Proper parameter estimation is critical for enhancing the simulation capability of land surface models, yet the high dimensionality of model parameters significantly increases the difficulty of parameter estimation. Sensitivity analysis of model parameters aims at identifying the most sensitive parameters for further analysis in order to estimate the parameters with finite computer resources. In this study, we conducted sensitivity analysis of forty adjustable parameters selected from the Common Land Model (CoLM) using soil temperature and soil moisture data. The Morris method was used to qualitatively screen out the sensitive parameters from the insensitive ones. We also adopted the Sobol' sensitivity method to quantitatively estimate the sensitivity of the screened parameters. The main effect, interaction effect, and total effect of the parameters were computed. The results showed that the Morris method could provide reliable parameter sensitivity analysis using a relatively small sample size, and the Sobol' results provided a quantitative measure how each parameter contributes to the total variance of the model response, which was consistent with the results obtained by the Morris method.