82-9 Assessing Agricultural Climate Resilience: Creating a Decision Support System at the National Agricultural Statistics Service.

See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Agricultural Remote Sensing: I
Monday, November 16, 2015: 3:15 PM
Minneapolis Convention Center, L100 GH
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Noemi Guindin-Garcia1, Carol Crawford1, Clyde W. Fraisse2 and Ana Wagner3, (1)National Agricultural Statistics Service, United States Department of Agriculture, Washington, DC
(2)Agricultural and Biological Engineering, University of Florida, Gainesville, FL
(3)State Center for Research on Remote Sensing and Meteorology, University of Florida, Gainesville, FL
Monitoring crop condition and predicting yield on regional and national scales is becoming increasingly important in developing countries and has sustained importance for government agencies, private industry, and researchers under current weather and climate change conditions.  Improving the crop yield forecast is the subject of continual study in the United States Department of Agriculture’s National Agricultural Statistics Service (USDA-NASS).  In recent years, crop yield forecasting has become more challenging since anomalous weather conditions (e.g., droughts, heat waves, freezes, and floods) have been observed in major United States crop-producing regions. 

One of the main challenges in forecasting crop yields is to develop meaningful statistical indicators about crop condition during anomalous conditions due to the ability of plants to adapt and compensate during short period of stress.  USDA-NASS is developing a Decision Support System (DSS) to identify, measure, and monitor the effect of climate variability and extreme weather events on crop yields during the growing season. The NASS DSS will emerge from the expansion of AgroClimate and integration of existing products developed by the scientific community.  Agronomic parameters, soil, weather, and remote sensing data will be combined into a decision support system to develop meaningful statistical indicators about crop condition to adjust crop yield forecasts during anomalous weather conditions. The integration and adaptation of these products would greatly enhance NASS’s decision-making capability. 

See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Agricultural Remote Sensing: I