Turbidity is an important indicator for monitoring water environment and water quality, and the satellite remote sensing technology has the advantages of macroscopic spatial coverage and repeated sampling, which is an effective way of monitoring water turbidity. Based on the remote sensing reflectivity of NPP-VIIRS satellite, a water turbidity remote sensing inversion algorithm is developed and applied to the VIIRS satellite data to obtain a long-time series of satellite-derived water turbidity in the Bohai and Yellow seas. The results indicate that the proposed algorithm has a high accuracy with the R2 of 0.97, the root mean square error of 16 NTU, the mean absolute deviation of 23 NTU, and the mean relative error of 34.63%. On a spatial scale, the turbidity distributions are generally high in the near-shore areas and low in the offshore areas. In contrast in the time scale, the water turbidity is at a high level in winter, but the regions with high turbidity shrink in spring. The turbidity is generally at the lowest level in summer and only the coastal waters show high turbidity values. In autumn, the turbidity gradually increases.