The Relative Accuracy of DRIFTSIM When Used as a Real-Time Spray Drift Predictor

dc.contributor.author Kruckeberg, John
dc.contributor.author Hanna, H.
dc.contributor.author Darr, Matthew
dc.contributor.author Hanna, H. Mark
dc.contributor.author Steward, Brian
dc.contributor.department Agricultural and Biosystems Engineering
dc.date 2018-02-13T03:37:14.000
dc.date.accessioned 2020-06-29T22:38:47Z
dc.date.available 2020-06-29T22:38:47Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2012
dc.date.embargo 2012-12-03
dc.date.issued 2012-01-01
dc.description.abstract <p>Increasing regulation of spray drift has led to the development of real-time drift monitoring systems that present drift potential to applicators so that drift reduction spraying techniques can be implemented on an as-needed basis. The central component in each of these state-of-the-art systems is a drift prediction model. A real-time drift monitoring system was developed using look-up tables produced from simulations of a random-walk model (FLUENT via DRIFTSIM). The predictive accuracy of this system, evaluated as the difference between predicted drift and in-field measured drift, was compared to alternative prediction models to determine the suitability of random-walk models for real-time drift prediction. DRIFTSIM was found to produce a significantly more accurate representation of real-time predicted drift when compared to four of the six alternative models tested. No significant difference in predictive accuracy was found when comparing DRIFTSIM to the two other models. When compared to alternative models at incremented distances downwind from the point of spraying, DRIFTSIM’s predictions were found to be overall more accurate up to 10 m from the boom edge; however, three alternative models provided more accurate predictions for long-distance drift (20 to 50 m from the boom). These results suggest the potential of using DRIFTSIM in future real-time drift monitoring for increased accuracy and performance. However, additional development is needed to improve far-field (>10 m downwind of an application) drift prediction accuracy.</p>
dc.description.comments <p>This article is from <em><a href="http://elibrary.asabe.org/abstract.asp?aid=42234&t=3&dabs=Y&redir=&redirType=" target="_blank">Transactions of the ASABE</a></em>, 55, no. 4 (2012): 1159–1165.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/abe_eng_pubs/31/
dc.identifier.articleid 1028
dc.identifier.contextkey 3507226
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath abe_eng_pubs/31
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/1062
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/abe_eng_pubs/31/Steward_2012_RelativeAccuracyDRIFTSIM.pdf|||Fri Jan 14 23:29:51 UTC 2022
dc.subject.disciplines Agriculture
dc.subject.disciplines Bioresource and Agricultural Engineering
dc.subject.keywords Drift prediction
dc.subject.keywords DRIFTSIM
dc.subject.keywords Random-walk model
dc.subject.keywords Spray drift
dc.title The Relative Accuracy of DRIFTSIM When Used as a Real-Time Spray Drift Predictor
dc.type article
dc.type.genre article
dspace.entity.type Publication
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relation.isAuthorOfPublication 732298de-2ea9-4502-8fcf-3418080016e1
relation.isAuthorOfPublication ef71fa01-eb3e-4e29-ade7-bcb38f2968b0
relation.isOrgUnitOfPublication 8eb24241-0d92-4baf-ae75-08f716d30801
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