PART I: Properties --Constructing multivariate distributions for soil parameters -- Modeling and simulation of bivariate distribution of shear strength parameters using copulas -- PART II: Methods -- Evaluating reliability in geotechnical engineering -- Maximum likelihood principle and its application in soil liquefaction assessment --Bayesian analysis for learning and updating geotechnical parameters and models with measurements -- Polynomial chaos expansions and stochastic finite-element methods -- Practical reliability analysis and design by Monte Carlo Simulation in spreadsheet -- PART III: Design -- LRFD calibration of simple limit state functions in geotechnical soil-structure design -- Reliability-based design: Practical procedures, geotechnical examples, and insights -- Managing risk and achieving reliable geotechnical designs using Eurocode 7 -- PART IV: Risk and decision -- Practical risk assessment for embankments, dams, and slopes -- Evolution of geotechnical risk analysis in North American practice -- Assessing the value of information to design site investigation and construction quality assurance programs --Verification of geotechnical reliability using load tests and integrity tests -- PART V: Spatial variability -- Application of the subset simulation approach to spatially varying soils.

Establishes Geotechnical Reliability as Fundamentally Distinct from Structural Reliability. Reliability-based design is relatively well established in structural design. Its use is less mature in geotechnical design, but there is a steady progression towards reliability-based design as seen in the inclusion of a new Annex D on "Reliability of Geotechnical Structures" in the third edition of ISO 2394. Reliability-based design can be viewed as a simplified form of risk-based design where different consequences of failure are implicitly covered by the adoption of different target reliability indices. Explicit risk management methodologies are required for large geotechnical systems where soil and loading conditions are too varied to be conveniently slotted into a few reliability classes (typically three) and an associated simple discrete tier of target reliability indices.