The advent of real-time, short-term farm management tools is motivated by the need to protect water quality above and beyond the general guidance offered by existing nutrient management plans. Advances in high-performance computing and hydrologic or climate modeling have enabled rapid dissemination of real-time information that can assist landowners and conservation personnel with short-term management planning. This paper reviews short-term decision support tools for agriculture that are under various stages of development and implementation in the United States: (i) Wisconsin's Runoff Risk Advisory Forecast (RRAF) System, (ii) New York's Hydrologically Sensitive Area Prediction Tool, (iii) Virginia's Saturated Area Forecast Model, (iv) Pennsylvania's Fertilizer Forecaster, (v) Washington's Application Risk Management (ARM) System, and (vi) Missouri's Design Storm Notification System. Although these decision support tools differ in their underlying model structure, the resolution at which they are applied, and the hydroclimates to which they are relevant, all provide forecasts (range 24-120 h) of runoff risk or soil moisture saturation derived from National Weather Service Forecast models. Although this review highlights the need for further development of robust and well-supported short-term nutrient management tools, their potential for adoption and ultimate utility requires an understanding of the appropriate context of application, the strategic and operational needs of managers, access to weather forecasts, scales of application (e.g., regional vs. field level), data requirements, and outreach communication structure.
Short-term Forecasting Tools for Agricultural Nutrient Management.
Z. Easton,P. Kleinman,A. Buda,D. Goering,Nichole Emberston,Seann Reed,P. Drohan,M. Walter,P. Guinan,J. Lory,A. Sommerlot,A. Sharpley
Published 2017 in Journal of Environmental Quality
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- Publication year
2017
- Venue
Journal of Environmental Quality
- Publication date
2017-11-01
- Fields of study
Agricultural and Food Sciences, Medicine, Computer Science, Environmental Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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