Precision Agriculture Decision Support

Soil Condition Prediction in Support of Precision Agriculture

Weather, both directly and indirectly, is the critical factor in the success of a harvest and farmers' livelihoods. Severe weather events, such as hail, high winds, tornados, and flash floods can destroy an entire harvest in a very short period. However, many agricultural decisions simply require more accurate forecasts of the weather and the resultant soil conditions. Precise soil temperature and soil moisture forecasts are critical to the timely application of pesticides, seed and fertilizer selection, and to efficient irrigation practices. RAL has been collaborating with industry to develop agricultural decision support capabilities that optimizes the timing of pesticide application and irrigation. These projects typically utilize advanced weather and land surface models and an intelligent data fusion technology that continuously optimizes the weather and soil predictions. This research has led to improvements in the High-Resolution Land Data Assimilation System (HRLDAS), Dynamic, Integrated Forecast System (DICAST®), and Noah Land Surface Model. This research is instrumental in providing critical feedback to the weather and land surface modeling, and satellite communities and represents a cross disciplinary effort. Continued work in this area will lead to more precise prediction of weather and soil condition and more efficient and profitable agricultural operations.



Sue Ellen Haupt

Senior Scientist, Deputy Director Research Applications Laboratory