The proposed project will investigate the development of a rapid-response drought monitoring tool prototype called the QuickDrought Response Index (QuickDRI) that integrates satellite-based vegetation, evapotranspiration, and soil moisture data with climateindex and biophysical data. QuickDRI will be designed to map and monitor early-stage and rapid-onset vegetation flash droughtstress, which is critical information needed to enhance the targeted application of the U.S. Drought Monitor (USDM) and associatedkey decision-making activities such as the multi-million dollar USDA Livestock Forage Disaster Program that use the USDM. MultipleNASA Earth Science products characterizing key components of the hydrologic cycles affecting vegetation drought stress will beintegrated into QuickDRI, including MODIS vegetation index data, GRACE and NLDAS soil moisture anomalies, and a GOES-basedEvaporative Stress Index (ESI). Climate indices that represent short-term climatic conditions (1 to 3 months) and other biophysicalcharacteristics (e.g., land use/land cover, soils, and topography) that can influence climate-vegetation interactions will also beincorporated into QuickDRI. A regression tree modeling approach will be applied to a 12-year time series of data for these variables togenerate weekly, empirical-based QuickDRI models across the growing season. Models will subsequently be applied to gridded data togenerate maps of short-term vegetation stress patterns across the continental United States (CONUS). For the Feasibility stage of thisproject, the two primary goals are to (1) develop a prototype QuickDRI tool and (2) establish a national network of drought expertsand decision makers to assess the utility of the various NASA Earth Science products for drought monitoring during tool developmentand evaluate the initial results from the QuickDRI prototype. NASA product inputs and QuickDRI output will be analyzed for thesevere 2011 drought in the south-central United States to determine the general performance of each product for monitoring vegetationdrought conditions.