In this study, the approaches adopted in the assimilation of hydrological remote sensing data were introduced. Emphasis was placed on the advantages and disadvantages of the commonly used methods in both variational and sequential data assimilation. Focusing on the assimilation of soil moisture and streamflow, the application progress of multisource observations including the soil moisture, streamflow, precipitation, evapotranspiration and snow cover in hydrological simulation and forecast was analyzed in detail. On this basis, the issues existed in the application of multisource observations in hydrological modeling were explored. Finally, future development trends of hydrological remotesensing data assimilation were proposed in terms of both data assimilation method and multisource data assimilation application. It is believed that the potential of remote sensing and insitu multisource data assimilation in improving the hydrological simulation and forecast will increase with the improvement of remote sensing observations and reversion techniques, the refinement of hydrological model structure and the optimization of data assimilation approaches. The integrated application of multisource observations in hydrological simulation and forecast will be the inevitable trend in the development of hydrological data assimilation.