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For Review OnlyASSESSMENT OF NITRIFICATION AND UREASE INHIBITORS

ON NITRATE LEACHING IN CORN (ZEA MAYS L.)

Journal: Canadian Journal of Soil Science

Manuscript ID CJSS-2018-0110.R1

Manuscript Type: Article

Date Submitted by the Author: 13-Nov-2018

Complete List of Authors: Pawlick, Amy; North Carolina State University, Crop and Soil SciencesWagner-Riddle, C.; University of Guelph, School of Environmental SciencesParkin, Gary; University of Guelph, School of Environmental SciencesBerg, Aaron; University of Guelph, Geography

Keywords: Leaching, Nitrogen, Soil management, Application timing, Nitrification and urease inhibitors

Is the invited manuscript for consideration in a Special

Issue?:Not applicable (regular submission)

https://mc.manuscriptcentral.com/cjss-pubs

Canadian Journal of Soil Science

For Review Only

ASSESSMENT OF NITRIFICATION AND UREASE INHIBITORS ON NITRATE

LEACHING IN CORN (ZEA MAYS L.)

Amy A. Pawlick1, Claudia Wagner-Riddle2, Gary W. Parkin2, and Aaron A. Berg3

1Crop and Soil Sciences, North Carolina State University, Plymouth, North Carolina, 279092School of Environmental Sciences, University of Guelph, Guelph, Ontario, Canada N1G 2WI3Department of Geography, University of Guelph, Guelph, Ontario, Canada N1G 2WI

ABSTRACT

Agricultural ecosystems are one of the largest global contributors to nitrate (NO3-)

contamination of surface- and ground-water through fertilizer application. Improved fertilizer

practices are needed to manage crop nutrient supply in corn (Zea mays L.) while minimizing

impacts to clean water reserves. The goal of this study was to compare current nitrogen (N)

fertilizer practices (urea at planting) with ‘packages’ of improved management practices (a

combination of right timing and product) that farmers potentially use. We conducted

measurements in a continuous corn system from November 2015 to May 2017 at a large field

scale (four 4 ha plots). Nitrate concentration was measured below the root zone and drainage

estimated using a soil water budget approach where evapotranspiration was measured using the

eddy covariance method. The objective was to compare NO3--N leaching from fields receiving

urea vs. urea+NUI fertilizer applications at planting, urea-ammonium nitrate (UAN) vs.

UAN+NUI applied at sidedress and a combination of these practices: urea+NUI at planting vs.

UAN at sidedress. Drainage was only significant in the non-growing season. Neither fertilizer

products applied with NUI at planting or sidedress proved to significantly reduce NO3--N

leaching. The combination of delaying fertilization to sidedress and applying UAN significantly

reduced the soil water NO3--N concentration compared to urea+NUI at planting (mean of 5.2 vs.

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6.7 mg L-1) but only in 2015-2016. Based on these results, applying UAN at sidedress is

recommended, although additional study years are needed to confirm results.

Key words: Application timing, drainage, nitrogen, nitrate leaching, nitrification inhibitors and

urease inhibitors.

INTRODUCTION

Corn (Zea mays L.), one of the most prominent cereal crops cultivated in North America,

requires large amounts of nitrogen (N) fertilizer to achieve high yields (Ma et al. 2003). In

Canada, 66% of grain corn production occurs in Ontario (Statistics Canada 2011). The fertilizer

most commonly applied to corn worldwide at this time is urea due to low cost and availability

(USDA 2008; Witte 2011). Within 2 to 4 days of application, urea is hydrolyzed to ammonium

(NH4+) and then nitrified within 2 to 4 weeks to nitrate (NO3

-) (Firestone and Davidson 1989;

Carmona et al. 1990; Grant et al. 1996). However, this can be problematic as N uptake is largest

several weeks after planting (Aldrich and Hauck 1982; Fox et al. 1986). There is a time gap then,

between pre-plant fertilizer application and significant plant N uptake. Another issue is that in

humid regions such as Ontario, there is a surplus in the water budget as precipitation often

exceeds evapotranspiration (ET) during spring (April and May) and also winter (December to

March) (Fallow et al. 2003). The availability of excess water and the presence of NO3--N in the

soil water can result in downward movement of NO3--N. This introduces a problem for possible

NO3--N contamination in drinking water and represents nutrient loss for the plant.

Good nutrient management has advocated proper use of fertilizer best management

techniques (Singh and Sekkon 1978). Recently, the fertilizer industry has developed the 4R

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nutrient stewardship as a guideline of best management practices (right source, right rate, right

time and right place) to improve crop N use efficiency (NUE) and mitigate N losses, without

compromising crop yields (Snyder et al. 2009). Synchronizing N fertilization with plant

requirement has been proposed as a best management practice to reduce NO3--N leaching. One

way to accomplish this is by applying fertilizer several weeks after corn has emerged (sidedress

stage). However, application at planting is preferred by farmers due to the short window of time

that is often available for field operations before plant N requirements are high and as pre-plant

application is less costly to apply. Plant N requirement is strongest between V8 and silking,

while yield loss may occur when fertilization is delayed until V12 (Russelle et al. 1983; Scharf et

al. 2002).

Nitrification and urease inhibitors are compounds that can be added to urea-based

fertilizers to provide a possible alternative to sidedress application by potentially better

synchronizing nutrient release with plant requirement. Urease inhibitors (UI) slow the rate at

which urea is hydrolyzed to ammonium (NH4+) (Timilsena et al. 2015). The UI may reduce

gaseous losses of NH3 by suppressing the rate at which NH4+ is produced (Abalos et al. 2012).

By doing this, UI delay the release of N in the soil until soil conditions are less likely to cause

loss, which may also reduce losses via NO3--N leaching and/or N2O emissions. Nitrification

inhibitors (NI) slow the microbial conversion of NH4+ to NO3

- (Timilsena et al. 2015). By

retarding the rate of nitrification with a NI, NO3--N leaching and N2O gas emissions may be

reduced by maintaining N in the less mobile NH4+ form (Motavalli et al. 2008; Liu et al. 2013).

Combining a UI and NI is a possible mitigation method to target all pathways for N losses.

The nitrification inhibitor dicyandiamide (DCD) is one of the most popular compounds

used with urea as it is inexpensive, water insoluble and efficient in cold climates (Di and

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Cameron 2004; Hatch et al. 2005; Chien et al. 2009; Sanz-Cobena et al. 2012). Urea treated with

DCD has been found to reduce nitrous oxide (N2O) emissions and NO3--N leaching in grazed

pastures, vegetable systems (capsicum, amaranth, radish), wheat, barley and corn (Ball-Coelho

and Roy 1999; Majumdar et al. 2002; Cui et al. 2011; Di and Cameron 2012; Roche et al. 2016).

The most widely used and most effective UI is N-(n-butyl) thiophosphoric triamide

(NBPT or NBTPT) (Chai and Bremner 1987; Trenkel 2010). In these studies, urea+NBPT was

confirmed to reduce ammonia volatilization in grazed pastures and corn (Schlegel et al. 1986;

Bronson et al. 1989; Sanz-Cobena et al. 2008; Zaman et al. 2009). Field and laboratory studies

showed that urea+NBPT is effective in reducing NO3--N losses from well-drained loam-textured

soils (Bronson et al. 1989; Carmona et al. 1990; Clay et al. 1990; Rawluk et al. 2001).

Few studies have examined the effectiveness of the combination of NI and UI (NUI) in

humid climates or in corn systems (Halvorson et al. 2014; Connell et al. 2011; Soares et al. 2012;

Parkin Hatfield 2014; Venterea et al. 2016). Additional studies in these conditions are needed as

the effectiveness of NUI is highly dependent on weather variables, particularly soil moisture,

with effectiveness being reduced under dry conditions (Sanz-Cobena et al. 2012). Of existing

research, it has been found that NO3--N leaching was reduced with urea+NUI in intensive pasture

production and corn (Zaman and Blennerhassett 2010). In contrast to these results, other studies

have found that NO3--N losses were greater with urea+NUI compared to urea or urea+DCD

(Gioacchini et al. 2002; Sanz-Cobena et al. 2012). More research is needed to assess if urea+NUI

at planting may provide a beneficial reduction in NO3--N similar to applying nitrogen at

sidedress. To our knowledge there has been no prior field-scale studies in southern Ontario

investigating this comparison. In addition, it is not clear whether a further reduction may be

obtained by applying NUI at sidedress.

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We hypothesized that using fertilizer products with NUI would reduce NO3--N leaching

compared with a conventional fertilizer product. In addition, we hypothesized that applying

fertilizer products with NUI at planting would provide similar benefits as applying a

conventional fertilizer as a sidedress. We tested these hypotheses at a large field scale (four 4 ha

plots) where NO3--N concentration was measured below the root zone and drainage estimated

using a soil water budget approach where evapotranspiration was measured using the eddy

covariance method. This approach required large field plots and prevented the use of a typical

agronomic factorial experiment. Instead, our intention was to compare current practices (urea at

planting) with ‘packages’ of improved management practices (a combination of right timing and

product) that farmers potentially use. The objective was to compare NO3--N leaching from fields

receiving urea vs. urea+NUI fertilizer applications at planting, urea-ammonium nitrate (UAN)

vs. UAN+NUI applied at sidedress and a combination of these practices: urea+NUI at planting

vs. UAN at sidedress.

MATERIALS AND METHODS

Site Description and Experimental Design

This study was commenced in May 2015 and measurements started in November 2015

until May 2017. Drainage was not significant during the growing season of 2016; therefore,

presentation of results and discussion is concentrated in two non-growing season periods:

November 2015 to May 2016 and November 2016 to May 2017. The experimental site was at

the University of Guelph Elora Research Station near Elora, Ontario (43°39’ N 80°25’ W, 376 m

elevation). The soils at the research site are classified as a Grey-Brown Luvisol or Albic Luvisol

and the soil at our site is an imperfectly drained Guelph silt loam with 29% sand, 52% silt and

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19% clay (Morwick and Richards 1946; Jayasundara et al. 2007). The soil chemical

characteristics have been previously assessed as follows: pH: 7.6 (water) in the 0-15-cm layer,

organic carbon: 26.9 g Kg-1, total N: 2.4 g Kg-1, available phosphorus: 24 mg Kg-1, available

potassium: 146 mg kg-1 (Jayasundara et al. 2007). The field was tile drained in the 1960s with

distance between tiles of 15-m and approximate depth of 80-cm.

The experiment was conducted on a large homogeneous 30 ha micrometeorological study

area, necessary to directly measure evapotranspiration and derive drainage (see below). The

experimental approach consisted of applying the following fertilizer treatments to four 240 m by

170 m (4 ha) side-by-side fields: 1) urea broadcast and incorporated at planting, 2) urea+NUI

broadcast and incorporated at planting (NBPT and DCD; SuperU©, Koch Agronomic Services),

3) UAN injected at sidedress and 4) UAN+NUI (NBPT and DCD; AgrotainPlus©, Koch

Agronomic Services) injected at sidedress. The site was a continuous corn (Zea mays L.) system

with a conventional tillage management consisting of fall moldboard plowing and pre-seeding

cultivation. Study fields received the OMAFRA (2016) recommended fertilizer treatment rate of

150 kg N ha-1 differing by timing of N application (planting or sidedress) and product

(conventional or conventional+NUI).At planting, all fields received monoammonium phosphate

(MAP) side-banded at 250 kg ha-1 containing 30 kg N ha-1. Urea and urea+NUI were broadcast

at rates of 120 kg N ha-1 one day before planting and incorporated to 10-cm (May 12, 2015 and

May 11, 2016). UAN and UAN+NUI were injected between 70-cm rows at rates of 120 kg N ha-

1 at sidedress (June 25, 2015 and June 17, 2016, V6 and V4 respectively). Differences in

vegetative stage at time of fertilizer side-dress application were due to weather conditions and

the available window for fertilizer application in both years.

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Nitrate-N Leaching

The amount of NO3--N leached below the root zone ([NO3

--N]leached) was calculated by

multiplying the NO3--N concentration sampled from the soil water solution at 80-cm depth by

drainage volume estimated from the water budget (see below) according to the following

equation:

[1][𝑁𝑂3― ― 𝑁]𝐿𝑒𝑎𝑐ℎ𝑒𝑑 = [𝑁𝑂3

― ― 𝑁 ]80 𝑐𝑚 × 𝐷 × 0.01

where D is drainage in mm (L m-2), explained further in a following section, and [NO3--N]80 cm is

the NO3--N concentration (mg N L-1) sampled from soil water at 80-cm depth with porous

ceramic cup water samplers and 0.01 (kg ha-1) is a unit conversion factor to give units of kg N

ha-1 to [NO3--N]leached.

Soil water samplers consisted of a porous ceramic cup mounted to a 2.54-cm diameter

PVC pipe and sealed with rubber stopper. Two sets of plastic tubing were inserted into each

sampler with a shorter tube for applying internal pressure and water extraction. Porous ceramic

cups have low cost, provide minimal soil disturbance, are easy to install and collected soil

solution has been found to accurately represent NO3--N in drainage water compared with

monolith lysimeters and soil cores (Grossmann and Udluft 1991; Webster et al. 1993).

Samplers were installed in November 2015 to a depth of 80-cm using a 45° angle to

minimize above-cup soil disturbance and the influence of preferential flow (Lord and Shepherd

1993). Nine samplers were installed in a grid pattern in each field to provide spatial coverage.

Installation was accomplished by augering with a metal rod and using a 45°-angled ramp as a

guide. Flexible metal tubing was seated at the top of the PVC pipe to protect against rodent

damage and to allow burial beneath the soil for planting and harvest operations. Plastic

containers were secured to the metal tubing to house sample extraction connections.

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Soil water was sampled from soil water samplers every 1 to 2 weeks during the drainage

period from November to May each year. Sampling intervals were longer during dry periods or

when freezing temperatures prevented water extraction. When the soil was dry a suction of 50

kPa was applied to each water sampler using a hand vacuum pump. Samples were extracted from

the water sampler using pre-evacuated vials and stability of the NO3- ion was maintained post-

sampling by transporting samples from the field on ice. Samples were transferred to plastic

containers and frozen until analyzed using an autoanalyzer (Seal Analytical AA3). Arithmetic

mean NO3--N concentration was calculated from the nine sub-samples for each field and reported

for each sampling time.

Drainage

Direct measurements of drainage are costly and difficult to accomplish with minimal soil

disturbance (Ramos and Kücke 2001). A soil water budget approach provides a non-invasive

method to estimate drainage flow which combined with a measurement of NO3-N concentration

at depth can provide an estimation of NO3-N leaching (McCoy et al. 2006). Drainage at 80-cm

depth was calculated by a soil water budget approach (McCoy et al. 2006):

[2]𝐷 = 𝑃 ― 𝐸𝑇 ― ∆𝑆

where D is drainage, P is precipitation (rainfall + snowmelt), ET is evapotranspiration, and ∆S is

the change in soil water storage for the soil profile, all terms expressed in mm, and runoff

assumed negligible due to the level field conditions (McCoy et al. 2006). Factors D and ∆S can

be positive or negative values. When D is positive, drainage occurs and when D is negative there

is capillary rise in the soil profile. Data for each factor in Equation 2 was measured in 30-minute

periods before being aggregated to daily, then weekly values.

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Rainfall and snowfall data were obtained from the Environment Canada Elora Weather

Station adjacent to the study site. To provide an accurate estimate of precipitation and of the

winter snow water balance, snowmelt was added to rainfall. Rainfall was measured using a

tipping-bucket rain gauge from the Environment Canada Elora Weather Station. Water added to

the soil in the form of snowmelt was estimated by determining the snow water equivalent (SWE,

kg m-2) by multiplying the snow density (kg m-3) by snow depth (m) (Dingman 1994). Snow

depth and density measurements were collected at the experimental site when there were gains or

losses in snow on ground. Snow depth was measured using a meter stick and a known volume of

snow was collected using a snow tube, melted and then weighed to determine snow density

(Dingman 1994). Since manual snow depth measurements were not taken daily, snowfall was

also obtained from the Environment Canada Elora weather station from November to May each

year to gap fill between measured data. From these measurements, snowmelt was then calculated

using snow depth at the end of a week subtracted from the snow depth at the beginning of that

week. For periods when there was less snow remaining at the end of the week compared with the

beginning, snowmelt was added to precipitation to determine total precipitation (McCoy et al.

2006).

The ET was measured using two eddy covariance systems (EC), one installed in the East

side and one in the West side of the 30-ha field. Measurement of ET decreases the uncertainty in

drainage estimates using Eqn. (2). The main EC system was comprised of a sonic anemometer

(CSAT3, Campbell Scientific) and a closed-path EC155 (Campbell Scientific) analyzer, when

this was not available data from the open path LI-7500 (LI-COR) was used. The ET was

assumed to be representative of the entire 30-ha area and equal across all fields. The EC

measured the water vapour flux as an average latent heat flux (W m-2) in 30-min averages. The

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latent heat flux data was filtered for friction velocity (u*) less than 0.11 m s-1 to eliminate data

when there was weak turbulence, commonly during night time. Additionally, the data was

filtered for wind direction to eliminate periods where tower shadowing occurs when the angle

between horizontal wind and sonic axis was between 60° and 120°. Once filtered for u* and

wind direction, latent heat (LE) was converted to ET (kg m-2 or mm) by using the latent heat of

vaporization (2.5 x 106 J kg-1).

Missing half-hourly ET values were gap-filled using a fit through origin linear regression

equation derived from the measured EC data and the equilibrium evaporation (λET) (Priestley

and Taylor 1972):

[3]𝜆𝐸𝑇 = ∆

∆ + 𝛾 (𝑅𝑛 ― 𝐺)

where λET is equilibrium evaporation, Δ is the slope of saturated vapour pressure at a given

temperature, γ the psychrometric constant, Rn is net radiation and G soil heat flux. Equations

from Allen et al. (1998) were used to calculate Δ and γ. Net radiation was measured at the site

using a net radiometer. Gaps in Rn data were filled by running a linear regression between solar

radiation and Rn. The soil heat flux was assumed to be 10% of net radiation according to

approximation suggested by Allen et al. (1998). A fit through origin equation was calculated for

each non-growing season: 2015 to 2016 and 2016 to 2017. If there were missing data in the

measured EC data, then the slope from the fit through origin equation was multiplied by the λET

value to gap fill. In 2015-2016, the linear equation was EC=1.09λET with a R2=0.71, compared

with 2016-2017 of EC=1.43λET with a R2=0.86. The agreement coefficient (R2) is high

providing confidence that this technique provided an adequate gap-filling method.

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Change in soil water storage, ∆S, was calculated as an average for the whole field based

on volumetric soil water content (SWC) measurements derived from sensors in four locations. In

June 2015 water content reflectometers (WCR, Campbell Scientific Model CS616) were

installed horizontally in the soil. Two sensors were installed in each field at depths of 5-cm and

25-cm for a total of 8 sensors per depth and one sensor in each field at 55-cm and 85-cm for a

total of 4 sensors per depth. During field operations, the 5-cm and 25-cm WCR sensors were

removed to prevent possible damage.

The WCR allows for an indirect measurement of soil water content. The output from the

WCR gives a period of 15-40 µs or (0.7-1.6 ms). This output was converted to volumetric water

content (θ) according to the calibration equation by Kulasekera et al. (2011):

[4]𝜃 = 0.0008𝜏2 ― 0.0168𝜏 + 0.0609.

where τ is the WCR period (µs).

Soil temperature was also measured at the same locations as SWC at 5-cm depth using

soil copper-constantan thermocouples. The WCR and thermocouples were wired to a CR23X

(Campbell Scientific) datalogger and a solar panel for a power source. The CR23X datalogger

recorded data in 10-minute intervals from the sensors. The average SWC was calculated for the

two sensors at every depth per field and for soil temperatures at 5-cm. Missing values were gap

filled using linear interpolation. These data were then aggregated to 30-min, 60-min and one-day

values. For SWC, a weighted average function was then used to determine the average SWC for

each soil increment across the four fields (1-cm through 85-cm). Storage was calculated using

the average weighted function by multiplying average soil water content for one-day across

fields by the soil increment. The total storage in each layer was obtained from the product of the

volumetric water contents for each soil increment of 1 through 85-cm. ΔS was calculated as the

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difference in storage between one-day and the previous day. The values for ΔS were then

aggregated to weekly values.

Statistical Analysis

Comparisons of NO3--N leaching from the four fields were performed based on the soil

water NO3--N concentrations since drainage values used were common to all four plots. The

Wilcoxon signed rank-test (Rstudio 1.1.423; R Core Team, 2017) was selected for comparison of

paired treatment means as data were non-normally distributed (Shapiro-Wilks test P < 0.05).

This test is applicable to repeated measurements and has been used to compare N2O emissions

from a similar four plot setup (Wagner-Riddle et al., 2007; Tenuta et al., 2016). Three

comparisons were made to examine the objectives: 1) urea vs. urea+NUI at planting, 2) UAN vs.

UAN+NUI applied at sidedress and 3) a combination of these practices: urea+NUI at planting vs.

UAN at sidedress. We acknowledge that method of application (broadcasting for urea and

injection for UAN) confound comparison 3 but our intent was to compare a ‘package’ of

practices as they would likely be applied at the farm scale by producers, who typically inject

UAN at sidedress and do not broadcast urea at that time. Comparisons were made using

measured values of NO3--N concentrations (before data was interpolated) from nine pseudo-

replicate observations per treatment in two separate analyses for years 2015-2016 and 2016-

2017. A Bonferroni correction was applied as a more conservative approach to reduce the chance

of receiving a significant result due to chance and account for pseudo-replication. From this

correction, values were considered significantly different for all analyses when α < 0.0167

(0.05/3; significance level divided by the number of paired tests).

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RESULTS AND DISCUSSION

Precipitation and Evapotranspiration

The 2015 growing season (May-October) started wet in May and June followed by a drier

period, but overall was wet with precipitation of 532 mm compared to climate normals of 502

mm (Table 1). In contrast, the 2016 growing season started off very dry in May and June

followed by wet months in July and August, but overall drier than 2015 and climate normals

with precipitation of 401 mm. The 2015 non-growing season (November-April) was drier than

climate normals except March. In contrast, the 2016-2017 non-growing season precipitation

exceeded climate normals every month except November which was drier. As a result, overall

precipitation in the non-growing season of 2015-2016 was lower compared to 2016-2017. Over

the whole year (May-April), precipitation for 2015-2016 was only slightly higher with 977 mm

vs. 930 mm in 2016-2017, compared to climate normal of 916 mm. However, the seasonal

distribution was different in the two experimental years with precipitation in 2015-2016 being

concentrated in the growing season and in 2016-2017 in the non-growing season.

Similar to the precipitation trend, cumulative ET during the non-growing season

(November-April) was greater in 2016-2017 than 2015-2016 with 298 mm compared to 193 mm,

demonstrating that precipitation influenced ET (Fig 1). The observed differences in ET between

experimental years could also have been related to higher air temperature in 2016-2017

compared with 2015-2016 (Table 1). These ET measurements are higher than normal compared

to average ET estimated by Fallow et al. (2003) over a 47-year period where ET in November-

April was 87 mm. In both non-growing seasons, ET was relatively low until February when

thawing events and increasing temperatures increased ET, as expected (Fig. 1).

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Soil water content and storage

Despite a drier growing season in 2016 compared to 2015, average soil water content was

similar with 0.16 m3 m-3 at the start (November) of both non-growing seasons (Fig. 2). Over the

two-year experimental period, soil water content at 85-cm averaged 0.26 m3 m-3 and at 55-cm

0.31 m3 m-3. At 25-cm depth, soil water content was similar in both experimental years with

2015-2016 ranging from 0.27 m3 m-3 to 0.34 m3 m-3 and 2016-2017 from 0.20 m3 m-3 to 0.34 m3

m-3. The 5-cm depth showed the largest variations, and these were associated with liquid water

moving into and out of the solid phase during freeze-thaw events in the non-growing season (Fig.

2). Liquid soil water content at 5-cm decreased when soil was frozen at 5-cm depth and

increased when there was thawing (Fig. 2). The 5-cm range was narrower in 2015-2016 with

0.03 m3 m-3 to 0.24 m3 m-3 and wider range in 2016-2017 with 0.02 m3 m-3 to 0.33 m3 m-3. In

January through March of both experimental years, thawing periods can be observed with

increases in air temperature with higher peak values in soil water content observed in 2016-2017

at 5-cm depth up to 0.33 m3 m-3 compared to 0.18 m3 m-3 in 2015-2016 (Fig. 2). Thus, when

thawing periods occurred, there was higher liquid soil water content at the 5-cm depth for 2016-

2017.

There were large variations in weekly changes in soil water storage between both non-

growing seasons, with 2015-2016 varying less ranging from -16 mm to 29 mm, and 2016-2017

varying more from -43 mm to 51 mm (Fig. 3). In 2016-2017, the soil profile gained water

(ΔS>0) over a longer period (DOY 321-335, 356-364, and 81-95) than 2015-2016, although

times with water loss (ΔS<0) were less frequent in 2015-2016 (Fig. 3). It can be observed that

some storage gains were from thawing and storage losses were due to freezing as liquid water

moved in and out of the solid phase (Fig. 2). In 2015-2016, weekly gains in liquid water were

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apparent from November-March, with losses in water most prominent in January, February and

March (Fig. 3a). In 2016-2017, there were weekly gains and losses from November-May, with

large gain and loss events in February and March which were associated with freeze-thaw cycles

as liquid soil water and air temperature also increased during these periods (Fig. 2b and 3b).

Drainage

Modelling of drainage began in November 2015 (DOY 319) as this was when soil water

samplers were installed, and NO3--N leaching could be calculated. With the exception of two

weeks in 2016 where there was a total of 70 mm drainage (DOY 297-310), the remainder of the

weeks between DOY 104 to DOY 293 consisted of small negative values. After DOY 136, 2017,

drainage concluded and similar to that of 2016, remained negative throughout the growing

season.

Drainage during the non-growing season was slightly higher in 2016-2017 with

cumulative totals from November-April equal to 202 mm, compared to 2015-2016 with 186 mm

(data not shown). Drainage was higher than 30-year averages by Fallow et al. (2003) for the

same region where 151 mm of drainage was predicted from November-April. The seasonal

distribution of weekly drainage showed different trends with drainage being higher in Nov-Jan in

2016-2017 and higher in Feb-April in 2015-2016. Weekly values varied in 2015-2016 from -29

mm to 35 mm, with a greater range observed in 2016-2017 from -49 mm to 61 mm. Drainage

events coincided with peaks in precipitation, as expected (Fig. 3). Variations in drainage

(positive and negative) were much less in April continuing into May in both years most likely

from increased ET starting in June when plants are actively growing.

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Nitrate-N Concentration

The average soil water NO3--N concentrations in 2015-2016 for urea, urea+NUI, UAN

and UAN+NUI were 6.1, 6.7, 5.2 and 4.6 mg L-1 respectively. For the 2016-2017 non-growing

season, average soil water NO3--N concentrations were very similar for all treatments with 2.0,

2.1, 2.1 and 1.9 mg L-1, respectively, for urea, urea+NUI, UAN and UAN+NUI (Fig. 4). Among

all fields, NO3--N concentrations were below the Health Canada (2013) MAC guideline of 10 mg

L-1 throughout both years (Fig. 4). Overall, 2015-2016 had a trend for greater NO3--N

concentration than 2016-2017. Beginning in November 2015, NO3--N was already higher than in

2016, with a steady increase continuing into winter then decreasing in April-May. In contrast, in

2016-2017 NO3--N concentrations were low throughout November-March, except for urea+NUI

showing a slight increase, with a small increasing trend towards the end of the measurement

period starting at the end of April.

The highest NO3--N concentrations in 2015-2016 were likely due to low corn yields and

the high amount of residual NO3--N remaining in the soil after harvest. In 2015, the corn crop

performed poorer compared to 2016, resulting in significant differences in corn yield with UAN

resulting in significantly less yield (8.89 Mg ha-1) compared with urea, urea+NUI and

UAN+NUI (10.91, 10.85 and 10.21 Mg ha-1) (Ferrari Machado 2017). Compared to 2015, in

2016 there were no significant differences in corn yield with an average of 11.9 Mg ha-1 (Ferrari

Machado 2017). With increasing yield, there is more N removed from the field therefore a

decrease in mineral N in soil. This is indicated in higher soil NO3--N concentrations from 0-15-

cm depth in 2015, with November, 2015 concentrations for urea, urea+NUI, UAN and

UAN+NUI at 3.68, 2.90, 5.24, 3.45 mg L-1 as determined by a separate study at the same site,

respectively (Ferrari Machado 2017). In contrast, soil NO3--N at 0-15-cm depth in 2016 was

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lower for urea by a factor of 2.97, urea+NUI by 2.10, UAN by 3.77, and for UAN+NUI by 1.33

(with NO3--N concentrations of 1.24, 1.39, 1.39, and 2.59 mg L-1, respectively) (Ferrari Machado

2017). Thus, the lower corn yield in 2015 left more residual NO3--N in the soil explaining the

higher NO3--N concentrations sampled from soil water compared to 2016. The higher growing

season precipitation in 2015 compared to 2016 may have contributed to wet conditions

restricting crop growth leaving residual soil NO3--N in the soil post-harvest. Other studies have

reported poor crop yield to be associated with high residual NO3--N post-harvest (Randall and

Mulla 2001; Kladivko et al. 2004; Jayasundara et al. 2007).

In 2015-2016, the combination of delaying fertilization to sidedress and applying UAN

significantly reduced the soil water NO3--N concentration compared to urea+NUI at planting

(mean of 5.2 vs. 6.7 mg L-1; Fig. 4a), although we are not able to determine which was the

controlling factor (timing or product) and caution that method of application also differed

between treatments. Regardless, we are able to state that in this year applying NUI with urea did

not have a similar effect on soil water NO3--N concentration as delaying fertilizer application to a

time when crop uptake was larger. There were no significant differences between urea at

planting and urea+NUI at sidedress (6.1 vs. 6.7, respectively; Fig. 4a), or between UAN+NUI at

sidedress and UAN at sidedress (5.2 and 4.6 mg L-1; Fig. 4a). In 2016-2017 there were no

significant differences observed between treatments (Fig 4b).

Nitrate-N leaching

Nitrate leaching was calculated as the product of drainage and NO3--N concentration

(Fig. 5). Although monitoring of NO3--N concentration occurred throughout the growing season

in 2016, drainage was negligible and NO3--N leaching was not significant. Discussion presented

here focuses on non-growing season NO3--N leaching. In 2015-2016 there were high NO3

--N

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concentrations and low drainage compared with 2016-2017 where there were low NO3--N

concentrations and high drainage. In 2015-2016 there were several short NO3--N leaching events

in November and December, with a prolonged leaching event in January-March, followed by one

more event (DOY 83; Fig. 5a.) before drainage ceased in April (DOY 97; Fig. 5a). In contrast, in

2016-2017 there was one very small event in December, followed by frequent events in January

and February of small magnitude, before a larger event in March then a decrease until increasing

again in April (Fig. 5b).

Differences in NO3-N leaching between non-growing seasons were associated with

amount of drainage and NO3-N concentration. For example, in January-February 2016 when

NO3--N concentrations were high, NO3

--N leaching was also high when drainage events occurred

(Fig. 4a and 5a). There was also a period of NO3--N leaching in January-February 2017;

however, NO3--N concentrations were low and drainage values were low, thus leaching was

minimal (Fig. 4b and 5b).

Significant differences in NO3--N leaching between treatments were evaluated based on

NO3--N concentration comparisons given that the same drainage value was used for all

treatments. In 2015-2016, the combination of delaying fertilization to sidedress and applying

UAN significantly reduced NO3-N leaching compared to urea+NUI at planting. There were no

differences observed between other fertilizer treatments (Fig. 6a). Similarly, in 2016-2017 there

were no differences observed between any treatments (Fig. 6b).

There was a trend of higher NO3--N leaching in 2015-2016 than 2016-2017 likely due to

higher NO3--N concentrations, higher drainage, residual NO3

--N and non-growing season

precipitation. Other studies have indicated these to be the main factors controlling NO3--N

leaching (Drury et al. 1996; Tan et al. 2002; Kladivko et al. 2004; Arregui and Quemada 2006;

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Sanz-Cobena et al. 2012). Nitrate leaching was highest during January-March in both non-

growing seasons, while other research has found the highest NO3--N leaching losses in the fall

from high precipitation and residual NO3--N, although these studies did not evaluate winter NO3

-

-N leaching (Bergström and Brink 1986; Kladivko et al. 2004). —Nitrate leaching is more

prominent during the non-growing season as low ET with adequate P create ideal conditions for

D and with adequate NO3--N concentrations, leaching can occur. This is supported by research

from Tan et al. (2002) and Drury et al. (1996) that found NO3--N leaching occurred in this region

only during the non-growing season of November-April. Similarly, Jayasundara et al. (2007)

found that 80% of NO3--N leaching occurred from November through April.

Fertilizer with UAN at sidedress resulted in significantly less NO3--N leaching than

urea+NUI at planting in 2016-2017 but it is difficult to ascertain what caused the observed

difference since UAN was injected and also was a different form of N fertilizer than urea (Fig.

6a). Plant N use efficiency is maximized when fertilizer is applied several weeks after plant

emergence by supplying N when plant N requirement is high (Aldrich and Hauck 1982). Thus,

by increasing the synchronicity between fertilization and plant N demand, the UAN treatment

could have maximized N use efficiency and resulted in significantly lower NO3--N leaching

compared to urea+NUI. However, this result is inconsistent with post-harvest 2015 and also

2016 soil NO3--N levels at 0-15-cm depth since UAN had higher NO3

--N in the soil compared to

the other treatments. Injection would have minimized NH3 volatilization likely also keeping

more N in the soil (Drury et al., 2017).

The lack of significant reduction in NO3--N leaching between urea and urea+NUI in both

experimental years (Fig. 6) could potentially be explained by NBPT and DCD favouring

immobilization and maintaining N as NH4+ in the soil. Gioacchini et al. (2002) suggest that the

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availability of NH4+ in the soil may stimulate organic matter mineralization and the release of

mineral N promoting NO3--N leaching losses. There have been several studies that have shown

an increase in NO3--N leaching from the use of urea+NUI (DCD+NBPT, specifically)

(Gioacchini et al. 2002; Sanz-Cobena et al. 2012). Based on the findings of this study and

previous research, the abatement effect of NUI may be countered by soil N retention, which may

be why no difference was observed between urea and urea+NUI.

Although reduction in losses was expected with UAN+NUI compared to UAN, they did

not occur. A study on N2O emissions by Parkin and Hatfield (2014) also found no significant

differences between UAN and UAN+NUI, although they did not evaluate NO3--N leaching.

However, an opposing result was found by Ferrari Machado (2017) with UAN+NUI

significantly reducing N2O emission compared with UAN, which is in agreement with other

studies (Halvorson et al. 2010). Ferrari Machado (2017) suggests that the beneficial properties of

N can be negated by high water filled pore space after application. Thus, no difference may have

been found between UAN+NUI in this study as there was high water filled pore space after

application.

When expressing the NO3--N as a fraction of N fertilizer applied we observe slightly

higher values in 2015/2016 for urea+NUI and urea at planting (13.6% and 12.5%) than for UAN

and UAN+NUI at sidedress (9.9% and 8.8%). This is comparable to results from Jayasundara et

al. (2007) that found a NO3--N leaching loss of 16% from corn in a conventional system;

however, use of the 15N tracer indicated only 2% of this was derived from fertilizer. Thus, a low

percentage of NO3--N leaching losses are likely directly from fertilizer and some of the N lost

could be derived from mineralization of organic matter. Thus, there is a large percentage of N

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that is unaccounted for that could be lost by other pathways such as denitrification (N2O), or NH3

volatilization or immobilized in the soil as organic N.

CONCLUSIONS

Drainage was only significant in the non-growing season, therefore only this period was

evaluated for NO3--N leaching. There were differences in precipitation between the growing

seasons preceding the non-growing seasons with more precipitation received in 2015-2016 than

2016-2017. The environmental conditions during the non-growing seasons were also very

different as 2016-2017 received more precipitation, had higher ET and higher D, experienced

greater variation in 5-cm soil water content and change in soil water storage due to thawing

events. Also, 2015-2016 had higher NO3--N concentration in sampled soil water due to higher

soil residual NO3--N from a poor corn yield, compared to 2016-2017. As a result, NO3

--N

leaching showed a trend of higher values in 2015-2016 than 2016-2017.

Combining the 4R fertilizer strategies of right product and right timing was shown to

influence NO3--N leaching. Neither fertilizer products applied with NUI at planting or sidedress

proved to significantly reduce NO3--N leaching. Applying UAN at sidedress presented the best

management practice to reduce NO3--N leaching presumably due to synchronizing nutrient

supply with plant requirement. However, these results were inconsistent, and a significant

difference was only observed in 2015-2016. Based on these results, applying UAN at sidedress is

recommended, although additional study years are needed to confirm results.

Acknowledgments

Primary funding for the research from Fertilizer Canada and Agriculture and Agri-Food

Canada, is greatly appreciated. We would also like to thank Koch Fertilizer for supplying

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fertilizer sources. Technical assistance was provided by Peter von Bertoldi and Sean Jordan, for

which we are grateful.

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REFERENCES

Abalos, D., Sanz-Cobena, A., Misselbrook, T., and Vallejo, A. 2012. Effectiveness of urease

inhibition on the abatement of ammonia, nitrous oxide and nitric oxide emissions in a non-

irrigated Mediterranean barley field. Chemosphere 89: 310–318.

Bergström, L., and Brink, N. 1986. Effects of differentiated applications of fertilizer N on

leaching losses and distribution of inorganic N in the soil. Plant Soil 93: 333–345.

Bronson, K.F., Touchton, J.T., Hiltbold, A.E., and Hendrickson, L.L. 1989. Control of ammonia

volatilization with N‐(N-butyl) thiophosphoric triamide in loamy sands 1. Commun. Soil

Sci. Plant Anal. 20: 1439–1451.

Carmona, G., Christianson, C.B., and Byrnes, B.H. 1990. Temperature and low concentration

effects of the urease inhibitor N-(n-butyl) thiophosphoric triamide (nBTPT) on ammonia

volatilization from urea. Soil Biol. Biochem. 22: 933–937.

Chai, H.S., and Bremner, J.M. 1987. Evaluation of some phosphoroamides as soil urease

inhibitors. Biol. Fertil. Soils 3: 189–194.

Chien, S.H., Prochnow, L.I., and Cantarella, H. 2009. Recent developments of fertilizer

production and use to improve nutrient efficiency and minimize environmental impacts.

Adv. Agron. 102: 267-322.

Clay, D.E., Malzer, G.L., and Anderson, J.L. 1990. Ammonia volatilization from urea as

influenced by soil temperature, soil water content, and nitrification and hydrolysis

inhibitors. Soil Sci. Soc. Am. J. 54: 263-266.

Connell, J.A., Hancock, D.W., Durham, R.G., Cabrera, M.L., and Harris, G.H. 2011.

Comparison of enhanced-efficiency nitrogen fertilizers for reducing ammonia loss and

improving bermudagrass forage production. Crop Sci. 51: 2237–2248.

Page 23 of 39



For Review Only

Cui, M., Sun, X., Hu, C., Di, H.J., Tan, Q., and Zhao, C. 2011. Effective mitigation of nitrate

leaching and nitrous oxide emissions in intensive vegetable production systems using a

nitrification inhibitor, dicyandiamide. J. Soils Sediments 11: 722–730.

Di, H. J., and Cameron, K.C. 2012. How does the application of different nitrification inhibitors

affect nitrous oxide emissions and nitrate leaching from cow urine in grazed pastures? Soil

Use Manag. 28: 54–61.

Di, H.J., and Cameron, K.C. 2004. Effects of temperature and application rate of a nitrification

inhibitor, dicyandiamide (DCD), on nitrification rate and microbial biomass in a grazed

pasture soil. Aust. J. Soil Res. 42: 927–932.

Dingman, S.L. 1994. Snow and snowmelt. Pages 159–160 in Physical Hydrology. Macmillian

College Publishing Company, New York, NY.

Drury, C.F., Tan, C.S., Gaynor, J.D., Oloya, T.O., and Welacky, T.W. 1996. Influence of

Controlled Drainage-Subirrigation on Surface and Tile Drainage Nitrate Loss. J. Environ.

Qual. 25: 317.

Drury, C.F., Yang, X., Reynolds, W.D., Calder, W., Oloya, T.O. and Woodley, A.L. 2017.

Combining urease and nitrification inhibitors with incorporation reduces ammonia and

nitrous oxide emissions and increases corn yields. J. Env. Qual. 46:939–949.

Fallow, D., Brown, D., Parkin, G., Lauzon, J., and Wagner-Riddle, C. 2003. Identification of

critical regions for water quality monitoring with respect to seasonal and annual water

surplus. Guelph, ON, Canada.

Ferrari Machado, P.V. 2017. Effect of sampling strategies and nitrogen fertilization best

management practices on cumulative nitrous oxide emissions. The University of Guelph.

Page 24 of 39



For Review Only

Firestone M.K., and Davidson, E.A. 1989. Microbial basis of NO and N2O production and

consumption in soil. Exchange of trace gases between terrestrial ecosystems and the

atmosphere. M.O. Andrea D.S. Schimel, Ed. Exch. Trace Gases between Terr. Ecosyst.

Atmos.: Wiley, Toronto pp. 7–21.

Fox, R.H., Kern, J.M., and Piekielek, W.P. 1986. Nitrogen fertilizer source, and method and time

of application effects on no-till corn yields and nitrogen uptakes. Agron. J. 78: 741-746.

Gioacchini, P., Nastri, A., Marzadori, C., Giovannini, C., Vittori Antisari, L., and Gessa, C.

2002. Influence of urease and nitrification inhibitors on N losses from soils fertilized with

urea. Biol. Fertil. Soils 36: 129–135.

Grant, C.A., Brown, K.R., Bailey, L.D., and Jia, S. 1996. Volatile losses of NH3 from surface-

applied urea and urea ammonium nitrate with and without the urease inhibitors NBPT or

ammonium thiosulphate. Can. J. Soil Sci. 76: 417–419.

Grossmann, J., and Udluft, P. 1991. The Extraction of Soil-Water by the Suction-Cup Method - a

Review. J. Soil Sci. 42: 83–93.

Halvorson, A.D., Del Grosso, S.J., and Alluvione, F. 2010. Tillage and inorganic nitrogen source

effects on nitrous oxide emissions from irrigated cropping systems. Soil Sci. Soc. Am. J. 74:

436.

Halvorson, A.D., Snyder, C.S., Blaylock, A.D., and Del Grosso, S.J. 2014. Enhanced-efficiency

nitrogen fertilizers: potential role in nitrous oxide emission mitigation. Agron. J. 106: 715-

722.

Hatch, D., Trindade, H., Cardenas, L., Carneiro, J., Hawkins, J., Scholefield, D., and Chadwick,

D. 2005. Laboratory study of the effects of two nitrification inhibitors on greenhouse gas

Page 25 of 39



For Review Only

emissions from a slurry-treated arable soil: Impact of diurnal temperature cycle. Biol. Fertil.

Soils 41: 225–232.

Health Canada. 2013. Guidelines for Canadian drinking water quality: Guideline technical

document — nitrate and nitrite. Water and air quality bureau, healthy environments and

consumer safety branch, Ottawa, Ontario. [Online] Available:

http://healthycanadians.gc.ca/publications/healthy-living-vie-saine/water-paraquat-

eau/alt/water-paraquat-eau-eng.pdf.

Jayasundara, S., Wagner-Riddle, C., Parkin, G., Von Bertoldi, P., Warland, J., Kay, B., and

Voroney, P. 2007. Minimizing nitrogen losses from a corn-soybean-winter wheat rotation

with best management practices. Nutr. Cycl. Agroecosystems 79: 141–159.

Kladivko, E.J., Frankenberger, J.R., Jaynes, D.B., Meek, D.W., Jenkinson, B.J., and Fausey,

N.R. 2004. Nitrate leaching to subsurface drains as affected by drain spacing. 1813: 1803–

1813.

Kulasekera, P.B., and Parkin, G.W. 2011. Influence of the shape of inter-horizon boundary and

size of soil tongues on preferential flow under shallow groundwater conditions : A

simulation study. Can. J. Soil Sci. 91: 211-221.

Liu, C., Wang, K., and Zheng, X. 2013. Effects of nitrification inhibitors (DCD and DMPP) on

nitrous oxide emission, crop yield and nitrogen uptake in a wheat-maize cropping system.

Biogeosciences 10: 2427–2437.

Lord, E., and Shepherd, M. 1993. Developments in the use of porous ceramic cups for measuring

nitrate leaching. J. Soil Sci.: 435–449.

Page 26 of 39



For Review Only

Ma, B.L., Ying, J., Dwyer, L.M., Gregorich, E.G., and Morrison, M.J. 2003. Crop rotation and

soil N amendment effects on maize production in eastern Canada. Can. J. Soil Sci. 83: 483–

495.

Ma, B.L., Wu, T.Y., Tremblay, N., Deen, W., McLaughlin, N.B., Morrison, M.J., and Stewart,

G. 2010. On-farm assessment of the amount and timing of nitrogen fertilizer on ammonia

volatilization. Agron. J. 102: 134–144.

Majumdar, D., Pathak, H., Kumar, S., and Jain, M.C. 2002. Nitrous oxide emission from a sandy

loam Inceptisol under irrigated wheat in India as influenced by different nitrification

inhibitors. Agric. Ecosyst. Environ. 91: 283–293.

McCoy, A.J., Parkin, G., Wagner-Riddle, C., Warland, J., Lauzon, J., von Bertoldi, P., Fallow,

D., and Jayasundara, S. 2006. Using automated soil water content measurements to estimate

soil water budgets. Can. J. Soil Sci. 86: 47–56.

Morwick, F.F., and Richards, N.R. 1946. Soil survey of Wellington County. Report no. 35 of the

Ontario Soil Survey.

Motavalli, P.P., Goyne, K.W., and Udawatta, R.P. 2008. Environmental impacts of enhanced-

efficiency nitrogen fertilizers crop management. Crop Manag.

OMAFRA. 2015. 2016 Field Crop Budgets. Publication 60, Toronto, Canada.

Parkin, T.B., and Hatfield, J.L. 2014. Enhanced efficiency fertilizers: Effect on nitrous oxide

emissions in Iowa. Agron. J. 106: 694–702.

Priestley, C.H.B., and Taylor, R.J. 1972. On the assessment of surface heat flux and evaporation

using large-scale parameters. Monthly Weather Review. 100: 81-92.

R Core Team. 2017. R: A language and environment for statistical computing. R

Foundation for Statistical Computing, Vienna, Austria.

Page 27 of 39



For Review Only

Randall, G.W., and Mulla, D.J. 2001. Nitrate nitrogen in surface waters as influenced by climatic

conditions and agricultural practices. J. Environ. Qual. 30: 337–344.

Rawluk, C.D.L., Grant, C.A., and Racz, G.J. 2001. Ammonia volatilization from soils fertilized

with urea and varying rates of urease inhibitor NBPT. Can. J. Soil Sci. 81: 239–246.

Roche, L., Forrestal, P.J., Lanigan, G.J., Richards, K.G., Shaw, L.J., and Wall, D.P. 2016. Impact

of fertiliser nitrogen formulation, and N stabilisers on nitrous oxide emissions in spring

barley. Agric. Ecosyst. Environ. 233: 229–237.

Russelle, M.P., Hauck, R.D., and Olson, R.A. 1983. Nitrogen accumulation rates of irrigated

maize. Agron. J. 75: 593-598.

Sanz-Cobena, A., Misselbrook, T.H., Arce, A., Mingot, J.I., Diez, J.A., and Vallejo, A. 2008. An

inhibitor of urease activity effectively reduces ammonia emissions from soil treated with

urea under Mediterranean conditions. Agric. Ecosyst. Environ. 126: 243–249.

Sanz-Cobena, A., Sánchez-Martín, L., García-Torres, L., and Vallejo, A. 2012. Gaseous

emissions of N2O and NO and NO3- leaching from urea applied with urease and nitrification

inhibitors to a maize (Zea mays) crop. Agric. Ecosyst. Environ. 149: 64–73.

Scharf, P.C., Wiebold, W.J., and Lory, J.A. 2002. Corn yield response to nitrogen fertilizer

timing and deficiency level. Agron. J. 94: 435-441.

Schlegel, A.J., Nelson, D.W., and Sommers, L.E. 1986. Field evaluation of urease inhibitors for

corn production. Agron. J. 78: 1007–1012.

Singh, B. and Sekhon, G.S. 1978. Nitrate pollution of groundwater from farm use of nitrogen

fertilizers – a review. Agric. Environm., 4: 207-225.

Page 28 of 39



For Review Only

Snyder, C.S., Bruulsema, T.W., Jensen, T.L., and Fixen, P.E. 2009. Review of greenhouse gas

emissions from crop production systems and fertilizer management effects. Agric. Ecosyst.

Environ. 133: 247–266.

Soares, J.R., Cantarella, H., and Menegale, M.L. de C. 2012. Ammonia volatilization losses from

surface-applied urea with urease and nitrification inhibitors. Soil Biol. Biochem. 52: 82–89.

Statistics Canada. 2011. Canada year book 2011. Ottawa, ON. [Online] Available:

http://www.statcan.gc.ca/pub/11-402-x/2012000/pdf/agriculture-eng.pdf [2016 Nov. 16].

Tan, C.S., Drury, C.F., Reynolds, W.D., Groenevelt, P.H., and Dadfar, H. 2002. Water and

nitrate loss through tiles under a clay loam soil in Ontario after 42 years of consistent

fertilization and crop rotation. Agric. Ecosyst. Environ. 93: 121–130.

Tenuta,M., Gao, X., Flaten, D.N., and Amiro, B.D. 2016. Lower nitrous oxide emissions from

anhydrous ammonia application prior to soil freezing in late fall than spring pre-plant

application. J. Env. Qual. 45:1133–1143.

Timilsena, Y. P., Adhikari, R., Casey, P., Muster, T., Gill, H., & Adhikari, B. 2015.

Enhanced efficiency fertilisers: a review of formulation and nutrient release patterns.

Journal of the Science of Food and Agriculture 95: 1131-1142.

Trenkel, M.E. 2010. Slow- and controlled-release and stabilized fertilizers: An option for

enhancing nutrient use efficiency in agriculture. CEUR Workshop Proceedings.

International Fertilizer Industry Association (IFA), Paris, France.

Venterea, R.T., Coulter, J.A., and Dolan, M.S. 2016. Evaluation of intensive “4R” strategies for

decreasing nitrous oxide emissions and nitrogen surplus in rainfed corn. J. Environ. Qual.

45: 1186.

Page 29 of 39



For Review Only

Wagner-Riddle, C., Furon, A., McLaughlin, N.L., Lee, I., Barbeau, J., and Jayasundara, S. 2007.

Intensive measurement of nitrous oxide emissions from a corn-soybean wheat rotation

under two contrasting management systems over five years. Glob. Change Biol. 13:1722–

1736.

Webster, C.P., Shepherd, M.A., Goulding, K.W.T., and Lord, E. 1993. Comparisons of methods

for measuring the leaching of mineral nitrogen from arable land. J. Soil Sci. 44: 49–62.

Witte, C.P. 2011. Urea metabolism in plants. Plant Sci. 180: 431–438.

Zaman, M., and Blennerhassett, J.D. 2010. Effects of the different rates of urease and

nitrification inhibitors on gaseous emissions of ammonia and nitrous oxide, nitrate leaching

and pasture production from urine patches in an intensive grazed pasture system. Agric.

Ecosyst. Environ. 136: 236–246.

Zaman, M., Saggar, S., Blennerhassett, J.D., and Singh, J. 2009. Effect of urease and nitrification

inhibitors on N transformation, gaseous emissions of ammonia and nitrous oxide, pasture

yield and N uptake in grazed pasture system. Soil Biol. Biochem. 41: 1270–1280.

Zhengping, W., Van Cleemput, O., Liantie, L., and Baert, L. 1991. Effect of organic matter and

urease inhibitors on urea hydrolysis and immobilization of urea nitrogen in an alkaline soil.

Biol. Fertil. Soils 11: 101–104.

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Figure Captions

Figure 1. Cumulative gap-filled ET for Nov to May in 2015-2016 (black) and 2016-2017 (grey).

DOY = day of year.

Figure 2. Daily soil volumetric water content (θ) at 5-cm (light black), 25 (light grey), 55-cm

(black) and 85-cm (dark grey) depths, soil temperature at 5-cm (soilT; medium grey) and air

temperature (airT; dotted line) from November 2015 to May 2016 (a) and November 2016 to

May 2017 (b). Gaps in data are from equipment failure or removal for planting/harvesting

operations.

Figure 3. Weekly components of the water budget: P (rainfall + snowmelt; bar graph with

horizontal line), ET (evapotranspiration; black line), D (drainage; dashed line) and ∆S (change in

storage; dashed line) from November 2015 to May 2016 (a) and November 2016 to May 2017

(b).

Figure 4. The NO3--N concentrations at 80-cm depth during the non-growing seasons for urea

(light grey), urea+NUI (light black), UAN+NUI (black) and UAN (dark grey) from November

2015 to May 2016 (a) and November 2016 to May 2017 (b). Error bars represent standard error

of mean. Note that NO3--N was monitored throughout the growing season; however, D was

negligible and as such only the non-growing season was included in this study.

Figure 5. Weekly amounts of NO3--N leached during the non-growing seasons for urea (light

grey), urea+NUI (light black), UAN+NUI (black) and UAN (dark grey) from November 2015 to

May 2016 (a) and November 2016 to May 2017 (b). Note that NO3--N was monitored throughout

the growing season; however, D was negligible and thus, NO3--N leaching did not occur.

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Figure 6. Paired NO3--N leaching comparisons between treatments of urea (white) vs. urea+NUI

(black), UAN (diagonal cross) vs, UAN+NUI (dotted), and urea (black) + NUI vs. UAN

(diagonal cross) from November 2015 to May 2016 (a) and November 2016 to May 2017 (b).

Asterisk denotes significant differences of paired means according to the Wilcoxon sign rank test

applied at a significance level of 0.0167 (=0.05/3 or significance level divided by the number of

paired tests; Bonferroni correction) to reduce the chance of receiving a significant result due to

chance and account for pseudo-replication. Error bars represent mean uncertainty +/- 10%.

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Table 1. Average monthly temperature and monthly precipitation (rainfall + snowfall) at Elora

Research Station compared with climate normals (1981-2010) (Waterloo Wellington:

http://climate.weather.gc.ca/climate_normals/index_e.html).

Month Daily average temperature (°C) Monthly precipitation (mm)Normals 2015/2016 2016/2017 Normals 2015/2016 2016/2017 2017

Maya 12.5 15.5 13.1 82.3 109.4 36.4 120.8June 17.6 16.6 17.5 82.4 172.6 30.6 N/AJuly 20 19.1 20.6 98.6 60.6 81.2 N/AAugust 18.9 17.8 20.8 83.9 87 143 N/ASeptember 14.5 16.9 16.6 87.8 22.6 55.6 N/AOctober 8.2 8.1 9.9 67.4 80.6 54 N/ANovember 2.5 4.6 4.8 87.1 78.2 55.6 N/ADecember -3.3 2.5 -4.0 71.2 66.7 90.1 N/AJanuary -6.5 -6.2 -4.4 65.2 50.6 119.6 N/AFebruary -5.5 -4.3 -2.3 54.9 50.1 78.1 N/AMarch -1 1.0 -2.8 61.0 140.8 94.1 N/AApril 6.2 3.7 7.8 74.5 57.8 92 N/AaDaily average temperature (C) in May 2017 of 10.8.

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http://climate.weather.gc.ca/climate_normals/index_e.html

For Review Only

Figure 1

143x102mm (240 x 240 DPI)

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Figure 2

99x121mm (240 x 240 DPI)

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Figure 3

93x120mm (240 x 240 DPI)

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Figure 4

88x119mm (240 x 240 DPI)

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Figure 5

90x118mm (240 x 240 DPI)

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Figure 6

82x120mm (240 x 240 DPI)

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