Robust, operational methodologies for mapping daily evapotranspiration (ET), soil moisture, and moisture stress over large areas using satellite remote sensing will have widespread utility in applications such as drought detection, crop yield forecasting, irrigation scheduling, water resource management, and weather and climate forecast initialization. Using thermal-infrared imagery from the Geostationary Operational Environmental Satellites (GOES), a fully automated inverse model of Atmosphere-Land Exchange (ALEXI) has been used to model daily ET and surface moisture stress over a 10-km resolution grid covering the continental United States. Examining monthly clear-sky composites of evaporative stress index for Apr-Oct 2002-2004, the ALEXI moisture stress index shows good spatial and temporal correlation with the Palmer Drought Index. The ALEXI index has the advantage of having higher spatial resolution and better comparability across seasons and climatic zones than do the Palmer Indices. The ALEXI moisture index also compares well to anomalies in monthly precipitation fields, proving that surface moisture has an identifiable thermal signature. The surface flux modeling techniques described here have demonstrated skill in identifying areas subject to soil moisture stress based on the thermal land-surface signature, without requiring information regarding antecedent rainfall. ALEXI therefore may have potential for operational drought monitoring in countries lacking well-established precipitation measurement networks.