A Bayesian Forecast Model for the Climatic Response of Unsaturated Soils

The climate-driven volumetric response of unsaturated soils (shrink-swell and frost heave) frequently causes costly distresses in lightly loaded structures (pavements and shallow foundations) due to the sporadic climatic fluctuations and soil heterogeneity which is not captured during the geotechnical design. The complexity associated with the unsaturated soil mechanics combined with the high degree of variability in both the natural characteristics of soil and the empirical models which are commonly implemented tends to lead to engineering judgment outweighing the results of deterministic computations for the basis of design. Recent advances in the application of statistical techniques and Bayesian Inference in geotechnical modeling allows for the inclusion of both parameter and model uncertainty, providing a quantifiable representation of this invaluable engineering judgement. The overall goal achieved in this study was to develop, validate, and implement a new method to evaluate climate-driven volume change of shrink-swell soils using a framework that encompasses predominantly stochastic time-series techniques and mechanistic shrink-swell volume change computations. Four valuable objectives were accomplished during this research study while on the path to complete the overall goal: 1) development of an procedure for automating the selection of the Fourier Series form of the soil suction diffusion equations used to represent the natural seasonal variations in suction at the ground surface, 2) development of an improved framework for deterministic estimation of shrink-swell soil volume change using historical climate data and the Fourier series suction model, 3) development of a Bayesian approach to randomly generate combinations of correlated soil properties for use in stochastic simulations, and 4) development of a procedure to stochastically forecast the climatic parameters required for shrink-swell soil volume change estimations. The models presented can be easily implemented into existing foundation and pavement design procedures or used for forensic evaluations using historical data. For pavement design, the new framework for stochastically forecasting the variability of shrink-swell soil volume change provides significant improvement over the existing empirical models that have been used for more than four decades.