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Fate of Applied Nitrogen under Forced Runoff and Leaching from Bermudagrass Fairways

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Title:
Fate of Applied Nitrogen under Forced Runoff and Leaching from Bermudagrass Fairways
Physical Description:
1 online resource (101 p.)
Language:
english
Creator:
Adams, Ryan S
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Master's ( M.S.)
Degree Grantor:
University of Florida
Degree Disciplines:
Horticultural Sciences, Environmental Horticulture
Committee Chair:
Unruh, Joseph Bryan
Committee Co-Chair:
Kruse, Jason Keith
Committee Members:
Sartain, Jerry B

Subjects

Subjects / Keywords:
bermudagrass -- leaching -- nitrogen -- runoff
Environmental Horticulture -- Dissertations, Academic -- UF
Genre:
Horticultural Sciences thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract:
Numerous regulations and ordinances have recently been enacted to reduce nonpoint source pollution from turfgrass systems as a result of Nitrogen (N) runoff and leaching.  A worst case scenario field study was conducted to determine the fate of applied N from bermudagrass fairways. Each 48 kg N ha-1 fertilizer treatment was applied to a 7% slope at four separate interval distances (0.0, 0.9, 1.8, and3.6 m) and was immediately followed by an irrigation event of 46 mm hr-1.The N leaching study was to determine N fate following a 144 kg N ha-1application coupled with excess natural and simulated rainfall. Forced runoff and leachate samples were collected systematically after treatment and analyzed for Total Soluble Nitrogen (TSN) (Antek 9000N Series analyzer).  Runoff TSN loads were significantly affected by fertilizer source with the highest loads occurring from the soluble source ammonium sulfate (4.13 mg TSN L-1) > ureaformaldehyde (1.04 mgTSN L-1) > polymer coated urea (0.06 mg TSN L-1) =control (0.02 mg TSN L-1). A 3.6 m unfertilized buffer for ureaformaldehyde reduced TSN loads by a quantity of 0.26 to 0.75 mg TSN L-1 in contrast to 1.8 m buffer. Results from the N leaching found inconsistent results in the first event, followed by TSN levels in the second and third below the analytical instrument’s method detect limit (MDL) of 1.0 mg TSN L-1.
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility:
by Ryan S Adams.
Thesis:
Thesis (M.S.)--University of Florida, 2013.
Local:
Adviser: Unruh, Joseph Bryan.
Local:
Co-adviser: Kruse, Jason Keith.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2013
System ID:
UFE0046019:00001

MISSING IMAGE

Material Information

Title:
Fate of Applied Nitrogen under Forced Runoff and Leaching from Bermudagrass Fairways
Physical Description:
1 online resource (101 p.)
Language:
english
Creator:
Adams, Ryan S
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Master's ( M.S.)
Degree Grantor:
University of Florida
Degree Disciplines:
Horticultural Sciences, Environmental Horticulture
Committee Chair:
Unruh, Joseph Bryan
Committee Co-Chair:
Kruse, Jason Keith
Committee Members:
Sartain, Jerry B

Subjects

Subjects / Keywords:
bermudagrass -- leaching -- nitrogen -- runoff
Environmental Horticulture -- Dissertations, Academic -- UF
Genre:
Horticultural Sciences thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract:
Numerous regulations and ordinances have recently been enacted to reduce nonpoint source pollution from turfgrass systems as a result of Nitrogen (N) runoff and leaching.  A worst case scenario field study was conducted to determine the fate of applied N from bermudagrass fairways. Each 48 kg N ha-1 fertilizer treatment was applied to a 7% slope at four separate interval distances (0.0, 0.9, 1.8, and3.6 m) and was immediately followed by an irrigation event of 46 mm hr-1.The N leaching study was to determine N fate following a 144 kg N ha-1application coupled with excess natural and simulated rainfall. Forced runoff and leachate samples were collected systematically after treatment and analyzed for Total Soluble Nitrogen (TSN) (Antek 9000N Series analyzer).  Runoff TSN loads were significantly affected by fertilizer source with the highest loads occurring from the soluble source ammonium sulfate (4.13 mg TSN L-1) > ureaformaldehyde (1.04 mgTSN L-1) > polymer coated urea (0.06 mg TSN L-1) =control (0.02 mg TSN L-1). A 3.6 m unfertilized buffer for ureaformaldehyde reduced TSN loads by a quantity of 0.26 to 0.75 mg TSN L-1 in contrast to 1.8 m buffer. Results from the N leaching found inconsistent results in the first event, followed by TSN levels in the second and third below the analytical instrument’s method detect limit (MDL) of 1.0 mg TSN L-1.
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility:
by Ryan S Adams.
Thesis:
Thesis (M.S.)--University of Florida, 2013.
Local:
Adviser: Unruh, Joseph Bryan.
Local:
Co-adviser: Kruse, Jason Keith.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2013
System ID:
UFE0046019:00001


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1 FATE OF APPLIED NITROGEN UNDER FORCED RUNOFF AND LEACHING FROM BERMUDAGRASS FAIRWAYS By RYAN STUART ADAMS A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR TH E DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2013

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2 2013 Ryan Stuart Adams

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3 To my par ents for their love and support

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4 ACKNOWLEDGMENTS I wish to express my gratitude to Dr. Bryan Unruh and Dr. Ja s on Kruse, the co chair of my supervisory committee. Dr. Unruh and Dr. Kruse gave me the opportunity to follow my dream of attaining a Master of Science degree and also provided mentoring and inspiration along the way. I am also appreciative to the other me mber of my supervisory committee Dr. Jerry Sartain, for his guidance, encouragement and wisdom. Special thanks go to Phil Moon, biological scientist at the West Florida Research and Education Center, and Mark Kann, manager of the Plant Science Education a nd Research Unit, for their assistance and management of my studies. Thanks go to Jayson Ging and Jason Haugh who provided insight and assistance during my graduate studies. Thanks also go to my fellow turf graduate students Brian Glenn, Natasha Restuccia, and Jing Zhang for assistance and encouragement. Finally, thanks go to my parents Todd and Lori Adams and the rest of my family, whose reassurance and support never stopped.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 9 LIST OF ABBREVIATIONS ................................ ................................ ........................... 11 ABSTRACT ................................ ................................ ................................ ................... 12 CHAPTER 1 GEN ERAL INTRODUCTION ................................ ................................ .................. 14 Bermudagrass Fertilization and Maintenance ................................ ......................... 15 Mitigating Nonpoint Source Pollution Unfertilized Buffer Strips ............................... 17 N Leaching Following High Application Rates ................................ ........................ 20 2 WIDTH OF TURFGRASS UNFERTILIZED BUFFER STRIPS AND THEIR IMMEDIATE INFLU ENCE ON NITROGEN FERTILIZER MOVEMENT FOLLOWING EXCESS IRRIGATION ................................ ................................ ..... 23 Introduction ................................ ................................ ................................ ............. 23 Materials and Methods ................................ ................................ ............................ 24 Res ults ................................ ................................ ................................ .................... 31 Total Kjeldahl Nitrogen and Biomass for Turfgrass Clippings ........................... 33 Soil Moisture ................................ ................................ ................................ ..... 33 Total Ortho Phosphate Loading in Runoff ................................ ........................ 34 RVI and NDVI Reflectance ................................ ................................ ............... 35 Visual Assessments ................................ ................................ ......................... 36 Dark Green Color Index Imagery ................................ ................................ ...... 37 Discussion ................................ ................................ ................................ .............. 38 3 TOTAL SOLUBLE NITROGEN LEACHED FROM NINE FERTILIZER SOURCES IN A BERMUDAGRASS FAIRWAY RECEIVING EXCESSIVE IRRIGATION ................................ ................................ ................................ ........... 72 Introduction ................................ ................................ ................................ ............. 72 Materials and Methods ................................ ................................ ............................ 73 Results ................................ ................................ ................................ .................... 77 Discussion ................................ ................................ ................................ .............. 78 4 CONCLUSIONS ................................ ................................ ................................ ..... 88

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6 APPENDIX A IRRIGATION UNIFORMITY FOR JAY LEACHING STUDY ................................ ... 90 B PERCOLATION RATES FOR LEACHING EVENT BY DAYS AFTER TREATMENT ................................ ................................ ................................ .......... 91 LIST OF REFERENCES ................................ ................................ ............................... 92 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 101

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7 LIST OF TABLES Table page 2 1 Runoff study area textural analysis data from Nov. 2011 to depth of 15.2 mm .. 51 2 2 Grouping co variance estimates for total soluble nitrogen analy sis .................... 51 2 3 Analysis of variance for total soluble nitrogen and ortho phosphate ................... 52 2 4 Total soluble nitrogen loads by fertilize r source averaged across three runs ..... 52 2 5 Tukey for buffer strip sizes ................................ ................................ ............................ 53 2 6 Tukey ................................ ...... 53 2 7 Analysis of variance for total Kjeldahl nitrogen clippings ................................ .... 54 2 8 Total Kjeldahl nitrogen clippings tissue analysis for fertilizer treatment by buffer strip size averaged across runoff events ................................ .................. 54 2 9 Total Kjeldahl nitrogen tissue clip pings analysis by runoff event ........................ 55 2 10 Analysis of variance for clipping biomass ................................ ........................... 55 2 11 Differences in clipping biomass colle ction for days after initiation across fertilizer source by buffer strip size ................................ ................................ ..... 56 2 12 Analysis of variance for soil moisture ................................ ................................ 56 2 13 Soil moisture differences across fertilizer treatment (source by buffer strip size) ................................ ................................ ................................ .................... 57 2 14 Tukey phosphate loads influence by differing ureaformaldeh ................................ .................... 58 2 15 Analysis of variance for normalized difference vegetation index, ratio vegetative index, visual color, visual quality, and visual density ......................... 58 2 16 ........ 59 2 17 Ratio vegetative index values for subplot location by .................. 61 2 18 Normalized difference vegetation index values for subplot location by runoff ................................ ................................ ................................ ............... 62 2 19 Visual col ................................ .. 63

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8 2 20 ............................... 64 2 21 .............................. 65 2 22 ......................... 66 2 23 Analysis of variance for dark green color index ................................ .................. 68 2 24 Dark green color index separated by distance adjacent to fertilized swath ........ 69 2 25 Dark green color index separated by fertilizer source by buffer strip size ........... 70 2 26 Dark green color index for distance away from fertilized swath by events .......... 71 3 1 Leaching study nitrogen fertilizer sources ................................ .......................... 84 3 2 Analysis of variance for total soluble nitrogen leachate ................................ ...... 85 3 3 Analysis of variance for visual color, visual quality, and visual density ............... 85 3 4 Total soluble nitrogen leachate loads by days after trea tment during the first event ................................ ................................ ................................ ................... 86 3 5 Visual color, visual quality, and visual density ratings by days after treatment ... 87 3 6 Vi sual color ratings for leaching event by fertilizer source ................................ .. 87

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9 LIST OF FIGURES Figure page 2 1 Compiled Thirty Year Weather Data for the Citra, FL region: NOAA National Climatic Data Center ................................ ................................ .......................... 41 2 2 Plant Science Research and Education Unit (PSREU) Soil pH Map. Photo courtesy of the Inst. of Food and Agric. Sci., Univ. of Florida, Gainesv ille. Area of interest is located in the northern part of field six. ................................ .. 42 2 3 A V shaped aluminum collection weir was situated at the downslope end of each runoff plot. Runoff water that accum ulated at the collection weir was directed through approximately 61.0 cm of 5.1 cm PVC drain pipe into a 114.0 L plastic barrel. Sleeves and buckets were removed during runoff events. Photo courtesy of Ryan Adams. ................................ ............................. 42 2 4 The number of images for dark green color index values was dependent on the unfertilized buffer strip size; with a possibility of 1, 3, 5, or 9 distances for 0.0, 0.9, 1.8, and 3.6 m, respectively. Each distance refers to the distance away from the fertilized swath with 1 = the 56 cm increment adjacent to the fertilized swath, 2 = the 56 to 112 cm area downslope of fertilized swath. For example in this image, a 1.8 m buffer treatment would have five distances, with distance 1 b eing adjacent to the fertilized swath, while distance 4 would be the unfertilized buffer strip section next to collection weir. Distance 0 refers to the fertilized swath. Photo courtesy of Ryan Adams. ........................... 43 2 5 Total soluble nitrogen (TSN) loads determined with nitrogen source application of ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated urea (PCU) by runoff event: May, June and August. Means with the same letter in a given sour ce were not significantly different (P = 0.05) ................................ ................ 44 2 6 Influence of unfertilized buffer strip size on total soluble nitrogen (TSN) loads below an ureaformaldehyde fertilized swath. Lines represent 95% confidence limits and overall means using Proc Glimmix for each unfertilized buffer strip size. 4 5 2 7 Soil moisture content percentage (SMC%) across runoff events sorted by time of collection. In each runoff event, soil moisture was taken before and after runoff initiation. Means with the same letter in a given collection time were not significantly different (P = 0.05) according to Tukey separation. ................................ ................................ ................................ .......... 46 2 8 Total ortho phosphate (OP) runoff loads as influenced by application of ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated urea (PCU) separate d by runoff event: May, June, August. Means with the same

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10 letter in a given source were not significantly different (P = 0.05) according to ................................ ................................ .... 47 2 9 Total ortho phosphate (OP) loads by runoff event: May, June, August. Means with the same letter were not significantly different (P = 0.05) according to ................................ ................................ .... 48 2 10 Three ev ent average normalized difference vegetation index (NDVI) values Bars at each DAI represent 95% confidence intervals. Normalized difference vegetation index (NDVI) value was calc ulated using: NDVI = (R NIR R red )/(R NIR + R red ). ................................ ................................ ............................... 49 2 11 Three event average of visual quality and density ratings by days after 0.05). Bars at each DAI represent 95% confidence intervals. Scale is from 1 to 9, 9=optimal turf quality/density, 6=acceptable turf quality/density. ........................ 50 3 1 Compiled Thirty Year Weather Data for the Jay, FL region from 1982 2012: NOAA National Climatic Data Center ................................ ................................ 81 3 2 Total soluble nitrogen (TSN) Loads in leachate from September 20 th 2011 to February 5 th 2012. ................................ ................................ ............................. 82 3 3 Rainfall in Jay, FL from September 20 th 2011 to February 5 th 2012. ................ 83

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11 LIST OF ABBREVIATIONS A S Ammonium sulfate B MPS Best management practices D GCI Digital gree n color index D IA Digital image a nalysis D AI Days after initiation E T Evapotranspiration F AWN Florida automated weather n etwork F BMPS Florida best management p ractices H AT Hours after t reatment MG T SN L 1 Milligrams of total soluble nitrogen per liter or parts per million N DVI Normalized difference vegetation index N Nitrogen O P Ortho Phosphate P CU Polymer coated u rea (60 day) R VI Ratio vegetative index S CU Sulfur coated u rea S PL Subplot location T KN Total Kjeldahl nitrogen T SN Total soluble n itrogen U F U rea formaldehyde U TC Untreated c ontrol X CU Agrium polymer sulfur coated u rea

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12 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requi rements for the Degree of Master of Science FATE OF APPLIED NITROGEN UNDER FORCED RUNOFF AND LEACHING FROM BERMUDAGRASS FAIRW AYS By Ryan S. Adams Au gust 2013 Chair: Name J. Bryan Unruh Cochair: Jason Kruse Major: Horticulture Sciences Numerous regulations and ordinances have recently been enacted to reduce nonpoint source pollution from turfgrass systems as a result of Nitrogen (N) runoff and leaching. A worst case scenario field study was conducted to determine the fate of applied N from bermudagrass fairways. { TC ABSTRACT } Each 48 kg N ha 1 fertilizer treatment was applied to a 7% slope at four separate interval distances (0.0, 0.9, 1.8, and 3.6 m) and was immediately followed by an irrigation event of 46 mm hr 1. The N leaching study was to determine N fate following a 144 kg N ha 1 application coupled with excess natural and simulated rai nfall. Forced runoff and leachate samples were collected systematically after treatment and analyzed for Total Soluble Nitrogen (TSN) (Antek 9000N Series analyzer). Runoff TSN loads were significantly affected by fertilizer source with the highest loads o ccurring from the soluble source ammonium sulfate (4.13 mg TSN L 1) > urea formaldehyde (1.04 mg TSN L 1) > polymer coated urea (0.06 mg TSN L 1) = control (0.02 mg TSN L 1). A 3.6 m unfertilized buffer for ureaformaldehyde reduced TSN loads by a quantity of 0.26 to 0.75 mg TSN L 1 in contrast to 1.8 m buffer. Results from the N leaching found inconsistent results in the

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13 first event, followed by TSN levels in the second and third below the analytical 1.

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14 CHAPTER 1 GENERAL INTRODUCTION Nonpoint source pollution from plant nutrients has th e potential to cause increased levels of algae or phytoplankton. Eutrophication is the process in which a water source becomes polluted with elevated levels of nitrogen (N) or phosphorus (P) (Rice and Horgan, 2010). Eutrophication and low oxygen levels hav e led to areas of the world being considered dead zones (Dodds, 2006). As algae and phytoplankton levels rise, the carbon dioxide and dissolved oxygen levels fluctuate resulting in rapid pH changes (NCDENR, 2013). Rapid pH changes have the potential to cre ate an environment containing insufficient dissolved oxygen through respiration and/or organism death and decomposition (NCDENR, 2013). A reduction in the amount of dissolved oxygen can produce a habitat unsuitable for certain fish species (Rice and Horgan 2010). In addition to the environmental concerns surrounding aquatic ecosystems, eutrophication can lead to contaminated drinking water. The current U.S. drinking water standard for nitrate nitrogen (NO 3 N) is 10 mg L 1 (USEPA, 1976). A growing environ mental concern in Florida and other states is nutrient leaching and runoff from established turfgrass sites. Previous research concluded that N leaching losses are dependent on the frequency of application and fertilization rate (Erickson et., 2010; Reike and Ellis, 1974; Petrovic, 1990; Barton et al., 2006; Soldat and Petrovic, 2008). In addition to the threat of leaching, Easton et al., (2005) determined nutrient transport in runoff is affected by intensity, duration, and total volume of rainfall/irrigat ion, soil moistu re content, soil texture, slope, and fertilizer application rate and source.

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15 Bermudagrass F ertilization and M aintenance season, sod forming perennial grasses which are able to produce high quality tur f and forage belong to the genus Cynodon (Taliaferro, 1995). Bermudagrass ( Cynodon dactylon [L.] Pers.) was first introduced to cross of Cynodon transvaalensis (2n=2x= 18) and Cynodon dactylon (2n=4x=36) called resiliency, resistance to diseases and weeds, and quick recovery capabilities (Burton, 1960). The generalized mean evapotra nspiration (ET) rate for Tifway ranges from 2.5 to 5 cm week 1 during the summer months (Cisar and Miller, 1999). Tifway is often labeled as the most extensively used improved cultivar in the warm climatic region (Beard, 1982) and is often used for golf co urse fairways. Bermudagrass fairways require N fertilization rates between 144 to 288 kg N ha 1 yr 1 (Sartain et al., 1999). Turfgrass demands for N are greater than any other nutrient (Beard, 1973). N is relied upon for several different functions which i nclude growth (Beard, 1973), composition of amino acids, protein synthesis (Brady and Weil, 2008), and its role as a component of chlorophyll, which aids in the conversion of light photons to chemical energy (Havlin et al., 2005). With the high frequency o f N fertilization, several N based fertilizer source s have been produced to reduce the number of application s needed by releasing N over time. These products range in source from slow/controlled release sources such as coated, stabilized, and methylated pr oducts. Maintaining sufficient levels of nutrients through fertilization practices can provide enhanced visual quality, recovery, regrowth, and vigor along with increased resistance to pests, diseases and unwanted weed species (Sartain et al., 1999; Bowm an et al.,

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16 200 2). Fertilizer needs and recommendations vary across the state of Florida depending on location, species, and desired maintenance level (Trenholm and Unruh, 2009). Day length has been determined to have a strong influence on turfgrass nutrien t uptake, with the largest nutrient quantities occurring during the stage of most active growth (Sartain, 2010). Plant growth rate which is positively correlated to temperature and moisture levels, how much N is available in the soil, N rate and fertilizer source applied, and differences in uptake rate by a specific turfgrass species are all factors that affect N uptake (Petrovic, 1990). Optimizing nutrient levels and N uptake capabilities reduces the consequences and concerns of nonpoint source pollution ( Petrovic, 1990). In addition to the threat of N, P nonpoint source pollution has been of concern for many years and is blamed for accelerated eutroph ication (Daniel et al., 1998). Like N, P also plays a significant role in energy transfer (Havlin et al., 2 005) and is a structural component of DNA and RNA (Brady and Weil, 2008). P availability for plant use is a function of the root growth, soil P concentration in solution, and the ability of the soil to replenish depleted P (Barber, 1995). With the potentia l to cause accelerated eutrophication, regulations have been developed to restrict P fertilizer applications across the country. Minnesota (Rosen and Horgan, 2005), Wisconsin (State of Wisconsin, 2009), and Westchester County, New York (County of Westchest er, 2009), have implemented P regulations in an effort to minimize environmental threats. The Florida Department of Environmental Protection (FDEP) in accordance with the United States Environmental Protection Agency (US EPA ) have set a numeric nutrient cr iterion to cover and monitor all significant waterways across the State of Florida (FDEP, 2012; USEPA, 2012 a ). In addition, the FDEP has taken another

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17 approach by designating Lake Okeechobee Basin, Everglades, Green Swamp and Apopka basin as P sensitive re gions (FDEP, 2007; 2008; Hodges et al., 2006). P sensitive designation means application of an organi c fertilizer source containing P must be determined by crop P requirements and not on N which is typical ly used for other regions of Florida (Mylavarapu, 2 011). The implementation of agricultural BMPs has prevented 2,429,440 kg of P from entering the Florida Everglades (FDEP, 2007). The numeric nutrient criterion, implementation of agricultural BMPs and the designation of P sensitive regions ensures imporved water quality to the 93% of Florida residents who use groundwater for drinking (FDEP, 2008); as well as creating a healthy habitat for wildlife and recreation (Mylavarapu, 2011). On county and local levels in the State of Florida, new ordinances and leg islation have been developed, which only allow P application when deficiencies have been confirmed by a soil or tissue analysis test performed by a State of Florida certified laboratory (FDEP, 2010; County of Pinellas, 2010). Furthermore, prior to 01 Janua ry 2014, all commercial fertilizer applicators must successfully complete training and continuing education requirements in the Florida friendly Best Management Practices for Protection of Water Resources by the Green Industries, offered by the FDEP throug h the University of Florida IFAS Florida friendly Landscapes program (FDEP, 2010). In addition, starting 01 January, 2014 all commercial applicators must carry their Florida Department of Agriculture and Consumer Services commercial fertilizer applicator c ertificate at all times when applying fertilizer (FDEP, 2010). Mitigating N onpoint S ource P ollution U nfertilized B uffer S trips Contamination of a water source that does not meet the definition criteria of point source in section 502(14) of the Clean Wat er Act is known as nonpoint source

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18 pollution ( US EPA 2012 b ). Nonpoint source pollution from golf courses via surface water runoff is a potential environmental threat because of the close proximity to bodies of water (Linde et. al., 1995). Hig her degrees of fairway slope, higher fertilizer use rates, and large fairway acreage present a greater threat to nonpoint source pollution than putting greens and tees drainage systems (Shuman, 2002). Fairway acreage equates to approximately 33% of a typic al golf course; which can create an increased risk because of the increased likelihood to border a body of water (Watson et al., 1992). These factors contribute to the negative public perception that golf courses potentially contaminate water bodies via nu trient surface runoff (Shuman, 2002). Dillaha et al., (1989) categorized buffer strips as riparian buffers, filter strips, grassed waterways, shelterbelts, windbreaks, living snow fences, contour grass strips, cross wind trap strips, shallow water areas t hat allow wildlife habitat, field borders, alley cropping, herbaceous wind barriers, and vegetative barriers. Vegetative buffer strips have been well studied and are a common occurrence to in agricultural settings (Dillaha et al., 1989). Vegetative buffer strips are designed to remove contaminates through filtration, deposition, adsorption, and infiltration (Dillaha et al., 1989). Previous research has shown that one of the best approaches to mitigate nutrient runoff is to use of vegetative buffer strips (B lanco Canqui et al., 2004; Krutz et al., 2003). Turfgrass has been used as a vegetative buffer because its dense nature can provide soil stability and reduce large amounts of sediment erosion (Gross et al., 1990). In addition, dense stands of turfgrass cr eate a more tortious pathway and encourage water infiltration (Easton et al., 2005; Moss et al., 2006). Proper management of

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19 turfgrass through fertilization, irrigation, mowing and aeration has been shown to promote healthy turfgrass (Walker and Branham, 1 992; Balogh and A nderson, 1992; Balogh and Walker, 1992; Turgeon, 2011 ; Witteveen and Bavier, 1999) A healthy turfgrass stand reduces nonpoint source pollution in contrast to bare soil or unhealthy turfgrass (Erickson et al., 2001). Turfgrass increased infiltration by more than 65% over a two year period in comparison to bare soil (Easton et al., 2005). Soil erosion was reduced when turfgrass was established over bare soils (Wauchope et al., 1990; Gross et al., 1990; 1991). Furthermore, the establishme nt of turfgrass increased the amount of irrigation/rainfall that was able to be applied before runoff initiated in comparison to bare soils. Krenitsky (1998) found bare soil consistently had higher runoff rates (1.21 1.52 mm min 1 ) in comparison to an area established with sod (0.21 0.76 mm min 1 ). In most research, data supports that N movement through and across the soil profile are positively correlated with rainfall/irrigation amounts and the initial soil moisture. Cole et al., (1997) observed that whe n the underlying soil of bermudagrass was relatively dry, runoff volumes were 4 to 16% of applied, however, when the same soil was moist, runoff volumes increased to 49 to 80%. Easton et al., (2005) found runoff volumes decreased as infiltration rates and shoot density increased. The unpredictable nature of rainfall has led to the utilization of rainfall simulators and irrigation when studying N movement. The use of artificial rainfall allows for increased efficiency and control. Ho wever, as Meyer & Harmon (1979) identified rainfall wide spread fie ld use. In a study comparing in ground irri gation and a rainfall simulator

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20 Bell & Koh (2011) detected that runoff from the irrigated plots averaged 23.6 mm h 1 ; while runoff from the rainfall simulator plots averaged 22.4 mm h 1 These differences in runoff rates between irrigation and simulation were not statistically significant. With the focus in Florida on implementati on of Best Management Practices (BMPs), there is a need to develop a better understanding of nonpoint source pollution via runoff from turfgrass systems. The N runoff study was created in response to some counties and municipalities developing their own lo cal ordinances to restrict fertilizer application within certain distances from a body of water. However, the optimal unfertilized width that will minimize movement of fertilizer sources and nutrients to nearby bodies of water has not been determined. N L e aching F ollowing H igh A pplication R ates Potential N los ses and nutrient contamination originate from surface runoff, leachate through the soil profile, volatilization, denitrification and clipping removal (Petrovic, 1990). Research suggests that numerous f actors such as fertilizer rate, fertilizer source, frequency, application technique, irrigation management, establishment period, and turfgrass species and cultivar are associated with N leaching losses (Barton, et al., 2006; Bowman et al., 2002; Cisar et al., 1991; Erickson et al., 2010; Geron et al., 1993; Reike and Ellis, 1974; Snyder et al., 1976, 1984, 1989; Petrovic, 1990). There are several methods used to study N leaching capabilities. Petrovic (1990) categorized these studies into drainage water, s oil sampling, sampling of soil water above the saturated zone, trapping NO 3 N on ion exchange resins and sampling shallow groundwater. Overall, research has consistently found that NO 3 N leaching in cool season turfgrass is greater with the use of solubl e N products in comparison to slow release

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21 products (Nelson et al., 1980; Mosdell and Schmidt, 1985; Sheard et al., 1985; Petrovic et al., 1986; Mancino and Troll, 1990; De Nobili et al., 1992; Geron et al., 1993; Engelsjord and Singh, 1997). Since polymer coated urea (PCU) products were first introduced, there have been several studies to examine their effectiveness at reducing N leaching losses (Guillard and Kopp, 2004; Petrovic, 2004; Wu et al., 2010). Guillard and Kopp (2004) found N leaching varied as much as 30 fold simply based upon fertilizer source s when applied at 147 kg N ha 1 yr 1 NO 3 N leaching losses were 16.8%, 1.7% and 0.6% of applied for am monium nitrate, PCU, and natural organic derived from turkey litter (Sustane ) respectively (Guillard and Kopp, 2004). A study conducted by Petrovic (2004) on a Kentucky bluegrass ( Poa P ra tensis L.) sports field showed N los ses were reduced from 29 47% to 0 12% of applied when PCU fertilizer were used compared to urea. Previous slow release N leaching r esearch has shown that the majority of N leached from ureaformaldehyde (UF), sulfur coated urea (SCU), activated s ewage 180 days after application (Rieke and Ellis, 1974; Nelson et al., 1980; Br own et al., 1982; Snyder et al., 1984; Morton et al., 1988; Mancino and Troll, 1990). NO 3 N losses in hybrid bermudagrass were greatest when fertilized with ammonium nitrate (AN) in comparison to less soluble sources > 12 12 12 > activated s ewage sludge (M > IBDU > UF (Brown et al., 1982). Guertal and Howe (2012) also determined leaching was significantly affected by fertilizer source with the greatest leaching occurring from the soluble source urea (6.8 mg NO N) > PCU (5.6 mg NO N) = stabiliz ed urea ( UMaxx ) (5.8 mg NO N) > control (3.0 mg NO N) when applied at a rate 73.0 kg N

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22 ha 1 A reduction was observed in NO 3 N leaching from 32% to 23% when fe rtilized with IBDU rather than u rea (Nelson et al., 1980). Greater nutrient leaching in sand y soils has been heavily correlated with increased irrigation and rainfall (Snyder et al., 1984; Morton et al., 1988; Petrovic, 2004; Erickson et al., 2005). For example, Snyder et al., (1984) found that daily irrigation losses ranged from 22 to 56%, while scheduling irrigation on soil moisture depletion reduced NO 3 N leaching to <1%. Over irrigation and the use of soluble fertilizer sources contributed more to NO 3 N leaching than the underlying soil composition (Brown et al., 1977; Snyder et al., 1984; Mor ton et al., 1988). Over irrigation and N fertilizer rates were found to be insignificant on total NO 3 N leached (McGroary et al., 2011). However, McGroary et al., (2011) observed the highest totals of NO 3 N leaching occurred under the highest N rate and m ost heavily irrigated plots. The nutrient leaching study was created to assess and evaluate nine N sources applied at an excess rate coupled with intense irrigation/rainfall events. Research has previously determined N leaching is of minimal risk when app lied at recommended rates (Erickson et al., 2008; Reike and Ellis, 1974; Sheard et al., 1985; Starr and DeRoo, 1981; Mancino and Troll, 1990; Miltner et al., 1996); however, the majority of these studies did not look at N fate when fertilizer recommendatio ns and irrigation rates were exceeded.

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23 CHAPTER 2 WIDTH OF TURFGRASS UNFERTILIZED BUFFER STRIPS AND THEIR IMMEDIATE INFLUENCE ON NITROGEN FERTILIZER MOVEMENT FOLLOWING EXCESS IRRIGATION Introduction Dillaha et al., (1989) categorized buffer strips as ripa rian buffers, filter strips, grassed waterways, shelterbelts, windbreaks, living snow fences, contour grass strips, cross wind trap strips, shallow water areas that allow wildlife habitat, field borders, alley cropping, herbaceous wind barriers, and vegeta tive barriers. Furthermore, vegetative buffer strips are recognized as one of the most widely accepted methods to mitigate runoff and pr event nutrient contamination (B lanco Canqui et al., 2004; Krutz et al., 2003). Vegetative buffer strips are designed to remove contaminates through filtration, deposition, adsorption, and infiltration (Dillaha et al., 1989). With proper maintenance, turfgrass has the ability to minimize environmental risks by performing as a vegetative buffer (Erikson et al., 2001). Dense t urfgrass creates a more tortious pathway that encourages water infiltration and reduces nutrient runoff (Easton et al., 2005; Moss et al., 2006). Turf sites need that turf contributes to no npoint source pollution (King et al. 2007). However, the npoint source pollution exists and adequate steps need to be taken to minimize risk (Pratt, 1985; Peacock et al., 1996; Smith and Bridges, 1996; Shuman, 2002; Kohler et al., 2004 ; Balogh and Walker, 1992) Nitrogen (N) applied to turfgrass can escape the turf/soil system via volatilization, denitrification, leaching, runoff, and clipping removal (Petrovic, 1990).

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24 With the focus in Florida on implementat ion of Best Management Practices (BMPs), there is a need to develop a better understanding of nonpoint source pollution via runoff from turfgrass systems. One attempt to reduce fertilizer loss from turfgrass systems is the Model Ordinance for Florida Frien dly Fertilizer Use on Urban Landscapes (Florida Department of Environmental Protection, 2009 b). The Model was designed to assess fertilizer application, landscape design, site preparedness, and irrigation. Within the ordinance, FDEP recommends a low mainte nance zone within 3.0 m of any potential water source. T his ordinance has been subjected to more stringent local and county ordinances and, as a result, some counties and municipalities have developed their own local ordinances to minimize urban fertilizer applications (Hartman et al., 2008; Hochmuth et al., 2011). Collier County, FL restricts fertilizer application within 3.0 m of water bodies or within 0.9 m when using a deflector shield or drop spreader (Collier County, 2011). Manatee County, FL recommen ds a 1.8 m low maintenance zone, with no fertilizer applied within 3.0 m of a body of water (Manatee County, 2011). However, the optimal unfertilized width that will minimize movement of fertilizers and nutrients to nearby bodies of water has not been dete rmined. Therefore, the objective of this study was to q uantify total soluble nitrogen (N) transport and to adjacent to a water body. Materials and M ethods Field tr ials were conducted at the University of Florida Plant Science Research and Education Unit (PSREU) in Citra, FL (2941 N, 8217 W). Thirty year average temperature and rainfall d ata have been compiled for Citra, FL (Figure 2 1). On 12 July hybrid bermudagrass ( Cynodon dactylon x C. transvaalensis Burtt Davey)

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25 was sprigged onto a research site constructed to simulate a golf course fairway. The study area is comprised of 85.0% Tavares sand (NRCS, 2009), mixed with soil from nearby lake to crea te a 7.0% laser graded sloped fairway. To better determine the soil composition, textural analysis samples were taken to a depth of 15.2 cm in November 2011 (Table 2 1). The soils were 78 91% sand, 1.7 6.6% clay, and 3.6 20% silt. The pH ranged from 5.7 an d 6.0 according to the University of Florida PSREU soil map (Figure 2 2). The fairway was segmented into fifty two individual plots running parallel to the slope (12.2 m by 1.4 m). Each plot was separated by an L shaped aluminum flashing material that ra n the length of the plot. Flashing was buried to a depth of approximately 5.1 cm, leaving 2.5 cm above the turf to discourage runoff water from moving into adjacent plots. A V shaped aluminum collection weir was situated at the downhill end of each runoff plot. Runoff water that accumulated at the collection weir was directed through approximately 61.0 cm of 5.1 cm PVC drain pipe into a 114.0 L plastic barrel (Figure 2 3). Between 0 1 Dec 2009 and 31 Jan 2010 collection containers were installed by boring a nd removing soil with a 90.0 cm diameter auger. A 20.3 cm layer of gravel was placed in the bottom of each bored hole followed by a 61.0 cm long piece of 10.2 cm perforated pipe leading to a 10.2 cm header pipe. 114 L plastic barrels were placed over the u nderlying gravel and piping followed by backfilling with native soil. Three downslope drainage lines were later added to the headers to prevent collection containers from floating. A French drain was installed along the uphill end of study site and perpend icular to the plots to reduce upslope runoff from entering the plots. During

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26 simulated runoff events holes were dug to help infiltration in areas near irrigation heads where excess water was known to aggregate. Each plot was mowed biweekly at a height of 12.7 mm using a Toro Greensmaster 1000 walking mower (The Toro Co., Bloomington, MN). Due to the inability to mow closely to the flashing and weir, each triangular weir was mowed with a Redmax Reciprocator (Redmax Zenoah America Inc., Lawrenceville, GA) t o approximately 12.7 mm before each experimental run. Following mowing, a backpack blower was used to remove any grass clippings. The height of cut along the flashing edge was slightly higher to provide a more tortious pathway that would minimize water mov ement down the flashing. The turfgrass near the flashing edges was maintained at a height of approximately 19.0 mm using a string trimmer. This higher height of cut was preserved 7.6 cm inward from the aluminum flashing that ran the length of each plot. Tw elve Toro 835 (The Toro Co., Bloomington, MN) irrigation heads supplied the irrigation for each simulat ed rainfall event and to produce supplemental i rrigation. A row of six heads ra n parallel across the top of the sloped fairway and six heads ra n parallel across the bottom of the sloped fairway below the collection containers. All irrigation heads were leveled and set to 180 for pre wetting and runoff events. Each irrigation head was installed with nozzle set #34, which supplied 35 gpm In between runoff events and during fallow periods, irrigation heads were returned to 360 and watered to meet evapotranspiration (ET) rates. Three N containing fertilizers were evaluated: 1.) ammonium sulfate (AS); 2.) polymer coated urea (PCU); and 3.) ureaformaldehyde ( UF). Each N source was applied at a rate of 48.0 kg N ha 1 to plots situated upslope from the collection weirs.

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27 Four different upslope distances were tested; 0, 0.9, 1.8, and 3.6 m and each fertilized plot measured 1.4 m by 2.7 m. Four replications of eac h combination of N source and distance were conducted along with four untreated plots for comparison purposes. Experimental treatments were arranged as a 3 X 4 factorial in a randomized complete block design wit h the factors being N source, upslope distanc e and an untreated control. To manage the area above the fertilized swath a 91.0 cm drop spreader was used to apply 24.0 kg N ha 1 of AS six times during the summer of 2012. The fertilization started on 27 May 2012 and was subsequently applied on 10 Jun e, 4 July, 23 July, 7 August and 24 August 2012. The area outside of the drop spreader width (each 22.9 cm plot edge separately) was fertilized on the same dates by predetermined weighing and hand fertilization. The plots were lightly watered to prevent fe rtilization volatilization loss, turfgrass burn and downslope movement. The area downslope from each 2.7 m fertilized swath was left unfertilized throughout the duration of the study period. On 23 February 2012, Oxadiazon ( Bayer Crop Science Corp. Shawnee Mission, KS) impregnated on a 5 0 15 carrier was applied at a rate of 48.0 kg N ha 1 to the entire study area. Three Bayer Crop Science Corp ., Shawnee Mis sion, KS) applications were applied on 13 March 2012 13 June 2012, and 12 July 20 12 to help manage doveweed ( Murdannia nudiflora Brenan). Prior to each simulated rainfall event and fertilizer application, the entire site was pre wet to the point of saturation T wo irrigation events of approximately 76.2 mm were applied 48h prior to fe rtilizer application followed by a third application of 95.3 mm 24h

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28 prior. The day prior to each runoff event, flashing integrity was confirmed and collection barrels were emptied and cleaned using a submersible pump and wet/dry vacuum. Following fertiliz er application, b ut prior to rainfall simulation, % soil moisture readings were taken using a Field Scout TDR 300 (Spectrum Technologies Inc., Plainfield, IL). Three 7.6 cm depth s oil moisture readings were taken 0.0, 1.5, 4.6, 7.6, and 10.7 m from the col lection weir Soil moisture readings at the same location were also taken immediately following rainfall simulation. During each runoff event, four catch cans were placed in each plot at 1.5, 4.6, 7.6, and 10.7 m upslope from the runoff weir to c atch irrig ation water and to allow the determination of irrigation system uniformity. After the simulated rainfall event concluded, each catch can was emptied i nto a graduated cylinder and volumes were recorded. Catch can totals were extrapolated across the runoff g radient as a determination of total irrigation applied to each plot. Irrigation unifor mity based upon oefficient of Uniformity (CU) (Christiansen, 1942) and Distribution Uniformity (DU) (Merriam and Keller, 1978) were dete rmined to be 83.2/ 72.5; 87.3/79.2; 85.6/79.5 for the first, second and third runs, respectively. Three simulated runoff events using the in ground irrigation system were generated during 2012: 11 May, 29 June, and 15 August. Runoff was encouraged by irrigation events provid ing 44.7, 46.2, and 47.2 mm h 1 for the first, second and third runs, respectively. Once runoff ceased approximately 10 15 min after initiation, runoff samples were collected. Contents of each collection barrel were stirred and a 20 ml water sample was col lected and placed into a 20 ml scintillation vial. Duplicates were taken every eight samples to check for accuracy.

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29 Water samples were analyzed for total soluble nitrogen (TSN) using an Antek 9000NS Series analyzer (Antek Instruments, Inc., Houston, TX). Samples were also analyzed for Ortho Phosphate (OP) using a Seal AQ2 method discrete auto analyzer (Seal Analytical Inc., Mequon, WI). The Antek 9000N instrument allows for TSN calibration standards to be analyzed, which produce internal calibration curves The standard curve before each test required an R 2 value of 0.995 and each four injection calibrant was examined for outliers using a 5.0% relative standard deviation (RSD). Once the calibration curves of the known standards were determined to be suffic ient, raw unknown N contents were analyzed and compared to the known calibration curve concentrations. Each sample was initially tested on a 1 10 mg TSN L 1 calibration curve with four injections per sample. Samples with less than 1 mg TSN L 1 concentratio n were under the method detection limit (MDL) and considered to have undetectable levels. Samples greater than 10 mg TSN L 1 were reanalyzed on a 10 100 mg TSN L 1 calibration curve with the same set requirements. Samples with a RSD >5.0% were reanalyzed u ntil an accepted standard deviation was achieved. All samples were analyzed within 72h after runoff initiation. The AQ2 OP method uses internal calibration curves based upon absorbance measured photometrically at 880 nm with a MDL of 0.002 mg P L 1 Quali ty control solutions such as duplicates and spikes were used every 15 samples. If duplicates were not within a 5.0% RSD, all samples processed since the last spike/duplicate combination were reanalyzed automatically to ensure accuracy. OP samples were anal yzed within 48h of collection during the second and third runoff events. Samples from the first event were frozen and analyzed within 3 months of sampling.

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30 Weight flow analysis was conducted after concentration samples were taken by pumping collection tank s into a 208.2 L water barrel suspended from a model DI 100 U RAS1 Restrictive Load Cell (Loadstar Sensors, Inc., Fremont, CA) mounted to a tripod. Runoff water from each plot was weighed individually. Runoff water was inspected for fertilizer prills wh en samples were collected. Photos of each unfertilized buffer strip were collected weekly using a Sony Cybershot camera, model DSC H10 (Sony Corp., New York, NY). Camera set tings were; ISO100, 1/40 second shutter speed, and F3 aperture. All images were colle cted with the use of a portable 53 x 61 x 51 cm light box fitted with four ten watt compact florescent, 6500 kelvin daylight bulbs. Digital images were taken at 56.0 cm increments down the entire u nfertilized buffer strip to detect downslope fertilizer mov ement following rainfall simulation (Figure 2 4) The number of distances was dependent on the unfertilized buffer strip size; with the possibility of 1, 2, 4, or 8 distances for 0.0, 0.9, 1.8, and 3.6 m, re spectively. Each distance refered to the distance downslope from the fertilized swath with 1 = the 56.0 cm increment adjacent to the fertilized swa th and 2 = the 56 to 112 cm area downslope of fertilized swath. For example a 1.8 m buffer treatment would have four distances, with distance 1 being adjacent to the fertilized swath, while distance 4 would be the unfertilized buffer strip section next to collection weir. Distance 0 refers to the fertilized swath and distance 1 is the UTC. Unfertilized buffer strip images were analyzed for dark green color in dex (DGCI) with the use of digital image analysis software (SigmaScan, v. 5.0, SPSS, Inc., Chicago, image was taken of the fertilized swath.

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31 Normalized Diff erence Vegetation Index ( NDVI) and Ratio Vegetative Index (RVI) were taken using a Crop Circle Model ACS 210 (Holland Scientific Inc., Lincoln, NE). A Geo Scout GIS 400 (Holland Scientific., Lincoln, NE) was used to log the NDVI/RVI data. While taking data, the instrument was held approximately 91.4 cm above the turf surface and each subplot was recorded separately. The subplots were defined as the area above the fertilized swath, the fertilized swath, and unfertilized buffer strip. Clippings were collected weekly for one month fo llowing runoff events. Clippings we re only collected from a single mower pass through the fertilized strip. Clipping samples were immediately placed into a drying oven set at 70C for a minimum of 72 hours. Once weighed, clipping were proportioned (25% of each sample) and combined (5 collections) based upon plot designation, during a given run. Clippings were ground to 1 mm using a Cyclone Sample Mill (UDY Corp., Fort Collins, CO) in preparation for total Kjeldahl nitrogen (TKN) tissue analysis at UF/IFAS A nalytical Services Laboratories in Gainesville, FL. Color, Quality and Density v isual ratings were taken based upon the NTEP rating scale which ranges from 1 9 with a qu ality rating of 9 being optimal and 1 being dead turf, color rating of 9 being a dark green turf and 1 light pale green color, and density rating of 9 being maximum density (Shearman and Morris, 200x) Ratings in this study > 6 were considered acceptable. All ratings were reported in whole numbers. Results The main objectives of the sta tistical analysis were to identify the most effective combination between unfertilized buffer strip size and fertilizer source to minimize TS N runoff loads from turfgrass systems and to maximize turfgrass quality surrounding environmentally sensitive areas To carr y out such an analysis, data were pooled over

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32 all three runs and analyzed with SAS/GLI MMIX using a linear mixed model (SAS, 2008) A heterogeneous fitted model was used because variability was not constant across TSN loads by sources. Th e variabil ity of the response was heterogeneous across two groups; Group 1 (Soluble N source) contained AS, while Group 2 was comp osed of UF, PCU (Insoluble N source ) and the UTC When separated by grouping, va riability became more constant and the resulting heterog eneous parameter estimates are listed in Table 2 2 A fitted linear mixed effects model using SAS/GLIMMIX determined a n event by treatment ( fertilizer source by upslope p lacement) interaction (Table 2 3 ). Treatments fertilized with AS had the highest TSN loads across all runoff events ( Figure 2 5 ). PCU was able to reduce TSN loads in runoff waters to 0 .02 g or 0.41% of the applied N. UF fell in betwee n the two other fertilizer sources at 1.048 g (Table 2 4). Tukey estima tes using a 0.05 nominal le vel showed no differences between PCU and the UTC and upslope placement across AS and PCU. Tukey also indicated 95% confidence that the average TSN runoff under UF treatments was 0.86 to 1.11 mg L 1 greater than PCU (Table 2 5). TSN s ignificance occurred when UF was applied from a 3.6 m buffer strip (Figure 2 6 ), which reduc ed N losses to 3.9% of applied N while all other distances were comparable and ranged from 6.9% 7.7% of applied N A 3.6 m buffer provided 45% less N in compar ison to downslope placement closer to the water body. Using Tukey confidence that average AS treatments was 1.90 to 4.27 mg TSN L 1 grea ter than UF and 2.89 to 5.26 mg TSN L 1 greater than PCU (Table 2 6).

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33 Total Kje ldahl Nitrogen and B iomass for Turfgrass C lippings A linear mixed effects model for Total Kjeldahl Nitrogen (TKN) concluded significant interaction between treatment and runoff event (Table 2 7 ). PCU in the August event had the highest TKN levels across al l fertilizer sources (Table 2 8 ). The UTC in the August and June events had the lowest TKN levels in comparison to all other August and June treatments; however UTC TKN levels in August and June runoff events were still higher than any treatment in the May event. Results of statistical tests determined the May event had the lowest TKN and no differences between treatments (Table 2 9). A linear mixed effects model for clipping biomass weights concluded significant in teraction between treatment and Days After Initiation (DAI) (Table 2 10 ). With the exception of the PCU applied at 0.0, 1.8, and 3.6 m at 1 DAI (Table 2 11) all DAI treatments were not significantly different than the UTC. A difference in clippings at 7 and 14 DAI suggests AS and PCU had higher b iomass weights than the UTC. There is no evidence to suggest UF treatments yielded more biomass than the UTC at 1, 7, 14, and 28 DAI. At 21 DAI, all treatments had higher biomass weights than the UTC. Soil M oisture A linear mixed effects model for soil mo isture concluded a significant interaction between treatment and runoff event by time (Table 2 12 ). Soil Moisture B efore ( SM B) application was highly correlated with Soil Moisture A fter ( SM A) runoff events. For all three runoff events soil moisture followi ng runoff events was highest while the SM B was lower. The soil moisture before and after simulations was highest during the August event. SMA application from the May and June events were in the lowest statistical SMB was statistica lly higher than May (Figure 2 7 ).

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34 Soil moisture analysis found no evidence AS treatments were significantly different at 0.05 nominal levels (Table 2 13 ). Tests of statistical analysis determined UF with a 1.8 unfertilized buffer had higher VWC% than the 3.6 m buffer treatment. The offset zero and 0.9 m treatments were not statistically different than the 1.8 or 3.6 m UF was the wettest treatment among the fertilizer sou rce PCU. The 3.6 m PCU treatment was in the second statistical grouping and was greater than the offset zero at a 0.05 nominal level. No evidence suggested that soil moisture was different across PCU 0.0, 0.9, and 3.6 m treatments. Total Ortho P hosphate Loading in R unoff The main objectives of the Ortho Phosphate (OP) statistical analysis were to identify the potential OP losses following N fertilization. Total OP loads were determined to be of environmental significance ( > 10 g OP L 1 ). Data were poo led over all three runoff events and analyzed using SAS/GLIMMIX across N fertilizer sources using a linear mixed model. Analysis of OP was similar to TSN, but the variability of the response was homogenous across all fertilizer sources and no grouping was used. Across all three runoff events of the study, the driving factor to reduce OP loads was based upon runoff event by N treatment (Table 2 3). AS treatments had the highest OP loads in runoff occurring in June (Figure 2 8). The May and August events had less OP loads in runoff water following AS fertilization. The lowest statistical OP loads for UF and PCU were observed in the May event. These were the only two fertilizer sources by runoff event interactions that reduced loads under the 10 g OP L 1 thres hold. Higher loads were recorded in June and August for both UF and PCU.

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35 The June event produced the highest OP loads and significantly higher than the May event (Figure 2 9). August fell between the other runoff events and differences in Total OP loads w ere observed from both runoff events. Using Tukey estimates, the average OP loads under AS treatments were greater than UF, PCU and the UTC at the nominal 0.05 level (Table 2 14). Least square means estimates also indicated there was a 95% confidence level that the average OP loads under UF fertilization from 0.9 m was 0.76 to 13.12 g OP L 1 greater than UF applied 3.6 m above the collection weir. RVI and NDVI R eflectance Turfgrass r eflectance measurements were taken to compare the relati ve strengths and uses between RVI and NDVI reflectance as a plant stress indicator. Results of statistical tests for RVI indicated a significant interaction between runoff event and sub plot location (SPL) and SPL and DAI (Table 2 15 ). The fitted linear mix ed effects model provided no evidence to suggest differe nces in SPL at 1 DAI (Table 2 16 ) RVI values for f ertilized AS subplots were greater than unfertilized PCU and UF subplots at 7 and 14 DAI. PCU subplots were in a higher statistical grouping than all unfertilized subplots at 28 DAI and UTC subplots exhibited the least RVI reflectance at 7, 14, 21, and 28 DAI. Statistical tests concluded a SPL by runoff event interaction for RVI and NDVI. In May, NDVI measured from AS fertilized subplots w as in a high er statistical grouping than the UTC. According to RVI (Table 2 17) and NDVI (Table 2 18), AS subplots fertilized in June had greater values than the unfertilized PCU, UF, and UTC subplots. Statistical tests from the August runoff event also determined UF s NDVI was statistically greater than the UTC. The fitted linear mixed effects model for NDVI

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36 provided no evidence for a SPL by DAI inter action and was analyzed by DAI Tukey 0 .05 nominal levels found 7, 14, and 21 DAI had the high est NDVI values (Figure 2 10 ). The second categorical grouping contain ed 28 DAI, followed by the lowest NDVI reflectance being the first day following runoff events (1DAI) Visual A ssessments Change s in visual parameters as a result of fertilization a ppli cation and runoff events were fitted into a linear mixed effects model which determined runoff event by SPL interaction s for color, quality, and density (Table 2 15 ). Visual color of AS fertilize d turf in May was statistically greater than unfertilized sub plots, UTC, and th e area managed above the fertilized swath (Table 2 19 ). Visual color in June and August had higher ratings for fertilized swaths than all unfertilized buffer strips and UTC plots, as well as, PCU fertilized swaths had better color of gree n than the area above the fertilized swath. During June and August turf color of all fertilized subplots was above the minimum acceptable color rating. Visual quality of fertilized subplots locations was better than the UT C in June and August (Table 2 20 ) The August runoff event provided no evidence to suggest differences between the management above and fertilized subplots existed Throughout the August runoff event, fertilized subplot quality and density were above the minimum acceptable rating. Ratings of visual density indicated AS and PCU fertilized subplots were more dense than the UTC in June (Table 2 21 ). During t he August runoff event, subplots fertilized with AS had increased density in comparison to the UF unfertilized buffer strip AS and PCU c onsistently produced higher density ratings than the UTC through out all three runoff events.

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37 V isual color ratings were different between SPL by DAI (Table 2 22 ). S ubplots fertilized with PCU and AS had a higher visual color rating then unfertilized subpl ots 7 and 21 DAI. At 14 DAI, AS treatments had higher visual quality ratings than the unfertilized buffer strips. Color ratings at 1 and 28 DAI showed fertilized PCU subplots performed better than unfertilized buffer subplots regardless of fertilizer sourc e Visual quality and density ratings were analyzed using a fitted linear mixed model, which indicated differences between DAI. Analysis of visual quality ratings showed that 1, 14, and 21 DAI had the best overall visual quality (Figure 2 11). Visual q uality ratings taken at 7 and 28 DAI were lower Analysis of visual density rati ngs suggested that turf at 7 and 14 DAI had the greatest density. Density at 21 DAI was in the second statistical grouping, while 1 and 28 DAI had the lowest t urf density ratin gs. Dark Green Color Index I magery Dark Green Color Index (DGCI) imagery data were pooled over all three runoff events and analyzed using SAS/GLIMMIX with a l inear mixed model Statistical tests using a fitted linear mixed model determined an event by dist ance and a distance by treatment interaction (Table 2 23). Analysis of DGCI distance by treatment using the fitted linear mixed model found no differences at distances 0,2,3,5,6,7,8 when separated by distance (Table 2 24) At distance 1, AS and UF treatmen ts applied with no buffer had a higher DGCI than PCU applied at 1.8 and 3.6 m. Distance 4 determined DGCI than UF and PCU 3.6 m as well as PCU applied at 1.8m. When the linear mixed model was separated b y treatment, all fertilized DGCI distances had a significantly higher DGCI than unfertilized buffer strips, with the exception of the 0.0 m AS treatment (Table 2 25). AS applied from a 1.8 m unfertilized buffer strip was the only treatment that saw unferti lized buffer strip

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38 distance differences at 0. 05 nominal levels. Distance 4 had a statistically greater DGCI in co mparison to all other distances. The untreated had the lightest green color throughout the study. The fitted linear model for DGCI also found an interaction between runoff events by distance. The fertilized swath and the distance furthest away from the fertilzed swath had the highest DGCI in May (Table 2 26 ). Distances 1, 5, 6 were found to have greater DGCI values than other distances. In June the fertilized swath had the highest DGCI There was no evidence to suggest differences between other distances in June. Distances 1, 0, 4, 7, and 8 were in the highest grouping in August; however distances 1, 7, 4 were not statistically different than t he rest of the DGCI distances. Discussion In this worst case scenario, PCU minimized TSN runoff levels i n comparison to AS and UF PCU also had the highest TKN values in August across all events by treatments. Although not statically different, TKN from t he May runoff event showed that PCU was higher than any other fertilizer source. Petrovic (1990) determined that optimizing nutrient levels and N uptake capabilities reduces nonpoint source pollution, increased TKN levels and lower levels of TSN in the runoff water. An increase in TKN levels was seen across all fertilizer sources as day length and the period most conducive to growth increased over the summer months. The only exception to this was the PCU treatment in June which had a higher TKN value then the other treatments in the June runoff event This was potentially skewed by the possibility that a fertilizer prill ended up in the TKN analysis. Numerous prills were observed in the

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39 clippings biomass from collections 1 and 7 DAI, but were separated out as best as possible prior to tissue grinding and TKN analysis. PCU produced high visual ratings, consistently above the minimum level of acceptability from June on (with a few exceptions of values just below the minimal accept able threshold). PCU color ratings also increased 7 DAI. The lower color ratings prior to 7 DAI may have been caused by excess irrigation applied for the runoff event or All turfgrass plots began the season at or belo w minimal acceptable, however as the season progressed there was a steady increase in color, quality, den sity, NDVI, and RVI values, with the highest values occurring following the August runoff event. This may have been due to the minimal fertilization th e plots had received in the years leading up to the study. Also the possibility of the excess irrigation above evapotranspiration rates applied b etwe en 12 May 2012 and 3 June 2012 and the increased growth r ates during the summer months could have influence d the turf. Differences among subplots were supported by NDVI/RVI data taken across all three runoff events. NDVI/RVI is a measurement value of reflectance sensory that has been show in bermudagrass to be closely correlated with turf quality, N fertilizat ion, and irrigation (Xiong et al., 2007). NDVI/RVI values seemed with relate with differences in fertility (fertilized vs. unfertilized subplots), however differences were not observed across N sources. There was only one significant difference among TSN loads based upon ups lope placement in this study A reduction in TSN and OP loads was observed when UF was applied from a 3.6m buffer in contrast to shorter buffer strips (1.8, 0.9, 0.0 m). The rest

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40 of the fertilizer sources produced no significant differe nces in upslope placement, which indicates that buffer strip sizes were too narrow in range to reduce AS TSN loads, and regardless of placement minimal to no TSN came from PCU treatments.

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41 Figure 2 1 Compiled Thirty Year Weather Data for the Citra, FL region: NOAA National Climatic Data Center

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42 Figure 2 2 Plant Science Research and Education Unit (PSREU) Soil pH Map. Photo courtesy of the Inst. of Food and Agric. Sci., Univ. of Florida, Gainesville. Area of intere st is located in the northern part of field six. Figure 2 3 A V shaped aluminum collection weir was s ituated at the downslope end of each runoff plot. Runoff water that accumulated at the collection weir was directed through approximately 61.0 cm of 5.1 cm PVC drain pipe into a 114.0 L plastic barrel. Sleeves and buckets were removed during runoff events. Photo courtesy of Ryan Adams.

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43 Figure 2 4 The number of images for dark green color index values was dependent on the unfertilized buffer str ip size ; with a possibility of 1, 3 5 or 9 distances for 0.0, 0.9, 1.8, and 3.6 m, respectively. Each distance refers to the distance away from the fe rtilized swath with 1 = the 56 cm increment adjacent to the fertilized swath, 2 = the 56 to 112 cm area downslope of fertilized swath For example in this image, a 1.8 m buffer treatment would have f ive distances, with distance 1 being adjacent to the fertilized swath, while distance 4 would be the unfertilized buffer strip section next to collection weir. D istance 0 refers to the fertilized swath Photo courtesy of Ryan Adams.

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44 Figure 2 5 Total soluble n itrogen (TSN) loads determined with nitrogen source application of ammonium sulfate (AS), ureaformaldehyde (UF), and p olymer coated u rea (PCU) by runoff event: May, June and August Means w ith the same letter in a given source were not significantly different (P = 0.05) according to

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45 Figure 2 6 Infl uence of unfertilized buffer strip size on total soluble n itrogen (TSN) loads below an ureaformaldehyde fertilized swath Lines represent 95% confidence limits and overall means using Proc Glimmix for each unfertilized buffer strip size.

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46 Figure 2 7 Soil moisture c ontent percentage (SM C%) across runoff events sorted by time of collection. In each runoff event soil moisture was taken before and after runoff initiation. Means with the same letter in a given collection time means separation.

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47 Figure 2 8 Total ortho phosphate (O P) ru noff loads as influenced by application of a m monium sulfate (AS), ureaformaldehy de (UF), and polymer coated u rea (PCU) separated by runoff event: May, June, August Means with the same letter in a given source were not significantly different (P = 0.05)

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48 Figure 2 9 Total ortho phosphate (OP) loads by runoff event: May, June, August Means with the same letter were not significantly different (P = 0.05)

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49 Figure 2 10 Three event a verage normalized difference vegetation index (NDVI) values across separation. B ars at each DAI represent 95% confidence intervals. Normalized difference vegetation index (NDVI) value was calculated using: NDVI = (R NIR R red )/(R NIR + R red ).

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50 Figure 2 11 Three event a verage of visual quality and density ratings by days after LS means separation (P = 0.05). Bars at each DAI represent 95% confidence intervals. Scale is from 1 to 9, 9=optimal turf quality/density, 6=acceptable turf quality/density.

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51 Table 2 1 Runoff study area textural a nalysis data from Nov. 2011 to d epth of 15.2 mm Sample #§ %Sand % Clay %Silt Class 1 90.81 5.60 3.60 Sand 2 86.54 2.96 10.50 Loamy Sand 3 81.05 6.60 12.34 Loamy Sand 4 87.60 1.68 10.72 Loamy Sand 4 85.94 3.12 10.94 Loamy Sand 5 83.89 3.68 12.43 Loamy Sand 6 85.46 2.88 11.66 Loamy Sand 7 84.00 3.52 12 .48 Loamy Sand 8 87.25 2.32 10.44 Sand 9 77.87 2.16 19.98 Loamy Sand 10 84.72 2.96 12.32 Loamy Sand 11 87.49 2.72 9.79 Sand 12 89.08 2.32 8.60 Sand 13 87.60 2.48 9.92 Sand 14 87.80 2.88 9.32 Sand 15 88.53 2.64 8.83 Sand 16 87.55 2.64 9 .81 Sand 17 86.50 2.64 10.86 Loamy Sand C for 183 min with a pipette depth of 100 mm. § Samples were taken from random plots moving west to east across study site Table 2 2 Grouping co variance estimates for total soluble nitrogen analysis Covariance Parameters Subject Parameter Estimate Standard Error Soluble Treatment*Rep Variance 0.819 0.215 Soluble Treatment*Rep 0.459 0.323 Insol uble Treatment*Rep Variance 0.015 0.003 Insoluble Treatment*Rep CS 0.017 0.006 Insol uble; polymer coated urea (PCU), ureaf ormaldehyde (UF), and the untreated c ontrol (UTC). Compound symmetry (CS )

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52 Table 2 3 Analysis of variance for total soluble nitrogen and ortho phosphate Runoff ANOVA TSN OP Effect Df pr > F pr > F Treatment 12 <0.001 0.045 2 0.005 0.001 Event*Treatment 24 0.011 0.0 19 ces; ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated urea (PCU) by unfertilized buffer strip sizes (0.0, 0.9, 1.8, and 3.6m) and an untreated control. Event consists of the May, June, and August runoff events. Table 2 4 Total soluble nitrogen loads by fertilizer source averaged across three runs Total Soluble Nitrogen Loads Source TSN Loads g Ammonium Sulfate 4.069 a Urea Formaldehyde 1.048 b Polymer Coated Urea 0.064 c Untreated Control 0.020 c Means with the same letters were not significantly different (P = 0.05) according to Tukey Kram three runoff events

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53 Table 2 5 Tukey means estimates for ureaformaldehyde total soluble nitrogen for buffer strip sizes Effect Buffer Esti mate Standard Error DF t Value alpha Lower Upper m 0.0 vs 0.9 0.01 0.12 27 1.19 0.243 0.05 0.39 0.10 0.0 vs 1.8 0.07 0.12 27 0.61 0.545 0.05 0.17 0.32 0.0 vs 3.6 0.58 0.12 27 4.82 <0.001 0.05 0.33 0.82 0.9 vs 1 .8 0.22 0.12 27 1.81 0.082 0.05 0.03 0.46 0.9 vs 3.6 0.72 0.12 27 6.01 <0.001 0.05 0.47 0.96 1.8 vs 3.6 0.50 0.12 27 4.21 0.003 0.05 0.26 0.75 Adjusted Pr > |t|, lower, and upper limits were equal to normalized and removed. Table 2 6 Tukey means estimates for fertilizer sources Effect Source Estimate Standard Error DF t Value alpha Lower Upper AS vs UF 3.09 0.55 27 5.66 0.001 0.05 1.90 4.27 AS vs PCU 4.07 0.55 27 7.47 <0.001 0.05 2.89 5.26 UF vs PCU 0.98 0.06 27 16.48 <0.001 0.05 0.86 1.11 AS vs UTC 4.12 0.55 27 7.48 <0.001 0.05 2.92 5.31 UF vs UTC 1.03 0.09 27 10.89 <0.001 0.05 0.83 1.22 PCU vs UTC 0.04 0.09 27 0.47 0.644 0.05 0.15 0.24 averaged across three runoff events. Adjusted Pr > |t |, lower, and upper limits were equal to normalized and removed.

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54 Table 2 7 Analysis of variance for total Kjeldahl n itrogen clippings Total Kjeldahl Nitrogen ANOVA Effect Df pr > F Treatment 12 <0.001 Event 2 <0.001 Treatment* Event 24 <0.001 Treatment refer s to sources; ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) by unfertilized buffer strip sizes (0.0, 0.9, 1.8, and 3.6m). Event consists of the May, June, and August runoff events. Table 2 8 Total Kjeldahl nitrogen clippings tissue analysis for fertilizer treatment by buffer strip size averaged across runoff events Buffer Total Kjeldahl Nitrogen m % N May June August AS 0 .0 1.7 2.7 2.7 ab AS 0.9 1.7 2.6 ab 2.8 ab AS 1.8 1.7 2.6 ab 2.9 a AS 3.6 1.8 2.6 ab 2.7 ab UF 0 .0 1.5 2.4 ab 2.8 ab UF 0.9 1.6 2.6 ab 2.8 ab UF 1.8 1.6 2.4 ab 2.8 ab UF 3.6 1.5 2.5 ab 2.8 ab PCU 0 .0 1.5 2.7 ab 3.2 a PCU 0.9 1.6 2.8 a 3.1 a PCU 1.8 1.5 2.7 ab 3.1 a PCU 3.6 1.3 2.5 ab 3.1 a UTC 1.5 2.2 b 2.2 b Nitrogen sources (F) used were ammonium sulfate (AS), ureaformaldehyde (UF), polymer coated urea (PCU), and an untreated control (UTC). Means with the same letter in a given event were not significantly different (P = 0 .05)

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55 Table 2 9 Total Kjeldahl nitrogen tissue clippings analysis by runoff event Total Kjeldahl Nitrogen Loads Event TKN % N May 1.6 a June 2.6 b August 2.9 c Means with the same letters were n ot significantly different (P = 0.05) according to for three runoff events Table 2 10 Analysis of variance for clipping biomass Clipping Biomass ANOVA Effect df pr > F 12 0.154 4 <0.001 DAI*Treatm ent 48 <0.001 Treatment refer s to sources; ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) by unfertilized buffer strip sizes (0.0, 0.9, 1.8, and 3.6m). Days after i nitiation (DAI) refer to collection days 1, 7, 14, 21 and 28 following three runoff events.

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56 Table 2 11 Differences in clipping biomass c olle ction for days after i nitiation across fertilizer source by buffer strip size F Buffer Days After Initiation m g of clippings 1 7 14 21 28 AS 0 .0 2.10 j o 3 .98 abc 4.31 a 3.93 a d 3.50 a g AS 0.9 2.07 k o 3.57 a g 3.86 a f 3.79 a g 3.51 a g AS 1.8 1.96 mno 3.53 a g 3.58 a g 3.75 a g 3.25 a l AS 3.6 1.98 mno 3.58 a g 3.58 a g 3.59 a g 3.15 a m UF 0 .0 2.15 i o 3.51 a g 3.80 a g 3.74 a g 3.20 a m UF 0.9 2.07 k o 2.68 d o 2.72 c n 3.17 a m 3.03 b n UF 1.8 2.19 h o 3.19 a m 2.65 e o 3.37 a j 3.27 a l UF 3.6 2.02 l o 2.76 b n 2.62 f o 3.20 a m 2.85 b n PCU 0 .0 2.72 b n 3.41 a i 3.67 a g 3.96 abc 3.68 a g PCU 0.9 2 .55 g o 3.26 a l 3.38 a j 3.90 a e 3.53 a g PCU 1.8 2.88 b n 3.46 a h 3.3 0 a k 3.94 a d 3.77 a g PCU 3.6 3.04 b n 3.51 a g 3.62 a g 3.99 ab 3.77 a g UTC 1.29 o 1.8 0 mno 1.73 no 1.66 no 1.72 no Means with the same letter were not s ignificantly different (P = 0.05) according to Nitrogen sources used were ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) and an untreated c ontrol (UTC). Table 2 12 Analysis of variance for soil moisture Soil Moisture ANOVA Effect Df pr > F Time 1 <0.001 Event § 2 <0.001 3 <0.001 Event *Time 2 0.001 Treatment 9 <0.001 OVA table is not shown; all interactions not displayed here had Pr >F values above 0.05. Time r efers to the volumetric water content percentage taken before and after runoff initiation § Event co nsists of the May, June, August runoff events. Nitrogen sources used were ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated urea (PCU) and an untreated control (UTC). Treatment refers to sources; ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated urea (PCU) by unfertilized buffer strip sizes (0.0, 0.9, 1.8, and 3.6m)

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57 Table 2 13 Soil moisture differences across fertilizer t reatment (source by buffer strip size) Source Buffer Soil Moisture m S Ammonium Sulfate 0 .0 44.667 ab Ammonium Sulfate 0.9 44.968 a Ammonium Sulfate 1.8 44.998 a Ammonium Sulfate 3.6 44.059 abc Urea Formaldehyde 0 .0 42.442 a d Urea Formaldehyde 0.9 42.763 a d Urea Formaldehyde 1.8 43.588 abc Urea Formaldehyde 3.6 42.175 bcd Polymer Coated Urea 0 .0 40.253 e Polymer Coated Urea 0.9 41.117 e Polymer Coated Urea 1.8 42.907 a d Polymer Coated Urea 3.6 41.591 cde Untreated Co ntrol 42.911 a d Soil water content percentage was taken before and after runoff initiation and averaged across source by buffer strip size. Means with the same letters were not aration.

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58 Table 2 14 Tukey means estimates for ortho phosphate loads influence by differing ureaformaldehyde buffer strip sizes Effect Label Estimate Standard Error DF t Value alpha Lower Upper m UF 0.0 vs 0.9 0.003 0. 003 117 0.84 0.403 0.05 0.009 0.004 0.0 vs 1.8 0.003 0.003 117 0.87 0.384 0.05 0.003 0.009 0.0 vs 3.6 0.004 0.003 117 1.38 0.169 0.05 0.002 0.011 0.9 vs 1.8 0.005 0.003 117 1.71 0.089 0.05 0.001 0.012 0.9 vs 3.6 0.007 0.003 117 2.22 0. 028 0.05 0.001 0.013 1.8 vs 3.6 0.002 0.003 117 0.51 0.611 0.05 0.005 0.008 ormaldehyde (UF) ortho phosphate l oads by unfertilized buffer strip sizes (0.0, 0.9, 1.8, and 3.6m). Adjusted Pr > |t|, lower, and upper limits were equal to normal ized and removed. Table 2 15 Analysis of variance for normalized difference vegetation index, ratio vegetative index, visual color, visual quality, and visual d ensity NDVI RVI Color Quality Density Effect Df pr > F pr > F p r > F pr > F pr > F Event 2 <0.001 <0.001 <0.001 <0.001 <0.001 SPL 33 <0.001 <0.001 <0.001 <0.001 <0.001 DAI 4 <0.001 <0.001 <0.001 <0.001 <0.001 Event *SPL 66 <0.001 <0.001 <0.001 <0.001 <0.001 DAI*SPL§ 132 0.091 0.009 <0.001 0.052 0.147 F ull ANOVA table is not shown; all interactions not displayed here had Pr >F values above 0.05. Event consists of the May, June, and August runoff events. § Subplot location (SPL) refers to fertilized swath, unfertilized buffer strip and the m anagement o f the area above by days after initiation (DAI) across all treatment combinations.

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59 Table 2 16 Ratio vegetative index values for subplot location by days after i nitiation Ratio Vegetation Index F § Buffer Day 1 Day 7 Day 14 m Fert Unfe rt Above Fert Unfert Above Fert Unfert Above AS 0 .0 3.208 3.114 3.942 a d 3.480 b e 3.942 ab 3.514 a e AS 0.9 3.177 3.230 3.001 4.049 abc 3.587 b e 3.534 b e 3.961 ab 3.787 abc 3.537 a e AS 1.8 3.067 2.912 2.903 4.212 a 3.431 de 3.50 4 b e 4.067 a 3.536 a e 3.499 a e AS 3.6 3.252 3.122 2.990 4.081 ab 3.374 de 3.483 b e 3.930 ab 3.380 b e 3.472 a e UF 0 .0 2.998 3.104 3.405 de 3.498 b e 3.458 b e 3.476 a e UF 0.9 3.227 2.955 3.172 3.558 b e 3.253 e 3.387 de 3.511 a e 3.289 cde 3.364 b e UF 1.8 3.024 2.831 2.983 3.567 b e 3.260 e 3.454 cde 3.450 b e 3.249 cde 3.411 b e UF 3.6 3.093 2.967 3.062 3.578 b e 3.219 e 3.493 b e 3.504 a e 3.237 cde 3.456 b e PCU 0.0 3.042 3.058 3.452 cde 3.405 de 3.376 b e 3.3 90 b e PCU 0.9 3.119 2.857 3.041 3.585 b e 3.318 e 3.478 b e 3.595 a e 3.302 cde 3.526 a e PCU 1.8 3.318 2.903 3.060 3.627 a e 3.196 e 3.342 de 3.669 a d 3.130 de 3.296 b e PCU 3.6 3.252 2.939 2.988 3.653 a e 3.143 e 3.403 de 3.715 a d 3.050 e 3.372 cde UTC 2.930 3.115 e 2.995 e Subplot location (SPL) refers to fertilized swath, unfertilized buffer strip and the management of the area above the fertilized swath by days after initiation (DAI) across all treatment combinati ons. NIR /R VIS RVI was taken weekly for a month following runoff events. § Nitrogen sources used were ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) and an unt reated control (UTC). Means w ith the same letter in a given day after i nitiation (DAI) were not significantly differen t (P = 0.05) according to

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60 Table 2 16 Continued Ratio Vegetation Index F § Buffer Day 21 Day 28 m Fert Unfer t Above Fert Unfert Above AS 0.0 3.706 abc 3.345 abc 3.404 a f 3.248 b f AS 0.9 3.780 ab 3.935 a 3.235 bc 3.508 a f 3.575 a e 3.299 a f AS 1.8 3.797 ab 3.463 abc 3.313 bc 3.658 a d 3.234 b f 3.248 b f AS 3.6 3.706 abc 3.498 abc 3.20 2 bc 3.503 a f 3.147 c f 3.195 b f UF 0.0 3.492 abc 3.466 abc 3.509 a f 3.286 a f UF 0.9 3.560 abc 3.469 abc 3.406 abc 3.513 a f 3.170 b f 3.163 c f UF 1.8 3.531 abc 3.329 bc 3.378 abc 3.523 a f 3.049 ef 3.174 b f UF 3.6 3.557 abc 3. 371 abc 3.311 bc 3.559 a f 3.119 c f 3.205 b f PCU 0.0 3.438 abc 3.248 bc 3.498 a f 3.139 c f PCU 0.9 3.489 abc 3.236 bc 3.296 bc 3.768 ab 2.967 f 3.263 b f PCU 1.8 3.716 abc 3.173 c 3.266 bc 3.672 abc 3.033 ef 3.090 def PCU 3.6 3.74 7 abc 3.266 bc 3.266 bc 3.876 a 3.060 def 3.144 c f UTC 3.144 c 2.997 ef Subplot location (SPL) refers to fertilized swath, unfertilized buffer strip and the management of the area above the fertilized swath by days after initiation ( DAI) across all treatment combinations. NIR /R VIS RVI was taken weekly for a month following runoff events. § Nitrogen sources used were ammonium sulfate (AS), ureaformaldehyde (UF), and p olymer coated u rea (PCU) and an untreated control (UTC). Means w ith the same letter in a given day after i nitiation (DAI) were not significantly differen t (P = 0.05) according to

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61 Table 2 17 Ratio v egetati ve index values for subplot l ocation by runoff e vent s Subplot location (SPL) refers to fertilized swath, unfertilized buffer strip and the management of t he area above by days after initiation (DAI) across all treatment combinations. Ratio vegetation index (RVI) value was calculated using: RVI = R NIR /R VIS RVI was taken weekly for a month following runoff events. § Nitrogen sources used were ammonium su lfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) and an untreated control (UTC). Means with the same letter in a given monthly event were not significantly different (P = 0.05) according to Tukey Ratio Vegetation Index F§ Buffer May June August m Fert Unfert Above Fert Unfert Above Fert Unfert Above AS 0 .0 2.980 b e 3.874 a d 3.556 a f 3.660 a f 3.484 a f AS 0.9 3.378 abc 3.353 a d 2.928 b e 3.897 abc 3.554 a f 3.517 a g 3.811 a d 3.9 61 a 3.519 a f AS 1.8 3.347 a d 2.928 b e 2.821 e 4.018 a 3.404 c g 3.516 a g 3.915 ab 3.619 a f 3.543 a f AS 3.6 3.522 a 3.007 b e 2.910 b e 3.858 a d 3.386 d g 3.444 b g 3.703 a e 3.521 a f 3.451 a f UF 0 .0 3.005 b e 2.967 b e 3.421 c g 3.598 a e 3.691 a f 3.532 a f UF 0.9 3.085 a e 2.972 b e 2.918 b e 3.611 a e 3.242 efg 3.527 a g 3.726 a e 3.467 a f 3.451 a f UF 1.8 2.985 b e 2.848 de 2.809 e 3.565 a f 3.194 efg 3.544 a g 3.707 a e 3.389 c f 3.487 a f UF 3.6 3.064 a e 2.946 b e 2.876 cde 3.527 a g 3.190 efg 3.522 a g 3.783 a e 3.412 b f 3.518 a f PCU 0 .0 2.936 b e 2.866 de 3.564 a f 3.464 b g 3.583 a f 3.414 b f PCU 0.9 3.078 a e 2.954 b e 2.950 b e 3.769 a d 3.120 efg 3.511 a g 3.687 a f 3.334 c f 3.501 a f PCU 1.8 3.086 a e 2.871 cde 2.888 b e 3.950 ab 3.108 efg 3.375 c g 3.765 a e 3.281 ef 3.369 c f PCU 3.6 3.121 a e 2.918 b e 2.848 de 3.990 a 3.061 fg 3.432 d g 3.835 abc 3.30 4 def 3.406 b f UTC 2.882 b e 3.039 g 3.188 f

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62 Table 2 18 Normalized difference vegetation i ndex values for subplot location by runoff events Normalized Difference Vegetation Index F§ Buffer May June August m Fert Unfert Above Fert Unfert Above Fert Unfert Above AS 0 .0 0.493 cde 0.583 abc 0.557 a e 0.566 a f 0.551 a f AS 0.9 0.535 abc 0.529 a d 0.487 de 0.585 abc 0.555 a f 0.552 a g 0.578 a e 0.591 a 0.553 a f AS 1.8 0.545 ab 0.497 b e 0.485 de 0.596 a 0.541 c h 0.553 a f 0.589 ab 0.564 a f 0.555 a f AS 3.6 0.550 a 0.496 b e 0.485 de 0.581 abc 0.537 c h 0.545 b h 0.569 a e 0.554 a f 0.546 a f UF 0 .0 0.495 cde 0.492 cde 0.543 b h 0.560 a d 0.571 a e 0.555 a f UF 0.9 0.505 a e 0.492 cde 0.486 de 0.563 a d 0. 523 d h 0.554 a f 0.575 a e 0.548 a f 0.547 a f UF 1.8 0.506 a e 0.488 cde 0.484 de 0.559 a e 0.518 d h 0.556 a f 0.573 a e 0.540 b f 0.550 a f UF 3.6 0.503 a e 0.489 cde 0.481 de 0.555 a f 0.518 d h 0.554 a f 0.579 a d 0.544 a f 0.553 a f PCU 0 .0 0.486 de 0.479 e 0.558 a e 0.548 a h 0.560 a f 0.543 a f PCU 0.9 0.503 a e 0.487 cde 0.490 cde 0.577 abc 0.507 fgh 0.552 a g 0.569 a e 0.533 d f 0.551 a f PCU 1.8 0.504 a e 0.480 de 0.483 de 0.592 ab 0.510 e h 0.537 c h 0.578 a e 0.530 ef 0.537 c f PCU 3.6 0.508 a e 0.485 de 0.479 e 0.595 a 0.503 gh 0.545 b h 0.582 abc 0.532 def 0.542 a f UTC 0.482 de 0.502 h 0.519 f Subplot location (SPL) refers to fer tilized swath, unfertilized buffer strip and the management of the area above by days after initiation (DAI) across all treatment combinations. Normalized difference vegetation index (NDVI) value was calculated using: NDVI = (R NIR R red )/(R NIR + R red ) Average of NDVI values taken weekly for a month following runoff events § Nitrogen sources used were ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) and an untreated c ontrol (UTC). Means with the same letter in a given mont hly event were not significantly different (P = 0.05) according to Tukey

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63 Table 2 19 Visual color ratings for subplot l ocation by runoff e vent s Visual Color Ratings F§ Buffer May June August m Fert Unfert Abo ve Fert Unfert Above Fert Unfert Above AS 0.0 6.2 a 5.0 c j 7.0 ab 5.9 efg 6.5 b e 6.2 d i AS 0.9 6.1 ab 5.1 c j 4.8 f j 6.7 a d 5.0 hij 5.7 fgh 6.3 c h 5.5 i n 6.0 e j AS 1.8 5.0 d j 4.7 ij 6.9 abc 4.9 ij 5.9 efg 6.5 b e 5.1 k o 6.0 e j AS 3.6 6.1 ab 4.9 e j 4.8 g j 6.7 a d 4.8 j 6.1 d g 6.5 b g 5.1 l p 6.0 e j UF 0.0 5.4 b i 4.8 f j 6.2 c g 5.9 efg 6.6 a e 6.0 d i UF 0.9 5.5 a f 5.3 c j 4.8 f j 6.3 b f 4.8 j 5.8 efg 6.5 b g 5.3 j o 5.9 e j UF 1.8 5.6 a e 5.0 c j 4.7 i j 6.2 c g 4.7 j 5.8 efg 6.7 a d 5.0 m p 5.8 g l UF 3.6 5.4 b i 5.0 c j 4.7 hij 6.4 a e 4.8 j 5.8 efg 6.5 b g 5.0 nop 5.7 h m PCU 0.0 5.5 a g 4.6 j 6.8 abc 5.9 efg 7.0 abc 5.9 e j PCU 0.9 5.4 b h 5.0 c j 4.7 hij 7.0 ab 4.7 j 5.8 efg 7.0 abc 5.3 j o 5.8 f k PCU 1.8 5.7 abc 4.9 f j 4.7 hij 7.1 a 4.7 j 5.8 efg 7.3 a 4.7 op 5.9 e j PCU 3.6 5.7 a d 5.0 c j 4.9 e j 7.1 a 4.7 j 5.6 ghi 7.1 ab 5.1 k o 6.0 d i UTC 4.8 g j 4.5 j 4.4 p Subplot location (SPL) refers to fertilized swath, unfertilized buffer strip and the management of the area above by days after initiation (DAI) across all treatment combinations. Average of visual color rating taken weekly for a month following runoff events. Scale is from 1 to 9, 9=optimal turf color, 6=acceptable turf color. § Nitrogen sources used were ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) and an untreated c ontrol (UTC). Means with the same letter in a given monthly run were not significantly different (P = 0.05) according to Tukey

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64 Table 2 20 Visual quality ratings for subplot l ocation by runoff e vents Visual Quality Ratings F§ Buffer May June August m Fer t Unfert Above Fert Unfert Above Fert Unfert Above AS 0.0 5.9 ab 5.2 abc 6.8 a 6.1 a e 6.6 ab 6.5 abc AS 0.9 5.7 abc 5.6 abc 5.0 bc 6.1 a e 5.2 fgh 5.5 b h 6.3 a d 5.6 d h 6.0 b f AS 1.8 5.7 abc 5.2 abc 5.1 abc 6.2 a d 5.1 fgh 5.6 b h 6.9 a 5.4 e h 6.1 a f AS 3.6 5.5 abc 5.4 abc 5.4 abc 6.2 a d 5.3 e h 6.1 a e 6.6 ab 5.3 fgh 6.3 a d UF 0.0 5.9 a 5.3 abc 6.3 ab 6.2 abc 6.1 a f 6.2 a f UF 0.9 5.3 abc 5.5 abc 5.3 abc 5.8 b g 5.3 e h 6.1 a e 6.0 b f 5.1 gh 6.3 a d UF 1.8 5.2 abc 5.6 abc 5.0 bc 5. 7 b g 5.3 e h 5.6 b h 6.2 a e 5.5 d h 6.0 b f UF 3.6 4.9 c 5.4 abc 5.2 abc 5.6 b h 5.5 b h 5.7 b g 6.1 a f 5.3 fgh 5.9 b g PCU 0.0 5.5 abc 4.9 c 6.2 abc 6.0 a f 6.2 a e 6.3 a d PCU 0.9 5.3 abc 5.5 abc 5.0 bc 6.2 abc 5.3 d h 5.7 b g 6.6 ab 5.8 b g 6.0 b f PCU 1.8 5.4 abc 5.4 abc 5.1 abc 6.3 ab 5.1 gh 5.8 b g 6.5 ab 5.4 e h 6.0 b f PCU 3.6 5.0 bc 5.6 abc 5.2 abc 5.8 b g 5.4 c h 5.9 b g 6.1 a f 5.6 c h 6.3 a d UTC 5.1 abc 4.8 h 4.8 h Subplot location (SPL) refers to fertilized swath, unfertilized buffer strip and the management of the area above by days after initiation (DAI) across all treatment combinations. Average of visual quality rating taken weekly for a month following run off events. Scale is from 1 to 9, 9=optimal turf quality, 6=acceptable turf quality. § Nitrogen sources used were ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) and an untreated c ontrol (UTC). Means with the same letter in a given monthly run were not significantly different (P = 0.05) according to Tukey

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65 Table 2 21 Visual density ratings for subplot l ocation by runoff e vents Visual Density Ratings F§ Buffer May June August m Fe rt Unfert Above Fert Unfert Above Fert Unfert Above AS 0 .0 6.1 abc 5.3 bc 6.7 a 5.9 a g 6.5 abc 6.4 abc AS 0.9 5.8 abc 6.1 ab 5.1 c 6.0 a f 5.2 e i 5.5 b i 6.4 abc 5.6 b g 5.7 b g AS 1.8 6.1 abc 5.7 abc 5.4 bc 6.2 a d 5.1 f i 5.5 b i 6.9 a 5.1 fg 5.9 b g AS 3.6 5.7 abc 5.6 abc 5.7 abc 6.2 abc 5.0 ghi 5.8 a h 6.6 ab 5.4 d g 6.2 a e UF 0 .0 6.6 a 5.2 bc 6.1 a e 5.9 a g 6.1 a f 6.0 a g UF 0.9 5.5 bc 6.0 abc 5.3 bc 5.8 a h 5.2 d i 5.9 a h 5.8 b g 5.0 g 6.2 a e UF 1.8 5.4 bc 5.8 abc 5.2 bc 5.7 b i 5. 1 f i 5.7 b i 6.2 a e 5.3 efg 5.8 b g UF 3.6 5.4 bc 5.8 abc 5.4 bc 5.3 c i 5.2 d i 5.6 b i 6.1 a f 5.4 d g 5.9 b g PCU 0 .0 5.8 abc 5.3 bc 6.1 a e 5.8 a h 6.4 abc 6.2 a e PCU 0.9 5.6 abc 6.0 abc 5.5 bc 6.1 a e 5.3 c i 5 .7 b i 6.4 abc 5.5 c g 5.9 a g PCU 1.8 5.4 bc 5.6 bc 5.2 bc 6.3 ab 4.9 hi 5.8 a h 6.4 abc 5.0 g 5.9 b g PCU 3.6 5.3 bc 5.8 abc 5.6 bc 5.9 a h 5.3 d i 5.8 a h 6.1 a e 5.5 c g 6.2 a e UTC 5.2 bc 4.8 i 5.0 g Subplot location (SPL) refers to fertilized swath, unfertilized buffer strip and the management of the area above by days after initiation (DAI) across all treatment combinations. Average of visual density rating taken weekly for a month following run off events. Scale is from 1 to 9, 9=optimal turf density, 6=acceptable turf density. § Nitrogen sources used were ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) and an untreated c ontrol (UTC). Means with the same letter in a given monthly run were not significantly different (P = 0.05) according to Tukey

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66 Table 2 22 Visual color ratings for subplot location by days after i nitiation F§ Buffer Day 1 Day 7 Day 14 m Fert Unfert Above Fert Unfert Above Fert Unfert Above AS 0.0 5.9 abc 5.7 a e 7.0 a 5.8 d g 6.7 a 5.9 a e AS 0.9 5.7 a e 5.0 d g 5.2 c g 6.5 a d 4.9 ghi 5.5 e h 6.7 a 5.7 cde 6.1 a e AS 1.8 6.0 abc 4.9 d g 5.3 c g 6.8 ab 4.8 hi 5.7 d h 6.6 ab 5.7 cde 6.1 a e AS 3.6 5.7 a e 4.8 efg 5 .4 b f 6.7 abc 4.9 ghi 5.5 e h 6.6 ab 5.7 cde 6.0 a e UF 0 .0 5.9 abc 5.5 b f 5.8 d g 5.3 fgh 6.3 a e 5.8 a e UF 0.9 5.5 b f 4.8 fg 5.3 c g 5.9 c f 5.0 ghi 5.5 e h 6.3 a e 5.7 cde 5.8 a e UF 1.8 5.8 a d 4.8 efg 5.2 c g 6.0 b f 5.0 ghi 5.6 e h 6.2 a e 5.7 cde 6.0 a e UF 3.6 5.8 a d 4.8 fg 5.2 c g 5.8 d g 4.8 hi 5.3 fgh 6.5 abc 5.7 cde 6.0 a e PCU 0 .0 6.2 ab 5.3 c g 6.0 b f 5.4 e h 6.3 a e 6.0 a e PCU 0.9 6.2 ab 4.9 d g 5.2 c g 5.9 c f 5. 0 ghi 5.5 e h 6.4 a d 5.7 cde 6.0 a e PCU 1.8 6.5 a 4.5 g 5.3 c g 6.1 b f 4.9 ghi 5.4 e h 6.5 abc 5.5 e 5.8 a e PCU 3.6 5.9 abc 4.8 efg 5.2 c g 6.2 a e 4.8 hi 5.6 e h 6.4 a d 5.7 cde 5.8 b e UTC 4.4 g 4.3 i 5.6 de Subplot location (SPL) refers to fertilized swath, unfertilized buffer strip and the management of the area above by days after initiation (DAI) across all treatment combinations. unoff events. Scale is from 1 to 9, 9=optimal turf color, 6=acceptable turf color. § Nitrogen sources used were ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) and an untreated c ontrol (UTC). Means with the same letter in a g iven monthly run were not significantly different (P = 0.05) according to Tukey

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67 Table 2 22 Continued Visual Color Ratings F§ Buffer Day 21 Day 28 m Fert Unfert Above Fert Unfert Above AS 0.0 5.6 f k 6.3 bcd 5.4 d g AS 0.9 6.6 a d 5.3 f k 5.5 f k 6.3 bcd 5.0 g l 5.1 g k AS 1.8 6.7 abc 4.9 i m 5.3 f k 6.4 abc 4.5 h l 5.1 g k AS 3.6 6.8 ab 4.8 klm 5.7 e j 6.3 bcd 4.4 i l 5.3 e h UF 0.0 6.1 b g 5.8 c h 6.0 c f 5.3 e h UF 0.9 6.5 a e 5.2 h l 5.7 e j 6.2 cde 4.9 g l 5.3 f i UF 1.8 6.5 a e 4.8 klm 5.3 g l 6.4 abc 4.3 kl 4.9 g l UF 3.6 6.2 b f 4.9 i m 5.5 f k 6.2 cde 4.4 i l 5.0 g l PCU 0.0 6.8 ab 5.3 f k 6.7 abc 5.2 f j PCU 0.9 6.6 a d 4.8 klm 5.5 f k 7.1 ab 4.5 h l 5.0 g l PCU 1.8 7.2 a 4.4 lm 5.6 f k 7.2 a 4.3 jkl 5.1 g k PCU 3.6 7.3 a 4.8 j m 5.8 d i 7.2 a 4.5 h l 5.2 f j UTC 4.2 m 4.2 l Subplot location (SPL) refers to fertili zed swath, unfertilized buffer strip and the management of the area above by days after initiation (DAI) across all treatment combinations. Average of visual color rating taken weekly for a month following runoff events. Scale is from 1 to 9, 9=optimal turf color, 6=acceptable turf color. § Nitrogen sources used were ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) and an untreated c ontrol (UTC). Means with the same letter in a given monthly run were not significantly diffe rent (P = 0.05) according to T ukey

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68 Table 2 23 Analysis o f variance for dark green color i ndex Dark Green Color Index ANOVA Effect df Pr > F Event 22 0.353 Event *Distance § 16 <0.001 Distance*Treatment 37 <0.00 1 Treatment refer s to sources; ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) by unfertilized buffer strip sizes (0.0, 0.9, 1.8, and 3.6m). Event consists of the M ay, June and August runoff events § Each distance refers to the distance away from the fertilized swath with 1 = the 56.0 cm increment adjacent to the fertilized swath, 2 = the 56.0 to 112 .0 cm ar ea downslope of fertilized swath

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69 Table 2 24 Dark green color index s eparated by distance adjacent to fertilized swat h F Buffer Dark Green Color Index m D0 D1 D2 D3 D4 D5 D6 D7 D8 AS 0 .0 0.510 0.509 a § AS 0.9 0.516 0.483 bcd 0.488 AS 1.8 0.516 0.488 bcd 0.486 0.490 0 .502 a AS 3.6 0.510 0.489 bcd 0.490 0.492 0 .489 ab 0.489 0.486 0.4 92 0.495 UF 0 .0 0.506 0.498 ab UF 0.9 0.506 0.483 bcd 0.486 UF 1.8 0.507 0.487 bcd 0.485 0.483 0 .489 ab UF 3.6 0.508 0.486 bcd 0.484 0.487 0 .485 b 0.483 0.486 0.491 0.494 PCU 0 .0 0.509 0.497 abc PCU 0.9 0.514 0.4 80 d 0.486 PCU 1.8 0.511 0.483 cd 0.481 0.480 0 .485 b PCU 3.6 0.512 0.482 d 0.483 0.485 0 .483 b 0.483 0.483 0.485 0.488 Nitrogen sources used were ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) and an untr eated c ontrol (UTC). Each distance refers to the distance away from the fertilized swath with 1 = the 56.0 cm increment adjacent to the fertilized swath, 2 = the 56.0 to 112 .0 cm ar ea downslope of fertilized swath § Means with the same letter in a given distance were not significantly different (P = 0.05) according to T means separation.

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70 Table 2 25 Dark green color i ndex separated by fertilizer source by buffer strip size F Buffer Dark Green Color Index m D0 D1 D2 D3 D4 D5 D6 D7 D 8 AS 0 .0 0.51 0 0.509 AS 0.9 0.516 a § 0.483 b 0.488 b AS 1.8 0.516 a 0.488 c 0.486 c 0.490 c 0.502 b AS 3.6 0.510 a 0.489 b 0.490 b 0.492 b 0.489 b 0.489 b 0.486 b 0.492 b 0.495 b UF 0 .0 0.506 a 0.498 b UF 0.9 0.506 a 0 .483 b 0.486 b UF 1.8 0.507 a 0.487 b 0.485 b 0.483 b 0 .489 b UF 3.6 0.508 a 0.486 b 0.484 b 0.487 b 0 .485 b 0.483 b 0.486 b 0.491 b 0.494 b PCU 0 .0 0.509 a 0.497 b PCU 0.9 0.514 a 0.480 b 0.486 b PCU 1.8 0.511 a 0.483 b 0. 481 b 0.480 b 0 .483 b PCU 3.6 0.512 a 0.482 b 0.483 b 0.485 b 0 .485 b 0.483 b 0.483 b 0.485 b 0.488 b Nitrogen sources used were ammonium sulfate (AS), ureaformaldehyde (UF), and polymer coated u rea (PCU) and an untreated c ontrol (UTC). Each di stance refers to the distance away from the fertilized swath with 1 = the 56.0 cm increment adjacent to the fertilized swath, 2 = the 56.0 to 112 .0 cm ar ea downslope of fertilized swath § Means with the same letter in a given fertilizer source by buffer s trip size were not significantly different (P = 0.05) according to T

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71 Table 2 26 Dark green color index for distance away from fertilized swath by e vent s Dark Green Color Index May June August 1 0.4952 ab 0.4946 b 0.5076 ab 0 0.5089 a 0.5108 a 0.5131 a 1 0.4783 bc 0.4873 b 0.4992 b 2 0.4744 c 0.4834 b 0.4966 b 3 0.4765 c 0.4857 b 0.4944 b 4 0.4765 c 0.4873 b 0.5026 ab 5 0.4780 bc 0.4832 b 0.4908 b 6 0.4777 bc 0. 4842 b 0.4905 b 7 0.4736 c 0.4881 b 0.5055 ab 8 0.4766 c 0.4884 b 0.5137 a Each distance refers to the distance away from the fertilized swath with 1 = the 56.0 cm increment adjacent to the fertilized swath, 2 = the 56.0 to 112 .0 cm ar ea d ownslope of fertilized swath Distance 0 refers to the fertilized swath and distance 1 is the UTC. event were not significantly different (P = 0.05)

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72 CHAPTER 3 TOTAL SO LUBLE NITROGEN LEACHED FROM NINE FERTILIZER SOURCES IN A BERMUDAGRASS FAIRWAY RECEIVING EXCESSIVE IRRIGATION Introduction the potential to cause eutrophication, red tides, and algal blooms (Spalding and Exner, 1993). Overall, most previous turfgrass res earch has generally found that n itrogen (N) leaching is a small risk in properly managed turfgrass (Erickson et al., 2008; Reike and Ellis, 1974; Sheard et al., 1985; Starr and D eRoo, 1981; Mancino and Troll, 1990; Miltner et al., 1996). However, research has suggested that numerous factors such as fertilizer rate, source, frequency, application technique, irrigation management, establishment period, and turf species and cultivar are associated with N leaching losses (Barton, et al., 2006; Bowman et al., 2002; Cisar et al., 1991; Erickson et al., 2010; Geron et al., 1993; Reike and Ellis, 1974; Snyder et al., 1984; Snyder et al., 1989; Petrovic, 1990). Several methods have been use d in studying N leaching factors. Pet rovic (1990), categorized them as soil testing, measuring saturated zone nutrients levels, monitoring drainage, trapping NO 3 N on ion exchange sites and testing groundwater supplies fo r nutrient concentration. Morto n e t al. (1988) reported that when N fertilizers where applied at recommended rates, NO 3 N leachate was low and below the maximum contaminant limit (MCL) of 10mg L 1 for drinking water set by the United States Environmental Protection Agency (USEPA) under th e Safe Drinking Water Act of 1974 (USEPA, 1976). The objectives of this study were to determine total soluble N leaching following an excess rate of applied N cou pled with high natural rainfall or simulated irrigation practices.

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73 Materials and Methods Tri Education Center (WFREC) in Jay, FL (30463 N, 8708 W). Thirty year average temperature and rainfall data has been compiled for Jay, FL (Figure 3 1). Plots were established on a native soil comprised of 85.3% Dothan fine sandy loam and 14.7% Fuquay loamy sand (NRCS, 2009), with an approximate pH of 5.7 and CEC value of 3.7 (Waters Agricultural Laboratory, Inc., Camilla, GA). Forty high density polyethylene (HDPE) drainage lysime ters were installed in the center of each 3.1 m x 6.1 m plot. Lysimeters measured 56 cm in diameter and 88 cm in height with a volume of 200 L. Lysimeters were assembled by placing HDPE cylinders into a one piece galvanized steel base unit measuring 25.4 c m in height. The leachate was accessed directly with the 9.5 mm LDPE tubing through one of two 9.5 mm holes bored through the side wall 10.16 cm down from the top rim of the lysimeter and routed to the inside apex of the conical bottom, the second hole pla ced directly above allowed for a ventilation line to prevent pressure differentials. The tubing was run underground from the lysimeter to a central aboveground collection portal. Lysimeters were installed by boring and removing soil in 15.2 cm sections to an approximate depth of 107 cm. Lysimeters were placed in holes and 38 L of washed egg rock (1.9 6.4 cm) were placed in the bott om of each lysimeter. The rock was covered with fitted non woven polyolefin cloth that was secured with a hoop of 1.3 cm HDPE tubing to reduce soil intrusion into the rock. Soil was replaced into the lysimeters as it had been removed from the soil profile. Soil was gently tamped with a tamping tool (17.0 kg and 858.0 cm 2 ) to approximate original soil bulk density. The top of each lysimeter was 10 cm below the soil surface.

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74 Cynodon dactylon x C. transvaalensis Burtt Davey) was established from sod on 31 May 2011. Plots were mowed three times weekly at 12.7 mm in height using a 3500 Toro Sidewinder ree l mower (The Toro Co., Bloomington, MN). Turf stands were allowed to mature until mid September, 2011. The turf received three 24.0 kg N ha 1 foliar applications between 31 May 2011 and 30 Aug 2011 to increase turf quality. Four quadrants of four Rain Bi rd 7005 (Rain Bird Corp., Azusa, CA) rotary irrigation heads supplied irrigation during turf establishment. Irrigation heads were arranged in a square layout with four 90 arcs creating a precipitation rate of 0.5 mm min 1 Throughout the establishment per iod plots were irrigated at a rate equal to reference evapotranspiration (ET) according to FAWN (Florida Automated Weather Network, University of Florida, Gainesville, FL) weather station at the Jay research ormity (CU) (Christiansen, 1942) for the irrigation system averaged >80% throughout several summer 2011 audits. However, uniformity was greatly dependent on wind strength and direction. The fertilizer t reatments were arranged in a complete block design wi th four replications. Nine organic and inorganic N sources were applied at a 144 kg N ha 1 rate using hand spreader on 20 September 2011, 22 May 2012 and 27 August 2012. The 27 Fertilizers sources used are given in (Table 3 1). The 20 September 2011 (event 1) and 22 May 2012 (event 2) were an identical irrigation regime, while a new protocol was developed for the 27 August 2012 (event 3) event. Forty eight hours prior to treatm ent in the first two runs, plots were pre irrigated to soil saturation to ensure uniform water

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75 distribution. Pre wet irrigation totaled 57.2 mm and was stopped 24h prior to fertilizer application to allow soil moisture to return to field capacity. During t he 27 August 2012 leaching event there was no pre wetting of the soil. Leachate samples were collected at 0, 4, 8, 12, 24, 48, 72, 96, 120, 144, and 168 hours after treatment (HAT), fo llowed by weekly sampling through 5 February 2012 (event 1), and 24 Jul y 2012 (event 2). In the third event leachate samples were taken at 24, 48, 72, 96,168 HAT, followed by weekly sampling for 31 weeks until 1 April 2013 (event 3). Four separate irrigation events conducted at 7:00, 10:00, 13:00 and 17:00 supplied the 25.4 mm d 1 total in the first two events, while weekly irrigation audits were taken to monitor irrigation uniformity (Appendix B). Irrigation audits were performed every two weeks during the third event. Additional precipitation from rainfall events and subseq uent increases in leachate were quantified and reported as comparators to non minus evapotranspiration (R ET) based irrigation scheme. Infiltration rates were deter mined by a single ring infiltrometer utilizing the falling head method vs. static head (Wu, 1998). Infiltration rates were taken weekly thr oughout the first two runs until 01 December 2012 when it was move d to every other week i n the third event. Rainfall and ET t otals were recorded using FAWN. Visual data were taken using the National Turfgrass Evaluation Program rating system (Shearman and Morris, 200x) Color, quality, density ratings were taken weekly from 20 May 2012 through 1 Dec 2012. Starting 1 Dec 2012 visual ratings were collected twice monthly. The NTEP scale ranges from 1 9 with a quality rating of 9 being

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76 optimal and 1 being dead turf; color rating of 9 being a dark green turf and 1 light pale green color; and density rating of 9 being maximum d ensity. Ratings in this study > 6 were considered to be acceptable Ratings were reported in whole numbers. Leachate samples were collected with the use of a leachate sampling vacuum apparatus. Once each leachate sample was collected, the entire vacuum t rap was sanitized by distilled water pumped into the triple rinse device (FDEP, 2004). Scintillation vial samples were immediately preserved using 1:1 sulfuric acid solution (pH <2) and chilled on wet ice (<4C) after extraction (FDEP, 2004). Following sc intillation vial collection, leachate catchment vessels were emptied into an 18.9 L bucket and weighed for leachate volume with the use of a hanging scale. Field duplicates and field blanks were taken every tenth sample (FDEP, 2004). Equipment blanks were taken at the end of each sampling period to ensure sufficient distilled water rinsing and the preventi on of contamination. Irrigation water samples were taken regularly to provide NO 3 N concentration added via irrigation. Samples were either frozen or ref rigerated based upon next sample transport from Jay, FL to Gainesville, FL. All samples were transported on wet ice in insulated coolers (FD EP, 2004). Once the samples arrived in Gainesville, those that were not immediately analyzed were kept frozen. All samples were analyzed for total soluble nitrogen (TSN) using an Antek 9000NS Series analyzer (Antek Instruments, Inc., Houston, TX). The Antek 9000N instrument allows for TSN calibration standards to be analyzed, which produce internal calibration curves. The standard curve before each

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77 test required an R 2 value of 0.995 and each four injection calibrant was examined for outliers using a 5.0% relative standard deviation (RSD). Once the calibration curves of the known standards were determined to be suffici ent, raw unknown N contents were analyzed and compared to the known calibration curve concentrations. Each sample was initially tested on a 1 10 mg TSN L 1 calibration curve with four injections per sample. Samples with less than 1 mg TSN L 1 concentration were under the method detection limit (MDL) and considered to have undetectable levels. Samples greater than 10 mg TSN L 1 were reanalyzed on a 10 100 mg TSN L 1 calibration curve with the same set requirements. Samples with a RSD >5.0% w ere reanalyzed un til an acceptable standard deviation was achieved. Results The main objective of the study was to identify the most effective fertilizer source to reduce TSN leaching. To determine if one or more source s performed greater than all others data were analyze d using SAS/GLIMMIX across N fertilizer source s using a fitted linear mixed model All samples analyzed for TSN from the second and third events were under the method detect limit (<1 mg TSN L 1 ) and sample analysis was stopped. At no time were difference s between N sources observed. The fitted linear mixed effects model for leachate determined sampling time significance (Table 3 2 ). At 1008 HAT, the highest average leaching loads were observed followed by 840 HAT. Leaching occurring 12 HAT had the least TSN collected (Table 3 4). Change in visual evaluations as a resu lt of fertilization application was fitted into a linear mixed effects model which showed time significant for visual color, quality, and density (Table 3 3). The best v isual color ratings o ccurred at 14 and 21 DAT (Table 3

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78 5). Visual quality ratings at 14, 21, 35, 126, and 140 DAT had the best overall quality. Visual quality at 7, 49, 77, 91 and 105 DAT resulted in lower quality ratings. Visual density was greatest at 14 and 35 DAT At all collection dates visual color, quality, and density were above the minimum acceptable rating. Analysis of visual color showed an event by fertilizer source significance. During the third leaching event, ammonium sulfate, polymer coated urea (Polyon) sulfu r coated urea, polymer sulfur coated urea ( Agrium XCU ) methylene urea ( Nutralene ) and activated sewage sludge ( ) provided the highest visual color ratings (Table 3 6) The untr eated control provided the lowest visu al color All fertilizer sou rces, with the exception of the untreated control were above the minimum acceptable rating in the third event. There were no differences between fertilizer sources during the second event. Discussion In this study there was no fertilizer source that perfo rmed better throughout the evaluation period. Time seemed to be the biggest factor according to nitrogen leaching, visual ratings, and percolation ratings. Only a small fraction of the fertilizer applied was recovered via N leaching across all three events Unaccounted N was presumably lost through volatilization, runoff and the collection process. With the excessively high amounts of irrigation in the first two events, runoff, and ponding water that was collected an d analyzed contained high levels of TSN ( 10 100 mg TSN L 1 ). High runoff TSN was also confirmed with a visual N response to the hillside adjacent to the study. Another possible explanation to the unaccounted N was a situation that would have promoted anaerobic condition s with high levels of bio chemical oxygen demand (BOD) BOD is the total amount of oxygen from water used by bacteria during the

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79 process of oxidizing organic matter (Hach et al., 1997). Converting the organic matter from a soluble fraction to a biological s olid encourages removal o f the organic matter through the process biological cells settling (Grady et al. 1980). E xcessive BOD and low oxygen levels can encourage growth of anaerobic bacteria such as a mucilaginous coating which can clog groundwater leaching (County of Barnstabl e 2011). Denitrifying bacterial relies on BOD as a primary food source in systems where bacte rially mediated nitrogen removal occurs (County of Barnstable, 2011). After dry downs during the second and third runs, a majority of the plots began to grow algae on the turf surface. The anaerobic environment also had the potential to slow or prevent nitrification altogether. Chen et al., (2007) found that in waterlogged conditions; both the amount of ammonia volatilization and the percentage of lost f ertilizer N were higher than under non waterlogged conditions. Chen (2007) also found that the ammonium volatilization rate increased with increasing N rates. With our waterlogged conditions and excessively high ( 144 kg N ha 1 ) rate of N application, there was the pot ential for excessively high volatilization rates. Gioacchini (2002) reported volatilization losses range between 1 to 60% of applied N. Many factors effect nitrogen volatilization loss es ; with the most important being pH, nitrate concentration, and wind s peed (De Datta, 1981). The depletion on carbon dioxide i n floodwater during the day and restored levels during night respiration cause diurnal variations in O2 content and pH. During a given day, the pH may reach 10 and shift 2 3 units at night (Mikkelsen et al., 1978), while the O2 levels potentially could be oversaturated by 200% (Roger et al., 1983).

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80 In addition to the possibility of runoff and volatilization, the collection of each leachate sample occurred at the end of lysimeters sampling collection. If stratification occurred in the lysimeters, the gravity fed vacuum extraction of water grab samples has the potential to have missed the N contained in each lysimeter.

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81 Figure 3 1 Compiled Thirty Year Weathe r Data for the Jay FL region from 1982 2012 : NOAA National Climatic Data Center

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82 Figure 3 2 Total soluble nitrogen (TSN) Loads in leachate from September 20 th 2011 to February 5 th 2012.

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83 Figure 3 3 Rainfall in Jay, FL from September 20 th 2011 to February 5 th 2012.

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84 Table 3 1 Leaching study nitrogen fertilizer sources The Fertilizer Institute. 2012. Enhanced Efficiency Fertilizers. 24 October 2012 < http://www.tfi.org/ >. Sartain, J.B., and J.K. Kruse. 2001. Selected Fertilizers Used in Turfgras s Fertilization. Inst. of Food and Agric. Sci. (IFAS), CIR. 1262. Univ. of Florida, Gainesville. Product Class Analysis Release Mechanism Additional Information Ammonium Sulfate soluble 21 0 0 Imm ediately available for plant u ptake 24% Sulfur and high burn p otential Urea soluble 46 0 0 Immediately available for plant u ptake Non Ionic c ompound Stabilized Urea (UFLEXX) soluble 46 0 0 Immediately available for plant u ptake C ompositi on inhibits volat ilization and n itrification UreaForm(Nitroform) slow release 38 0 0 Biological a ctivity 10 15% Unreact ed u rea 4 5 methyl groups or more Methylene Urea (Nutralene) slow release 40 0 0 Biological a ctivity 15 30% Unreacted u rea 3 4 methyl groups or more Activated Sewage Sludge (Milorganite) slow release 6 2 0 Biological a ctivity Natural o rganic contains water insolubl e nitrogen Polymer Coated Urea (Poly on) controlled release 41 0 0 Osmotic d iffusion Reactive layer technology Polymer/Sulfur Coated Ure a (XCU, Agrium Technologies) controlled release 43 0 0 Diffusion and capillary a ction Polymer/sulfur coated h ybrid Sulfur Coated Urea (SCU) controlled release 39 0 0 Water p enetration through micropores and imperfections Coating t hickness, quality, biolog ical activity, soil pH and tempe rature influence release. Burn p otential

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85 Table 3 2 Analysis of variance f or total soluble nitrogen leachate Leaching ANOVA Event One TSN Effect D f pr > F 9 0.157 DAT § 26 <0.001 Treatment* DAT 234 0.844 Event Two 9 1.000 DAT § 16 1.000 Treatment* DAT 144 1.000 Event Three 9 1.000 DAT § 34 1.000 Treatment* DAT 306 1.000 Table 3 3 Analysis of variance for visual color, visual quality, and visual d ensi ty Color Quality Density Effect Df pr > F pr > F pr > F Event 1 0.053 0.758 0.967 Treatment§ 9 0.056 0.162 0.165 16 < 0.001 <0.001 <0.001 Event Treatment 9 0.027 0.52 9 0.30 1 Treatment* DAT 144 0.084 0.999 0.989 9=optimal turf quality/density, 6=acceptable turf quality/d ensity. nt consisted of event two and three. § Treatments refer to nitrogen sources used; ammonium sulfate, urea, stabilized urea, ureaformaldehyde, methylated urea, biosolid, polymer coated urea, sulfur coated urea and polymer/sulfur coated urea. Days after Treatment (DAT) consists of the weekly visual ratings assessment during the second and third leaching events.

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86 Table 3 4 Total soluble nitrogen leachate loads by days after t reatmen t during the first event Total Soluble Nitrogen Loads DAT DA T TSN DAT TSN DAT TSN g g g 0 h 19.42 b e 14d 21.06 b e 77d 17.55 b e 4 h 2.52 de 21d 20.24 b e 84d 14.41 b e 8 h 1.83 de 28d 26.10 bc 91d 6.57 cde 12 h 1.14 e 35d 34.71 b 98d 3.71 de 1d 4.61 de 42d 51.48 a 105d 3.66 de 2d 8.35 cde 49d 22.16 bcd 112d 4.73 de 3d 4.86 de 56d 12.44 cde 119d 2.45 de 4d 4.68 de 63d 13.80 cde 126d 4.58 de 7d 9.96 cde 70d 11.16 cde 133d 2.10 de AT ) consist of the lysimeter sampling ti mes; (0, 4, 8, 12 hours and 1, 2, 3, 4, 7 days followed by weekly sampling for 22 weeks). Total soluble nitrogen (TSN) mg L 1 m eans w ith the same letter were not significantly different (P = 0.05) according to Tu

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87 Table 3 5 Visual c olor, visual q uality, and visual density ratings by days after t reatment Visual Ratings DAT Color Quality Density 1 6.4 def § 6.6 c f 6.3 cd 7 6.4 ef 6.2 fg 6.1 d 14 7.3 ab 7.5 a 7.6 a 21 7.5 a 7.1 abc 6.8 bc 28 6.6 c f 6. 6 b f 6.7 bc 35 6.9 bcd 7.2 ab 7.0 ab 42 7.0 bc 6.5 def 6.6 bcd 49 6.5 def 6.0 g 6.3 cd 56 6.8 b e 6.7 b e 6.7 bc 63 6.8 b e 6.6 c f 6.6 bc 77 6.6 cde 6.2 gf 6.4 cd 91 6.7 b e 6.3 d g 6.5 bcd 105 6.8 b e 6.2 efg 6.4 cd 126 6.5 c e 6.9 a e 6.8 bc 140 6.0 f 7.0 a d 6.8 bc 154 6.8 b e 6.7 b f 6.5 bcd 168 6.4 def 6.6 b f 6.4 cd Visual color, quality and density was rated using the NTEP scale which is from 1 to 9, 9=optimal turf quality/density, 6=acceptable tu rf quality/density. until 01 December 2012 when it was moved to a biweekly basis in the third leaching event. § Means w ith the same letter were not significantly different ( P = 0.05) according to Tu Table 3 6 Visual c o lor ratings for leaching event by fertilizer source Color Ratings Fertilizer Source Event Two Event Three Ammonium Sulfate 6.9 7.1 a Polymer Coated Urea 6.7 7.1 a Sulfu r Coated Urea 6.8 7.2 a Agrium XCU 6.7 6.9 a Nutralene 6.5 7.0 a Nitroform 6.5 6.6 ab Milorganite 7.1 7.1 a Urea 6.8 6.7 ab UFLEXX 6.6 6.6 ab Untreated Control 6 .0 5.5 b Visual color was rated using the NTEP scale which is from 1 to 9 9= optimal turf color, 6 =acceptable turf color. Means w ith the same letter were not significantly different (P = 0.05) according to Tu

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88 CHAPTER 4 CONCLUSIONS Nitrogen source should be chosen with consideration of the potentia l fate and contribution to nonpoint source pollution. In this study N runoff seemed to be a greater threat to eutrophication than N le aching. With greater loads observed from the runoff study than the leaching study greater emphasis needs to be on research and development of best management practices near environmental ly sensitive areas. The solubility of the given N source applied in the forced runoff events proved to be the most influential determination of total soluble nitrogen recovery rate. In this worst case scenario, PCU out performed AS and UF by minimizing TSN levels in runof f waters. Since AS and UF (10 15%) contain a soluble fraction, it may be beneficial to use polymer coated N products when fertilization is required when excess rainfall/irriga tion is known to be imminent and in low maintenance zones surrounding a body of water. Although inconsistent results were found in the first N leaching event, it substantiated previous research claims that immature turf is often more susceptible to N leac hing. In addition to a relatively immature turf stand it was quite evident that a 144 kg N ha 1 fertilization rate coupled with extreme irrigation practices of 25 mm day 1 was not conducive to proper turf management. Even with the intense irrigation and f ertilization regime, TSN leachate in the second event was below the MDL of 1 mg TSN L 1 F uture research needs to be conducted with a wider range of fertilizer sources and unfertilized buffer strip sizes as well as differing soil moisture values and s oil textures. This study was conducted at field capacity with forced runoff without watering

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89 forced immediately following fertilizer application. The significance of this research can be surmised by the understanding that N source and solubility should be chosen under consideration that a potential misapplication could result in nonpoint source pollution via runoff.

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90 APPENDIX A IRRIGATION UNIFORMITY FOR JAY LEACHING STUDY Date Time Distribution Christiansen Wind Speed 5/22/2012 9:45:00 AM 0.8684 0.8015 15 20mph 5/29/2012 11:00:00 AM 0.7571 0.5692 25 30mph 6/14/2012 10:30:00 AM 0.7357 0.5912 10 15mph 6/21/2012 1:00:00 PM 0.7070 0.5342 20mph 6/27/2012 10:00:00 AM 0.7669 0.6234 5mph 7/3/2012 9:00:00 AM 0.7595 0.5855 10 15mph 7/10/2012 NR 0.7941 0.6491 NR 7/17/2012 8:00:00 AM 0.8969 0.8331 0 5 mph 9/4/2012 NR 0.6870 0.5550 NR 9/10/2012 2:05:00 PM 0.7455 0.5910 10mph 9/17/2012 12:00:00 PM 0.6732 0.5010 10 20mph 9/24 /2012 NR 0.7318 0.5561 NR 10/1/2012 NR 0.8323 0.7281 NR 10/8/2012 10:00:00 AM 0.6473 0.4164 20 25mph 10/16/2012 8:10:00 AM 0.7896 0.6749 10mph 11/14/2012 10:00:00 AM 0.8637 0.8163 0 5mph 12/4/2012 NR 0.5823 0.4867 NR 12/19/2012 12:45:00 PM 0.6671 0.5 301 15 25mph 1/14/2013 11:00:00 AM 0.6813 0.5391 10 20mph 1/28/2013 2:30:00 PM 0.7300 0.6245 15 20mph 2/11/2013 11:00:00 AM 0.8322 0.7517 NR 2/25/2013 10:00:00 AM 0.8532 0.7553 0 5mph 3/11/2013 2:00:00 PM 0.8586 0.8065 5 10mph Not recorded (NR)

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91 A PPENDIX B PERCOLATION RATES FOR LEACHING EVENT BY DAYS AFTER TREATMENT Event Two Event Three DAT Perc olation DAT Perc olation cm h 1 cm h 1 1 0.3571 a 1 0.3769 a 2 0.2375 ab 7 0.0292 b 3 0.0340 c 14 0.1217 b 4 0.0965 bc 28 0.0541 b 5 0. 2289 ab 35 0.0686 b 7 0.1935 abc 42 0.2012 b 21 0.0780 bc 49 0.1059 b 28 0.1293 bc 56 0.0805 b 35 0.1537 bc 79 0.0523 b 42 0.1166 bc 93 0.1069 b 49 0.1153 bc 107 0.0660 b 56 0.0846 bc 128 0.1354 b 65 0.0366 c 142 0.1118 b 156 0 .0828 b 170 0.1095 b 184 0.1082 b 198 0.1179 b consists of the lysimeter sampling dates Means w ith the same letter were not significantly different (P = 0.05) according to Tu

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92 LI ST OF REFERENCES Balogh, J.C. and J.L. Anderson. 1992. Environmental impacts of turfgrass pesticides. p 221 353. In J.C. Bal ogh and W.J. Walker (ed.) Golf course management and construction: environmental i ssues. Lewi s Publishing Chelsea, MI. Balogh, J .C. a nd W.J. Walker. 1992. Role and conservation of water resources. p. 39 104. In J.C. Balogh and W.J. Walker (ed.) Golf course management and construction: environmental issues. Lewis Publishing, Chelsea, MI. Barber, S.A. 1995. Soil nutrient bioavailabi lity: a m echan istic a pproach. 2 nd ed. John Wiley & Sons New York. Barton, L., G.G.Y. Wan, and T.D. Colmer. 2006. Turfgrass ( Cynodon dactylon L.) sod production on sandy s oils: II. Effects of irrigation and fertilizer regimes on N l eaching. Plant Soil 28 4:147 164. Beard, J.B. 1973. Turfgrass science and c ult ure. Prentice Hall Publishing New York. Beard, J.B. 1982. Turf management for golf courses. Macmillan Publishing New York. Bell, G.E. and K. Koh. 2011. Nutrient and pesticide losses caused by simul ated rainfall and sprinkler i rrigation. USGA turfgrass and environmental research o nline 10(2):1 10. Blanco Canqui, H., C.J. Gantzer, S.H. Anderson, E.E. Alberts, and A.L. Thompson. 2004. Gras s barrier and vegetative filter strip effectiveness in reducing runoff, sediment, nitrogen, and phosphorus l oss. Soil Sci. Soc: Am. J. 68:1670 1678. Bowman, D .C., C.T. Cherney, and T.W. Rufty Jr. 2002. Fate and transport of nitrogen applied to six w arm seas on t urfgrasses. Crop Sci. 42:833 841. Brady, N.C. and R.R. We il. 2008. The nature and properties of s oils, 14th ed. Prentice Hall Publishing New York. Brown, K. W., R.L. Duble, and J.C. Thomas. 1977. Influence of management and season on fate of N applied to golf courses. Agron. J 69(4):667 671. Brown, K. W., J. C Thomas, and R.L. Duble. 1982. Nitrogen source effect on nitrate and ammonium l e aching and runoff losses from g reens. Agron. J. 74:947 950. Burton, G.W. 1960. Tifway (Tifton 419) b ermudagrass (Reg. No. 7). Crop Sci. 6:93 94. Chen, Z.H L.J. Chen, Z.J. Wu Y.L. Zhang and Y.H. Juan. 2007. Ammonia volatilization from rice field under different water conditions in low Liaohe river p lain. J. Appl. Ecol. 12:2771 2776

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94 Dodds, W.K. 2006. Nutr dissolved o xygen in the Northern Gulf of Mexico. Frontiers in Ecology and the Environment 4 :211 217. Easton, Z.M., A.M. Petrovic, D.J. Lisk, and I.M. L arsson Kovach. 20 05. Hillslope position effect on nutrient and pesticide runoff from t urfgrass. Int. Turfgrass Soc. Res. J. 10:121 129. Engelsjord, M.E. an d B.R. Singh. 1997. Effects of slow release fertilizers on growth and on uptake and l eaching o f nutrients in Kentuck y bluegrass turfs established on sand based root z ones. Can. J. Plant Sci. 77:433 444. Enloe, J. 2013a. Florida Climate Division 1 Time Series. NOAA National Climatic Data Center Available at http://ncdc.noaa.gov/temp and precip/time series/ (Verified 10 Mar 2013 ) Enloe, J. 2013b. Florida Climate Division 2 Time Series. NOAA National Climatic Data Center Available at http://nc dc.noaa.gov/temp and precip/time series/ (Verified 10 Mar 2013 ) Erickson, J.E., J.L. Cisar, G.H. Snyder, D.M. Park, and K.E. Williams. 2008. Does a mixed species landscape reduce inorganic N leaching following establishme nt compared to a conventional st. a ugustinegrass l awn? Crop Sci. 48:1586 1594. Erickson, J. E., J.L. Cisar, G.H. Snyder, J.C. Volin, and D.M. Park. 2005. Phosp horus and potassium leaching under contrasting residential landscape models established on a sandy s oil. Crop Sci. 45(2):546 552. Erickson, J.E., J.L. Cisar, J.C. Volin, an d G.H. Snyder. 2001. Comparing nitrogen runoff and leaching between newly e stablishe d st. a ugustinegrass turf and an alternative residential l andscape. Crop Sci. 41:1889 1895. Erickson, J.E., D.M. Park, J.L. Cisar G.H. Snyder, and A.L. Wright. 2010. Effects on sod type, irrigation, and fertilization on nitrate nitrogen and orthophosphate phosphorus l eaching from newly established st. a ugustinegrass s od. Crop Sci. 50:1030 1036. The Fertilizer Institute. 2012. Enha nced Efficiency Fertilizers. Available at http://www.tfi.org/ (Verified 24 Oct. 2012) FDEP 2004. FDEP SOP sampling training for groundwater, surface water, and w astewater. SOP 001/01. Sec. 2. FD 5000, Sec. 3. FQ 1214 an d 1220, Sec. 5. FC 1190, Sec. 6. FS 1000, Sec. 8. FS 2100.

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98 Peacock, C.H., M.M. Smart, an d W. Warren Hicks. 1996. Best management practices and integrated pest manage ment strategies for protection of natural resources on golf course w ate rsheds. p. 335 338. Watershed Proc. 96th Baltimore MD. 8 12 June 1996. Petrovic, A.M. 1990. The fate of nitrogenous fertilizers applied to t urfgrass. J. Environ. Qual. 19:1 14. Petro vic, A. M. 2004. Nitrogen source and timing impact on nitrate leaching from t urf. Acta Horticulturae 661:427 432. Petrovic, A.M., N.W. Hummel, a nd M.J. Carrol. 1986. Nitrogen source effects on nitrate leaching from late fall nitrogen applied to t urfgrass. p.137. In 1986 Agronomy abstracts. ASA, Madison, WI. Pratt, P.F. 1985. Agricultural a nd groundwater quality. p. 62. Council for Agric. Sci. and Tech Cast Rep. No. 103. Ames, IA. Rice, P. and B.P. Horga n. 2010. Nutrient loss in runoff from turf: effect on surface water quality. USGA turfgrass and environmental research o nline 9(1):1 10. Rieke, P.E. an d B.G. Eliis. 1974. Effects of nitrogen fertilization on nitrate movement under t urfgrass. p. 120 130. In E.C. Roberts (ed.) Proc. 2 nd Int. Turfgrass Res Conf. ASA, Madison, WI. 19 21 June 1972. Blacksburg, VA. Roger, P.A., W.J. Zimm erman, and T.A. Lumpkin. 1993. Microbiological management of wetland rice f ields. I n B. Metting (ed .) Soil microbial t echnologies, p 417 455. Marcel Decker New York. Rosen, C.J. and B. P. Horgan. 2005. Regulation of phosphorus fertilizer a pplic ation in Minnesota: Historical perspective and opportunities for research and e ducation. Int. Turf Res. J. 10:130 135. S artain, J.B. 2010. Comparative influences of N source on leachi ng of N and st. augstinegrass q u ality, g rowth and N uptake. Soil Crop Sci. Soc., Florida Proc. 69. Sartain, J.B., and J.K. Kruse. 2001. Selected fertilizers used in turfgrass f ertilization. Inst. of Food and Agric. Sci. CIR. 1262. Univ. of Florida, Gainesv ille. Sartain, J.B., G.L. Miller, G.H. Snyder, J.L. Cisar, an d J.B. Unruh. 1999. Fertilizer programs. p 65 94. In J.B. Unru h and M.L. Elliot (2 ed.) Best management practices for Florida golf c ourse s. Inst. of Food and Agric. Sci., Univ. of Florida, Gaine sville. SAS Institute. 2008. The SAS System for Windows: Release 9.2.1 SAS Inst., Cary, NC.

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101 BIOGRAPHICAL SKETCH Ryan Adams received his M .S. degree under the direction of Dr. J. Bryan Unruh and Dr. Jason Kruse in August 2013 His work focused on nutrient management of bermudagrass fai rways surrounding environmentally sensitive areas. Mr. Adams received his B.S degree in 2010 from Iowa State University, Ames, IA. During his tenure at Iowa State University, Ryan interned at Pinehurst Resort in Pinehurst, NC, Shoal Creek Country Club in Shoal Creek, Alabama and with the United States Golf Association Green Section. He has also worked at the Iow a State University Research Farm, Ames, IA and at Charlotte Country Club in Charlotte, NC.