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Funded Research

Enhancing the USDA Global Crop Production Decision Support System with NASA Land Information System and Water Cycle Satellite Observations - PI

Crow, Wade: USDA ARS HRSL (Project Lead)
Bolten, John: (Institution Lead)
Reynolds, Curt: USDA FAS (Institution Lead)
Zhan, Xiwu: NOAA/NESDIS (Institution Lead)

Project Funding: 2010 - 2014

NRA: 2008 NASA: Decision Support through Earth Science Research Results   

Funded by NASA

Abstract:
The proposed project aims at enhancing the U. S. Department of Agriculture (USDA) Foreign Agricultural Service (FAS) global crop assessment decision support system via the integration of NASA soil moisture data products and adoption of NASA land surface modeling and data assimilation tools. USDA FAS crop yield forecasts affect decisions made by farmers, businesses, and governments by predicting fundamental conditions in global commodity markets. Regional and national crop yield forecasts are made by crop analysts based on the Crop Condition Data Retrieval and Evaluation (CADRE) Data Base Management System (DBMS). Soil moisture availability is a major factor impacting these forecasts and the CADRE DBMS system currently estimates soil moisture from a simple water balance model (the Palmer model) based on precipitation and temperature datasets operationally obtained from the World Meteorological Organization and U.S. Air Force Weather Agency. An on-going NASA Applied Sciences project has successfully assimilated NASA Advanced Microwave Scanning Radiometer (AMSRE) soil moisture retrievals into the existing USDA FAS Palmer model to create a global soil moisture analysis product. However, this existing product could be further enhanced in several aspects. First, its reliability is currently limited by the simplicity of the Palmer model. Recent software advances at NASA have led to the development of the Land Information System (LIS) data assimilation system. The modular nature of LIS enables the use of multiple (more physically complex) land surface models and contains an imbedded Ensemble Kalman filter data assimilation capability. As such, LIS provides an optimal framework for the integration of soil moisture products into the USDA CADRE system. Second, concerns over the future availability of AMSRE observations are hindering complete adoption of the approach. To address this need, new satellite sources of soil moisture retrieval products can be exploited to ensure the future continuity of soil moisture deliverables to USDA FAS. The proposed project will target the “Agricultural Efficiency” priority of NASA’s Applied Sciences Program. The specific objectives will be 1) maintaining the continuity of AMSRE soil moisture deliverables to the USDA FAS CADRE system, 2) developing contingency plans for a possible disruption in the availability of AMSRE data during the proposed project period, 3) designing a prototype of the CADRE DBMS system centered around NASA LIS, and 4) developing a LIS-compliant data assimilation system to integrate future soil moisture products from the upcoming NASA Soil Moisture Active/Passive mission into the CADRE DBMS system.


2011 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)

  • Potential Utility of Remotely-Sensed Surface Soil Moisture for Agricultural Productivity Forecasting   --   (Wade Crow, John Bolten, Grey Nearing, Kelly R Thorp, Rolf Reichle)   [abstract]
  • EV-1 Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) Mission Status   --   (Mahta Moghaddam, Wade Crow, Richard Cuenca, Dara Entekhabi, Anthony Freeman, Scott Hensley, David Hollinger, Paul R. Moorcroft, Rolf Reichle, Sassan Saatchi, Paul Shepson, Yunling Lou, Elaine Chapin)   [abstract]