Short-term Forecasting Tools for Agricultural Nutrient Management

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dc.contributor.authorEaston, Zachary M.en
dc.contributor.authorKleinman, Peter J. A.en
dc.contributor.authorBuda, Anthony R.en
dc.contributor.authorGoering, Dustinen
dc.contributor.authorEmberston, Nicholeen
dc.contributor.authorReed, Seannen
dc.contributor.authorDrohan, Patrick J.en
dc.contributor.authorWalter, M. Todden
dc.contributor.authorGuinan, Paten
dc.contributor.authorLory, John A.en
dc.contributor.authorSommerlot, Andrew R.en
dc.contributor.authorSharpley, Andrewen
dc.contributor.departmentBiological Systems Engineeringen
dc.date.accessioned2019-09-18T16:48:04Zen
dc.date.available2019-09-18T16:48:04Zen
dc.date.issued2017-11en
dc.description.abstractThe 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.en
dc.description.notesThis review was supported, in part, by USDA-NRCS Conservation Innovation Grants to improve P indexing and modeling and to improve short-term forecasting tools for nutrient management planning.en
dc.description.sponsorshipUSDA-NRCS Conservation Innovation Grantsen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.2134/jeq2016.09.0377en
dc.identifier.eissn1537-2537en
dc.identifier.issn0047-2425en
dc.identifier.issue6en
dc.identifier.pmid29293860en
dc.identifier.urihttp://hdl.handle.net/10919/93756en
dc.identifier.volume46en
dc.language.isoenen
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.titleShort-term Forecasting Tools for Agricultural Nutrient Managementen
dc.title.serialJournal of Environmental Qualityen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.dcmitypeStillImageen

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