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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Potential for improved crop yield prediction through assimilation of satellite-derived soil moisture data

Authors
item Mladenova, Iliana
item Crow, Wade
item Doraiswamy, Paul
item Teng, B -
item Milak, S -

Submitted to: International Association of Hydrological Science
Publication Type: Proceedings
Publication Acceptance Date: November 1, 2010
Publication Date: N/A

Technical Abstract: Official U.S. Department of Agriculture (USDA) yield estimates are summarized in the monthly World Agricultural Supply and Demand Estimates (WASDE) report released by the World Agricultural Outlook Board (WAOB). WAOB analyses contributing to the yield estimates are done using the Global Agricultural Decision Support Environment (GLADSE), which is a comprehensive collection of data and tools that allows for the thorough interpretation of crop model forecasts. Soil moisture is both an essential component of these crop models and a critical data source input into GLADSE. This paper describes an Ensemble Kalman Filter based integration methodology that aims to improve the USDA Environmental Policy Integrated Climate model and GLADSE soil moisture information through the assimilation of a satellite-based surface soil moisture product derived from the Advanced Microwave Scanning Radiometer-Earth Observing System. This research, supported by NASA’s Applied Sciences Program, is a part of ongoing USDA efforts to develop data assimilation systems to improve agricultural crop yield prediction.

Last Modified: 7/28/2014
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