Predicting nitrate-nitrogen loads in subsurface drainage as a function of fertilizer application rate and timing in southern Minnesota

Grace L. Wilson, David J. Mulla, Jeffrey A. Vetsch, Gary R. Sands

Research output: Contribution to journalArticlepeer-review

Abstract

Fertilizer management practices that focus on applying N fertilizer at the right rate and time have been proposed as a practical option to reduce NO3–N losses from subsurface drained agricultural fields. In this study, regression equations were developed to predict NO3–N losses for a corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] rotation in southern Minnesota, using fertilizer application timing and rate and growing season precipitation as inputs. The equations were developed using the results of the field-scale hydrologic and N simulation model DRAINMOD-NII, first calibrated and validated for three sites in southern Minnesota, and then run with different combinations of N fertilizer application rates and timings. Fertilizer timing treatments included a single application in the fall or spring and a split-spring application (half applied preplant and the remaining applied as sidedress). The predictive regression equations showed that the split fertilizer application timing could reduce regional N loads by 28% compared with spring or fall applications. Greater reductions were predicted when the split timing was combined with lower N fertilizer rates. Utilizing the split application timing and reducing the fertilizer rate by 10 and 30% showed 33 and 41% reductions in N loads, respectively, compared with current fertilizer management practices. Such reductions in fertilizer application rates could be achieved through the use of variable-rate nitrogen (VRN) fertilizer technologies. Results of this modeling study indicate that synchronizing fertilizer application with crop requirements and utilizing VRN technologies could significantly reduce N loads to surface waters in southern Minnesota.

Original languageEnglish (US)
Pages (from-to)1347-1358
Number of pages12
JournalJournal of Environmental Quality
Volume49
Issue number5
DOIs
StatePublished - Sep 1 2020

Bibliographical note

Funding Information:
Funding for this study provided by the Clean Water Land and Legacy Amendment Fund administered through the Minnesota Department of Agriculture. Additional data provided by G. Feyereisen and J. Strock.

Publisher Copyright:
© 2020 The Authors. Journal of Environmental Quality © 2020 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America

PubMed: MeSH publication types

  • Journal Article

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