Soil-water characteristic curve (SWCC) is a crucial input for modeling the geotechnical problems with unsaturated soil. The accuracy of modeling relies on the assessment of the model parameter uncertainty. In this paper a Bayesian framework is presented to evaluate the updated probability density function (PDF) of the uncertain model parameters for SWCC. The Bayesian analysis is applied to derive the PDF of the model parameters in various forms of van Genuchten equation using the observed data of sand, sandy loam and silty loam. The analysis demonstrates that a 2-parameter model is sufficient for curve-fitting of the SWCC and the two model parameters are approximately statistically independent. Furthermore, the model parameters are influenced by the soil texture. Finally, an engineering example of the probabilistic slope stability analysis is used to illustrate the application of the reliability of SWCC.