The variation and the spatial-temporal distribution of soil moisture content have significant effects on heat balance, agricultural moisture, etc. Research on the inversion of soil moisture content using reflectance spectral information can provide a theoretical basis for realizing rapid test of soil moisture content and revealing the spatial-temporal variation of the soil moisture content. In this paper, a semi-empirical model of reflectance spectral of black soil with different moisture content was built to thoroughly explore the relationship between the soil moisture content and the reflectance spectral. First, 12 soil samples with different moisture contents were prepared. Secondly, reflectance spectral of the black soil with different moisture content gradients was measured by ASD Field Spec Pro 3 spectrometer. Then, the soil surface reflection model was built by using the Fresnel reflectivity; In previous studies, the diffuse reflectance in the Kubelka-Munk (KM) model was often considered as a constant for a given material and illumination wavelength or a parameter that needed to be inverted. It has been found through research that diffuse reflectance is related not only to material and wavelength, but also to soil water content. By using the absorption and scattering coefficients which related to the soil moisture content, this model described the relationship between the soil moisture content and the diffuse reflectance. Besides, a model of volume scattering component was built based on KM theory; Furthermore, a semi-empiricalmodel of reflectance spectral of black soil with different moisture content was built. Next, according to the measurement data, the least squares algorithm was used to invert the model parameters, and the model was simplified by analyzing the inversion parameters. Finally, the data of different moisture content gradients that were not used for modeling were substituted into the model to verify the validity of the model. The results showed that compared with the spectral simulation accuracy in the range of 400～2 400 nm under different moisture contents, the root mean square error (RMSE) of reflectance spectra of soil with moisture content of 200 g·kg-1 is 0.008 which is the largest, and the RMSE of reflectance spectra of soil with moisture content of 40 g·kg-1 is 0.000 6 which is the smallest, the mean value of the RMSE of reflectance spectraof soil under different moisture contents is 0.005 1. In the range of 400～2 400 nm, the root mean square error of prediction (RMSEP) of black soil reflectance spectra at different wavelengths is generally less than 0.008. The RMSEP at 1 920 nm band is 0.002 068 which is the smallest. The soil in Changchun was collected to test the reliability of the model, and reflectance spectra of 15 soil samples with different moisture content were measured. Six samples were selected for model validation, and the remaining samples were selected as a calibration dataset for model calibration. The results showed that in 400～2 400 nm band, the RMSEP of reflectance spectra at different wavelengths is generally less than 0.015. The RMSEP at 525 nm band is 0.000 922 5 which is the smallest. In conclusion, the established model has a high prediction accuracy and can be well applied to simulate the reflectance spectra of black soil with different moisture contents.