Data assimilation has been successfully applied in atmospheric, oceanic, and land surface models. However, the fourdimensional variational (4DVar) assimilation system demands great computational costs. The authors introduced a new HistoricalSampleProjection data assimilation scheme(HSP4DVar), and accomplished the HSP4DVar land surface data assimilation system based on the Common Land Model(CoLM). As a scheme which requires no adjoint models, HSP4DVar can be directly solved and easily realized, therefore avoids high computational costs. The land surface data assimilation system was used to assimilate the soil moisture data for 56 months. After assimilation, the overall rootmeansquare error was significantly reduced with improved simulations, especially the simulation for the top 1000 mm layer.