Decision Support for Wisconsin's Manure Spreaders: Development of a Real-Time Runoff Risk Advisory Forecast

Persistent Link:
http://hdl.handle.net/10150/305874
Title:
Decision Support for Wisconsin's Manure Spreaders: Development of a Real-Time Runoff Risk Advisory Forecast
Author:
Goering, Dustin C.
Issue Date:
2013
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
The Runoff Risk Advisory Forecast (RRAF) provides Wisconsin's farmers with an innovative decision support tool which communicates the threat of undesirable conditions for manure and nutrient spreading for up to 10 days in advance. The RRAF is a pioneering example of applying the National Weather Service's hydrologic forecasting abilities towards the Nation's water quality challenges. Relying on the North Central River Forecast Center's (NCRFC) operational Snow17 and Sacramento Soil Moisture Accounting Models, runoff risk is predicted for 216 modeled watersheds in Wisconsin. The RRAF is the first-of-its-kind real-time forecast tool to incorporate 5-days of future precipitation as well as 10-days of forecast temperatures to generate runoff risk guidance. The forecast product is updated three times daily and hosted on the Wisconsin Department of Agriculture, Trade, and Consumer Protection (DATCP) website. Developed with inter-agency collaboration, the RRAF model was validated against both edge-of-field observed runoff as well as small USGS gauged basin response. This analysis indicated promising results with a Bias Score of 0.93 and a False Alarm Ratio (FAR) of only 0.34 after applying a threshold method. Although the threshold process did dampen the Probability of Detection (POD) from 0.71 to 0.53, it was found that the magnitude of the events categorized as hits was 10-times larger than those classified as misses. The encouraging results from this first generation tool are aiding State of Wisconsin officials in increasing awareness of risky runoff conditions to help minimize contaminated agriculture runoff from entering the State's water bodies.
Type:
text; Electronic Thesis
Keywords:
manure management; runoff risk; Natural Resources; Decision Support Services
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College; Natural Resources
Degree Grantor:
University of Arizona
Advisor:
Guertin, D. Phillip

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleDecision Support for Wisconsin's Manure Spreaders: Development of a Real-Time Runoff Risk Advisory Forecasten_US
dc.creatorGoering, Dustin C.en_US
dc.contributor.authorGoering, Dustin C.en_US
dc.date.issued2013-
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThe Runoff Risk Advisory Forecast (RRAF) provides Wisconsin's farmers with an innovative decision support tool which communicates the threat of undesirable conditions for manure and nutrient spreading for up to 10 days in advance. The RRAF is a pioneering example of applying the National Weather Service's hydrologic forecasting abilities towards the Nation's water quality challenges. Relying on the North Central River Forecast Center's (NCRFC) operational Snow17 and Sacramento Soil Moisture Accounting Models, runoff risk is predicted for 216 modeled watersheds in Wisconsin. The RRAF is the first-of-its-kind real-time forecast tool to incorporate 5-days of future precipitation as well as 10-days of forecast temperatures to generate runoff risk guidance. The forecast product is updated three times daily and hosted on the Wisconsin Department of Agriculture, Trade, and Consumer Protection (DATCP) website. Developed with inter-agency collaboration, the RRAF model was validated against both edge-of-field observed runoff as well as small USGS gauged basin response. This analysis indicated promising results with a Bias Score of 0.93 and a False Alarm Ratio (FAR) of only 0.34 after applying a threshold method. Although the threshold process did dampen the Probability of Detection (POD) from 0.71 to 0.53, it was found that the magnitude of the events categorized as hits was 10-times larger than those classified as misses. The encouraging results from this first generation tool are aiding State of Wisconsin officials in increasing awareness of risky runoff conditions to help minimize contaminated agriculture runoff from entering the State's water bodies.en_US
dc.typetexten_US
dc.typeElectronic Thesisen_US
dc.subjectmanure managementen_US
dc.subjectrunoff risken_US
dc.subjectNatural Resourcesen_US
dc.subjectDecision Support Servicesen_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineNatural Resourcesen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorGuertin, D. Phillipen_US
dc.contributor.committeememberValdes, Juan B.en_US
dc.contributor.committeememberOsterkamp, Waite R.en_US
dc.contributor.committeememberHawkins, Richard H.en_US
dc.contributor.committeememberGuertin, D. Phillipen_US
dc.contributor.committeememberRestrepo, Pedro J.en_US
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