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Weather-related geo-hazards are a major concern for the railway industry m Canada. The financial losses that result from derailments and delays amount to millions of dollars every year. On the other hand, the assessment and management of geo-hazards is a difficult problem that involves complex coupled phenomena and numerous soil and weather parameters. The primary goal of this paper is to illustrate the manner whereby unsaturated soil mechanics can be taken from the soil property assessment level using techniques based on the soil-water characteristic curve (SWCC), to the solution of this real and highly complex problem. First, a concise description of the weather-related geo-hazards assessment model (W-GHA model) is given. Deterministic and probabilistic aspects of the model were developed within a Decision Analysis framework. The deterministic core of the model consists of a two-dimensional stability analysis combined with the analysis of the effects of weather conditions on the pore-water pressures. According to the proposed model, weather conditions interact with the ground through the flow of liquid water, water vapour, and heat. Critical embankment stability conditions are determined using a Dynamic Programming Method (DPM) combined with Finite Element based stress fields. The soil system is ultimately represented by a series of partial differential equations (PDE’s) governing conservation of mass and momentum. A discrete stochastic analysis is implemented within the proposed framework. Several unsaturated soil property functions are required as input to the system of PDE’s. The hydraulic conductivity (i.e., coefficient of permeability), vapour diffusion coefficient, thermal conductivity, volumetric specific heat, and shear strength are all nonlinear functions physically related to the SWCC. The methodology by which these soil property functions can be inter-related to the SWCC is presented. The theoretical model illustrates the manner whereby it is possible to quantitatively assess embankment stability based on weather conditions. The methodology is feasible and yet relatively comprehensive. [ABSTRACT FROM AUTHOR]