To overcome the parameter inversion’s difficulty from the measurement uncertainty, mathematical model based on Bayesian inference was set up to estimate the coefficients in 2D convection diffusion equation with source. By Bayes’ theorem, the posterior distribution of model parameters was obtained, which is the solution of the inverse problem. While for multi parameter inversion problem, the posterior distribution obtained by numerical computation is hard to express easily,Markov chain Monte Carlo method is used to explore the posterior distribution to get the estimation. The effect of the observation position on inversion results was investigated and the form of the likelihood function’s effect was also studied. It indicates that the Laplacian distribution can lead to a robust estimation. Comparing the estimates under different number of measurement points, it can be concluded that at least two points are needed to ensure reasonable solution for the two parameters estimation problem of 2D steady convection diffusion equation.
