Soil moisture retrieval from SAR images is always affected by speckle noise, model errors and uncertainties associated to soil parameters, which impact negatively on the accuracy of soil moisture estimates. A Bayesian approach has been proposed to deal with these issues. As a natural advantage of the Bayesian approach, prior information about soil condition can be easily included. Based on simulations, the effect of prior information has been analyzed. It follows from simulations using the Oh's model that the soil moisture estimator is very sensitivity to the roughness prior.