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Enhancing the USDA FAS Crop Forecasting System Using SMAP L3 Soil Moisture Observations., , , and . IGARSS, page 5375-5377. IEEE, (2018)Benefit of modeling the observation error in a data assimilation framework using vegetation information obtained from passive-based microwave data., , , and . IGARSS, page 5325-5326. IEEE, (2016)Development and validation of the SMAP enhanced passive soil moisture product., , , , , , , , , and 28 other author(s). IGARSS, page 2539-2542. IEEE, (2017)Application of Triple Collocation in Ground-Based Validation of Soil Moisture Active/Passive (SMAP) Level 2 Data Products., , , , , , , , , and 2 other author(s). IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 10 (2): 489-502 (2017)Multivariate Calibration of the SWAT Model Using Remotely Sensed Datasets., , , , , , , and . Remote. Sens., 15 (9): 2417 (May 2023)Evaluating the application of microwave-based vegetation observations in an operational soil moisture data assimilation system., , , and . IGARSS, page 5190-5193. IEEE, (2015)Monitoring root-zone soil moisture through the assimilation of a thermal remote sensing-based soil moisture proxy into a water balance model, , and . Remote Sensing of Environment, 112 (4): 1268--1281 (April 2008)Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals., , , and . IEEE Trans. Geosci. Remote. Sens., 55 (12): 6780-6792 (2017)Impact of model coupling bias on water flux estimates acquired from a land data assimilation system.. IGARSS, page 3928-3930. IEEE, (2020)Evaluation of assimilated SMOS Soil Moisture data for US cropland Soil Moisture monitoring., , , , , , and . IGARSS, page 5244-5247. IEEE, (2016)