The presentation will address the development of an operational system for optimal assimilation of thermal infrared (TIR) and microwave (MV) soil moisture (SM) and insertion of near real-time vegetation fraction (GVF) into the NLDAS Noah LSM towards the improvement of LSM-based drought monitoring. It has been demonstrated that diagnostic information about SM and evapotranspiration (ET) from MW and TIR remote sensing can reduce SM drifts in LSMs such as Noah. The two retrievals have been shown to be quite complementary: TIR provides relatively high spatial (down to 100 m) and low temporal resolution (due to cloud cover) retrievals over a wide range of GVF, while MW provides relatively low spatial (25-60 km) and high temporal resolution (can retrieve through cloud cover), but only over areas with low GVF. Furthermore, MW retrievals are sensitive to SM only in the first few centimeters of the soil profile, while TIR provides information about SM conditions integrated over the full root-zone, reflected in the observed canopy temperature. Outputs from the operational DA system will include near real-time (updated each night) maps of surface and root-zone SM, ET and runoff. Finally, an evaluation of SM moisture anomalies from the DA simulations will be compared to ALEXI ESI and standard drought metrics, including operational NLDAS output.