The goal of this project is to develop the seasonal predictive capacity for the Drought Monitor-Decision Support System (DM-DSS) using Earth science models and satellite products. The enhanced DM-DSS will assist society¿s response to a drought from a traditional ¿crisis management¿ scenario, which emphasizes emergency response, to a ¿risk management¿ approach, which places greater emphasis on preparedness planning and mitigation actions. Research objectives are as follows: 1.Incorporate into the existing DM-DSS the seasonal hydroclimatic predictions from a state-of-the-art Climate extension of Weather Research and Forecast (CWRF) model coupled with an advanced terrestrial hydrologic model, which assimilates real-time MODIS and GRACE data to improve the forecast/prediction. 2.Couple a decision analysis component with the predictive DM-DSS for optimal irrigation scheduling, which will provide end users more relevant decision support information at a lead time of up to one season. 3.Assess the quantitative and qualitative enhancements with NASA¿s Earth science models and remote sensing products by evaluating and comparing the baseline and benchmark levels of the predictive DM-DSS and relating them to stakeholders¿ perceived benefits. Both scientific testing and evaluation based on end users¿ surveys will be used for the benchmark development. An integrated system solution (ISS) is designed to incorporate the NASA earth science model, Global Modeling and Assimilation Office (GMAO) coupled GCM, climate and hydrologic prediction models, and decision analysis modules into the DM-DSS. The multidisciplinary research team of PIs includes the primary developers of the DM-DSS and the prediction and decision analysis models, with collaboration from NASA researchers. A shared-vision approach will be adopted to involve national and local end users¿ organizations for benchmarking the enhanced DM-DSS. This project will first contribute to ¿Water Management¿ by extending Earth science research results for optimal irrigation scheduling during drought periods. It will also contribute to other national priorities such as ¿Agricultural Efficiency¿ and ¿Disaster Management¿. The outcomes of this project will directly contribute to the USGEO activity on drought by developing prototype tools for drought management under the framework of the National Integrated Drought Information System (NIDIS)