[Objective] Soil hydraulic properties refer mainly to soil hydraulic conductivity and water characteristic curve, which are essential basic data for numerical simulation of soil water movement. Most soils in nature are present in layers, but in the simulation experiments so far done, the soils were assumed to be homogeneous in texture. [Method] Through an indoor soil column infiltration test, vertical one-dimensional water movement was numerically simulated with the aid of Hydrous-1D software, and numerical inversions were carried out with the variables (cumulative infiltration volume, pressure head and combination of both) measured in the infiltration process in the indoor soil column infiltration test as objective functions to optimize the parameters obtained of the hydraulic properties of each layers of the static soil. In the light of the evaluation indices, such as determination coefficient (R²), root mean square error (RMSE), coefficient of variation (CV_S), correlation matrix of the optimized parameters and standard error of the optimized parameters, effects of different measured variables on non-uniqueness and accuracy of the solution were discussed. [Result] Results show that when the objective functions contain only the cumulative infiltration, although the value simulated through inversion is in good agreement with the measured value, R² reached up to 0.999 and RMSE was less than 0.005 62 cm, but the parameters verified with the measured value of pressure head was not so good in accuracy, with R² being only 0.338, and RMSE less than 0.096 5 cm. When the pressure head was used as the objective function for parameter optimization and solution, the fitting degree R² reached up to 0.855 and RMSE was less than 0.038 4 cm; the use of the measured value of cumulative infiltration in verification was quite good in effect, with R² reaching up to 0.99 and RMSE being less than 0.038 56 cm. The simulation of hydraulic properties of the soil through inversion using cumulative infiltration and pressure head in combination was quite high in goodness of fit, with R² reaching more than 0.905 and RMSE less than 0.035 4 cm. Although in the inversion, the indices, R² and RMSE, were inferior to that using cumulative infiltration, the inversion reduced correlation and standard error of the optimized parameters to a certain extent, thereby reducing the solution Non-uniqueness, and improving accuracy of the solution. [Conclusion] The above conclusions may serve as reference for selection of measured variables for use in the inversion for parameters of transient flow in the static soil.