In this work we take a Bayesian approach to the parameter calibration problem for heat transport in the shallow subsurface. We implement Markov Chain Monte Carlo methods using a one-dimenisonal nonlinear model for heat transport. The product of our simulations is a sample from the conditional distribution of the parameters given the data. We use this sample to make inferences about our parameters in each of three different climactic zones.