHOR]