The Sacramento Soil Moisture Accounting (SAC-SMA) model of the National Weather Service River Forecast System (NWSRFS) is one of the land surface models (LSMs) running in the multi-agency/multi-university Land Data Assimilation System project. The objectives for running SAC-SMA in LDAS are: (1) to test the applicability of SAC-SMA in different climatic regimes; (2) to explore the use of new data sources which can potentially upgrade the physical representation of SAC-SMA; and (3) to provide a framework for developing and testing new data assimilation techniques. This paper will present simulation results of SAC-SMA in both real-time and retrospective modes. The space-time variability of water balance components (i.e., precipitation, runoff, evapotranspiration, and soil water storage) at the continental scale is analyzed. The issues related to parameter estimation, forcing data errors, and model initialization are investigated. Comparison of SAC-SMA simulation results against the results from other LSMs is conducted as well.