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Utilizing In-Situ Benthic Mesocosms to Quantify Phosphorus and Nitrogen Fluxes in South Florida Agricultural Canals

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Title:
Utilizing In-Situ Benthic Mesocosms to Quantify Phosphorus and Nitrogen Fluxes in South Florida Agricultural Canals
Creator:
COLLINS, STEVEN DOUGLAS
Copyright Date:
2008

Subjects

Subjects / Keywords:
Ditches ( jstor )
Kinetics ( jstor )
Modeling ( jstor )
Nutrients ( jstor )
Parametric models ( jstor )
Phosphorus ( jstor )
Sediments ( jstor )
Soils ( jstor )
Sorption ( jstor )
Statistical models ( jstor )
Lake Okeechobee ( local )

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Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright Steven Douglas Collins. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Embargo Date:
2/28/2006
Resource Identifier:
495636960 ( OCLC )

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UTILIZING IN-SITU BENTHIC MESOCOSMS TO QUANTIFY PHOSPHORUS AND NITROGEN FLUXES IN SOUTH FL ORIDA AGRICULTURAL CANALS By STEVEN DOUGLAS COLLINS A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ENGINEERING UNIVERSITY OF FLORIDA 2005

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Copyright 2005 by Steven Douglas Collins

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To my wife, Annie, for all of her love and support

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ACKNOWLEDGMENTS I would like to thank my advisor, Sanjay Shukla, and my committee, Ken Campbell and Ramesh Reddy, for their guidance and insight. I am grateful to Christy Sackfield and Vibhuti Pandey for assisting me with field work and for not complaining too loudly while working in the ditches late into the night. I appreciate the help of the following people for providing insight and helping to construct and install mesocosms: Roger McGill, Bob Tonkinson, Dale Hardin, Ann Summeralls, Mark Clark, Ralph Hoffman, Billy Duckworth, and Gary Barfield. I would also like to thank Yu Wang, Gavin Wilson, Ed Dunne, Atanu Mukherjee, Chris Martinez, and Jaehyun Cho for helping with sediment and water analysis. This research was made possible by funding from the Florida Department of Agriculture and Consumer Services, the South Florida Water Management District, and the Florida Department of Environmental Protection. I am eternally grateful to my friends and family who have provided me with the most important things in life: love and laughter. iv

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TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................iv LIST OF TABLES .............................................................................................................ix LIST OF FIGURES ...........................................................................................................xi ABSTRACT .....................................................................................................................xiv CHAPTER 1 INTRODUCTION........................................................................................................1 2 LITERATURE REVIEW.............................................................................................4 Regional Background...................................................................................................4 Landuse..................................................................................................................6 Soils.......................................................................................................................8 Hydrology..............................................................................................................9 Best Management Practices.................................................................................10 Phosphorus..................................................................................................................11 Pollution..............................................................................................................11 Phosphorus Forms...............................................................................................12 Phosphorus Cycling.............................................................................................13 Mineralization..............................................................................................13 Sorption........................................................................................................14 Desorption....................................................................................................15 Movement............................................................................................................16 Factors Affecting Phosphorus Uptake and Release.............................................17 Abiotic factors..............................................................................................17 Biotic factors................................................................................................22 Methods of Phosphorus Flux Measurement........................................................25 Monitoring: Mass balance............................................................................25 Stream-scale nutrient addition experiments.................................................25 Batch incubation: Isotherm tests.................................................................27 Laboratory intact sediment cores.................................................................28 In-situ benthic mesocosms...........................................................................30 Porewater profiles........................................................................................32 v

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Phosphorus Modeling.................................................................................................32 Net P Flux............................................................................................................33 Calculations..................................................................................................33 Net P flux models.........................................................................................35 Kinetic P flux...............................................................................................37 Weather driven models.................................................................................42 Sorption Indices...................................................................................................44 Sorption maximum.......................................................................................44 Dutch saturation index.................................................................................44 Free Al and Fe..............................................................................................45 Nitrogen......................................................................................................................45 Nitrogen Cycle.....................................................................................................45 Mineralization......................................................................................................46 Nitrification.........................................................................................................46 Denitrification......................................................................................................47 Adsorption and Desorption..................................................................................47 Volatilization.......................................................................................................48 Biotic Uptake.......................................................................................................48 3 MATERIALS AND METHODS...............................................................................49 Site Description..........................................................................................................49 Location...............................................................................................................49 Ranch Description...............................................................................................49 Ranch Best Management Practices (BMPs)........................................................51 Study Site Description.........................................................................................51 Site Soils..............................................................................................................52 Ditch Vegetation..................................................................................................56 Ditch Cleaning.....................................................................................................56 Weather Conditions during the Study Period......................................................57 Field Preparation.........................................................................................................57 Mesocosm Preparation........................................................................................58 Installation...........................................................................................................58 Nutrient Additions...............................................................................................59 Dilution................................................................................................................60 Tracer Addition...................................................................................................62 Sampling..............................................................................................................62 Site Characterization...........................................................................................63 Laboratory Analyses...................................................................................................63 Water Quality Analysis.......................................................................................63 Water total phosphorus (TP)........................................................................63 Water soluble reactive phosphorus (SRP)....................................................64 Total Kjeldahl nitrogen (TKN)....................................................................64 Ammonium (NH 4 ) and nitrate and nitrite (NO 3 +NO 2 )................................64 pH.................................................................................................................64 Bromide........................................................................................................64 vi

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Sediment Analysis...............................................................................................66 Moisture content and bulk density...............................................................66 pH.................................................................................................................66 Organic matter (LOI)...................................................................................66 Total phosphorus (TP)..................................................................................66 Water-extractable phosphorus......................................................................67 Oxalate-extractable iron, aluminum, and phosphorus..................................67 Biomass Analysis................................................................................................67 Data Adjustment.........................................................................................................68 Evapotranspiration...............................................................................................69 Dilution from outside the Volume Enclosed by the Mesocosm..........................70 Water Loss...........................................................................................................72 4 RESULTS...................................................................................................................75 Measurements.............................................................................................................75 Effectiveness of Mesocosm.................................................................................75 Phosphorus Uptake and Release..........................................................................78 Phosphorus uptake over time.......................................................................78 Phosphorus release over time.......................................................................82 Uptake and release over time relative to initial concentrations....................87 Sediment characteristics...............................................................................90 Sorption indices............................................................................................92 Biomass measurements................................................................................95 Nitrogen Results..................................................................................................95 Simulation...................................................................................................................98 Modeling Net P Flux after 7 Days.......................................................................98 Site 4.............................................................................................................99 Site 5...........................................................................................................101 Kinetic P Flux Modeling...................................................................................103 Site 4...........................................................................................................104 Site 5...........................................................................................................110 Kinetic modeling of dilution treatments.....................................................114 Modeling Summary...........................................................................................117 5 SUMMARY AND CONCLUSION.........................................................................121 Summary...................................................................................................................121 Phosphorus Retention........................................................................................121 Phosphorus Release...........................................................................................122 Phosphorus Modeling........................................................................................123 Nitrogen.............................................................................................................124 Conclusion................................................................................................................125 APPENDIX: CHOICE OF CONSERVATIVE TRACER.............................................128 vii

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LIST OF REFERENCES.................................................................................................131 BIOGRAPHICAL SKETCH...........................................................................................149 viii

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LIST OF TABLES Table page 2-1 Phosphorus sorption characteristics for stream sediments and wetland soils in the S-154 basin.........................................................................................................29 2-2 Diffusion coefficient used with Fick’s First Law varies with solute and sediment type............................................................................................................34 3-1 Six soil series are present on the ranch and in the ditch drainage basins.................53 3-2 Average stream sediment and wetland soil properties from 10 streams and 20 wetlands in the S-154 sub-basin compared to results from the current study site ditches................................................................................................................54 3-3 Stream sediment and wetland soil phosphorus partitions for Dry Lake Dairy, located in the S-154 sub-basin.................................................................................56 3-4 Summary of P spike treatments at the two drainage ditches....................................58 3-5 Summary of dilution treatments at the two drainage ditches...................................58 3-6 Measured daily evapotranspiration at the ONA weather station..............................69 4-1 Net uptake for all spike treatments and controls......................................................79 4-2 Net uptake / release for all dilution treatments.........................................................83 4-3 Drainage ditch sediment characteristics for Sites 4 and 5........................................92 4-4 Average biomass above the sediment surface within each mesocosm at Site 4......95 4-5 Units for the model parameters used for net P flux analysis....................................99 4-6 Net P flux at Site 4: Best-fit parameters and goodness of fit for six models fit to net P flux data.....................................................................................................100 4-7 Net P flux at Site 5: Best-fit parameters and goodness of fit for six models fit to net P flux data.....................................................................................................102 ix

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4-8 Kinetic P sorption modeling at Site 4 (high spike): Best-fit parameters and goodness of fit statistics for four kinetic models fitted to the P sorption data from the high P spike treatment at Site 4...............................................................106 4-9 Kinetic P load modeling at Site 4 (high spike): Best-fit parameters and goodness of fit statistics for three kinetic models fit to observed P load data from the high P spike treatment at Site 4...............................................................106 4-10 Kinetic P sorption modeling at Site 4 (low spike): Best-fit parameters and goodness of fit statistics for four kinetic models fitted to the P sorption data from the low P spike treatment at Site 4................................................................108 4-11 Kinetic P load modeling at Site 4 (low spike): Best-fit parameters and goodness of fit statistics for three kinetic models fit to observed P load data from the low P spike treatment at Site 4................................................................109 4-12 Kinetic P sorption modeling at Site 5 (high spike): Best-fit parameters and goodness of fit statistics for four kinetic models fitted to the P sorption data from the high P spike treatment at Site 5...............................................................111 4-13 Kinetic P load modeling at Site 5 (high spike): Best-fit parameters and goodness of fit statistics for three kinetic models fit to observed P load data from the high P spike treatment at Site 5...............................................................111 4-14 Kinetic P sorption modeling at Site 5 (low spike): Best-fit parameters and goodness of fit statistics for four kinetic models fitted to the P sorption data from the low P spike treatment at Site 5................................................................113 4-15 Kinetic P load modeling at Site 5 (low spike): Best-fit parameters and goodness of fit statistics for three kinetic models fit to observed P load data from the low P spike treatment at Site 5................................................................114 4-16 Boundary layer model applied to high and low dilution treatment data sets at Site 4 and 5: Best-fit parameters and goodness of fit............................................115 4-17 R 2 coefficients for the tested models. Average values between high and low P spike treatments are shown.................................................................................118 x

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LIST OF FIGURES Figure page 2-1 Lake Okeechobee watershed......................................................................................4 3-1 Lake Okeechobee Basin and contributing sub-watersheds......................................50 3-2 Photos of study ditches on the Pelaez & Sons Ranch..............................................51 3-3 Map of Pelaez & Sons Ranch including study site drainage basins, drainage ditches, and grassed swales......................................................................................52 3-4 Pastures and planted forage grasses on the Pelaez & Sons Ranch...........................53 3-5 Soils located within the Pelaez & Sons Ranch and the study drainage ditch basins........................................................................................................................54 3-6 Mesocosms after being prepared for installation.....................................................59 3-7 Mesocosm locations at the two study ditches (top, Site 4 and bottom, Site 5)........60 3-8 Process used to dilute the water inside the mesocosms...........................................61 3-9 Water sample bromide response using a Dionex RFIC Ion-Pac AS4A-SC column......................................................................................................................65 3-10 Example of nutrient loads corrected for ET, dilution from outside the volume enclosed by the mesocosm, and water loss (Site 4 high spike treatment). The effects of these three processes can be removed since the relative contribution of each is known.......................................................................................................68 3-11 Comparison of measured bromide concentrations and those expected to occur from ET losses at Site 5............................................................................................70 3-12 Comparison of measured bromide concentrations and those expected to occur from ET losses at Site 4. Dilution from water outside the mesocosm is evident......................................................................................................................71 3-13 Effects of evapotranspiration and dilution can be removed from the measured nutrient data since the relative contribution of each is known (Site 4 high spike treatment)........................................................................................................73 xi

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3-14 Water level inside each mesocosm dropped steadily with time...............................73 4-1 SRP measured in control mesocosms at Site 4 resembled SRP measured from ambient ditch water. The variability in ambient water samples may be an indication of variable conditions within the ditch....................................................76 4-2 SRP measured in control mesocosms at Site 5 resembled SRP measured from ambient ditch water. The water depth may have been greater at the ambient water sampling locations than the control mesocosms............................................77 4-3 TKN measured in control mesocosms at Site 4 resembled TKN measured from ambient ditch water, supporting the notion that the mesocosms were effective....................................................................................................................77 4-4 TKN measured in control mesocosms at Site 5 resembled TKN measured from ambient ditch water.........................................................................................78 4-5 High nutrient spike and experimental control phosphorus loads over the course of the experiment at Site 4............................................................................80 4-6 Low nutrient spike and experimental control phosphorus loads over the course of the experiment at Site 4............................................................................80 4-7 High and low nutrient spike and experimental control phosphorus loads over the course of the experiment at Site 5......................................................................81 4-8 Phosphorus release over time observed at Site 4 after ~50% dilution.....................84 4-9 Phosphorus release over time observed at Site 4 after ~75% dilution.....................85 4-10 Phosphorus release over time observed at Site 5 after ~50% dilution.....................85 4-11 Phosphorus release over time observed at Site 5 after ~75% dilution.....................86 4-12 Measured loads at Site 4 from both nutrient spike treatments and the experimental control relative to each initial condition.............................................88 4-13 Measured loads at Site 5 from both nutrient spike treatments and the experimental control relative to each initial condition.............................................89 4-14 Measured loads at Site 4 from both dilution treatments and the experimental control relative to each initial condition...................................................................89 4-15 Measured loads at Site 5 from both dilution treatments and the experimental control relative to each initial condition...................................................................90 4-16 Soil cores. A) Site 4. B) Site 5...............................................................................91 xii

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4-17 High and low nutrient spike and experimental control ammonium loads over the course of the experiment at Site 4......................................................................96 4-18 High and low nutrient spike and experimental control ammonium loads over the course of the experiment at Site 5......................................................................97 4-19 Data and fitted models comparing net P flux to initial SRP concentration at Site 4.......................................................................................................................101 4-20 Data and fitted models comparing net P flux to initial SRP concentration at Site 5.......................................................................................................................102 4-21 Kinetic P sorption modeling at Site 4 (high spike): Cumulative observed and predicted phosphorus sorption using five kinetic models......................................106 4-22 Kinetic P load modeling at Site 4 (high spike): Decline in observed and predicted phosphorus load using three kinetic models...........................................107 4-23 Kinetic P sorption modeling at Site 4 (low spike): Cumulative observed and predicted phosphorus sorption using five kinetic models......................................108 4-24 Kinetic P load modeling at Site 4 (low spike): Decline in observed and predicted phosphorus load using three kinetic models...........................................109 4-25 Kinetic P sorption modeling at Site 5 (high spike): Cumulative observed and predicted phosphorus sorption using five kinetic models......................................111 4-26 Kinetic P load modeling at Site 5 (high spike): Decline in observed and predicted phosphorus load using three kinetic models...........................................112 4-27 Kinetic P sorption modeling at Site 5 (low spike): Cumulative observed and predicted phosphorus sorption using five kinetic models......................................113 4-28 Kinetic P load modeling at Site 5 (low spike): Decline in observed and predicted phosphorus load using three kinetic models...........................................114 4-29 Cumulative phosphorus releases observed and predicted using the boundary layer model.............................................................................................................115 xiii

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Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Engineering UTILIZING IN-SITU BENTHIC MESOCOSMS TO QUANTIFY PHOSPHORUS AND NITROGEN FLUXES IN SOUTH FLORIDA AGRICULTURAL CANALS By Steven Douglas Collins August 2005 Chair: Sanjay Shukla Cochair: Kenneth Campbell Major Department: Agricultural and Biological Engineering Improved pastures in the Lake Okeechobee Basin, Florida contain extensive surface drainage networks. The water and nutrients they transport eventually discharges to Lake Okeechobee. In addition to facilitating drainage for agricultural production, these drainage networks provide a means to reduce phosphorus (P) loading from pastures through biological and chemical retention. The effect of storing water in drainage ditches under varying runoff P concentrations was investigated using in-situ benthic mesocosms. Nutrient concentrations of the water inside the mesocosms were altered to promote P flux across the sediment-water interface. Four treatments (representing four P concentrations levels) were tested in triplicate across two drainage ditches on a 620 ha commercial cattle ranch. Nutrient concentrations in the water-column were monitored over 7 days. Ammonium-N was added when Phosphate-P was added, to maintain the N:P ratio. Both nitrogen (N) and P were monitored, though results indicated that N transformation processes could not be identified conclusively. xiv

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Results indicate that drainage ditch sediments possess a high P-retention capacity, closely related to sediment aluminum and iron contents. Soluble reactive phosphorus (SRP) retention over 7 days varied from 13 to 55% of the starting water-column concentration. Results indicated that P uptake is greater and releases more rapidly in drainage ditches with organic sediment and emergent macrophytes compared to ditches with mostly mineral sediment and without macrophytes. Phosphorus retention over time is rate-limited by diffusion and sediment porewater exchange. The applicability of five kinetic models and six net P flux models was tested with the data. Using those models that best represented the data, empirical models were derived to predict P retention based on known water-column SRP concentrations and hydraulic residence times. Results show that retaining ditch water for at least 4 days can be an effective BMP for reducing net discharge of P from cow-calf operations. xv

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CHAPTER 1 INTRODUCTION In Lake Okeechobee, FL, inorganic phosphorus (P) is the most limiting nutrient, thus regulating primary productivity (Steinman and Rosen, 2000). Agricultural operations in the Lake Okeechobee basin, which supply P to the lake, have resulted in accelerated eutrophication of the lake. To alleviate further degradation of the lake, the Florida Department of Environmental Protection developed a Total Maximum Daily Load (TMDL) in 2000 limiting the incoming P load to 198 T year -1 . Cow-calf operations encompass 38.7% of the area of the basin, and fertilizer for improved pasture contributes nearly 60% of the annual net P imports (Boggess et al., 1995). Several best management practices (BMPs) including cattle, field, and feed manipulation have been used to reduce P loading from the basin. Storing water on site may reduce P loading because of decreased runoff volume and increased P retention. Almost all agricultural operations in the region (including the cow-calf ranches) have a long network of drainage ditches. These ditches offer considerable capacity for storing runoff from pastures. Although storing water in ditches may reduce net nitrogen (N) and P discharge from cow-calf operations, insufficient data are available to determine the extent of N and P reduction from this practice. The capacity of drainage ditches in the Lake Okeechobee basin to retain or release P is not well understood. Drainage ditches may function as a sink, source, or regulator of dissolved P concentrations, and their role can only be determined by gaining an understanding of the nutrient dynamics between ditch sediment and water. Quantifying 1

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2 the retention/release potential of these ubiquitous systems is vital for future land and water management and meeting the TMDL for Lake Okeechobee. While soil retention of P has been studied in the region, most studies have involved laboratory experiments. Laboratory studies have limited application, since the experimental conditions do not represent the system. It is common practice to determine the maximum P-retention potential by mixing sediment samples with nutrient solutions, and measuring the P-concentration change in solution. However, the degree of contact between sediment particles and solution is not representative of field conditions. Other researchers have brought intact sediment cores to the laboratory, changing floodwater P concentrations while keeping other variables constant (Reddy et al., 1996b; Nguyen and Sukias, 2002), but these experiments usually underestimate actual retention occurring under field conditions (Reddy et al., 1995). Laboratory measurement techniques cannot incorporate the field hydrologic and redox fluctuations nor include the effects of bioturbation caused by benthic macrofauna (Fisher and Reddy, 2001). Additionally, removing sediment cores from the channels for laboratory studies may disturb the sediments and alter the P-retention capacity. Stream-scale experiments involving coupled nutrient and conservative tracer additions (Triska et al., 1989b; Stream Solute Workshop, 1990) have the advantage of quantifying whole aquatic systems; incorporating sediment sorption, advection, diffusion, groundwater influences, and biotic effects. However, stream-scale manipulation experiments are unreplicatable (Hurlbert, 1984) and cannot simultaneously characterize water and nutrient dynamics over a range of nutrient concentrations (Triska et al., 1989b). Most importantly, nutrient retention estimates will be unreliable if exchange timescales

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3 are too long (Wagner and Harvey, 1997), as is the case for south Florida drainage ditches where flow is ephemeral. To better understand N and P retention capacities, analyses should be conducted in-situ. Measuring nutrient fluxes in the field has several advantages over the laboratory intact sediment column approach. Variables such as water, air, and sediment temperature, photoperiod, dissolved-oxygen, pH, dissolved chemical constituents in the water-column, benthic organisms, and plant and microbial communities will be representative of true field conditions in the in-situ approach. Additionally, by conducting the analysis in-situ, the system will undergo less disturbance than if the sediment were transported to the laboratory. My study extends the sediment-core approach by leaving the sediment in place under natural conditions, and is conducted over a larger area. Error caused by differences in advective transport for the mesocosm studies are likely to be small, since flow in Lake Okeechobee drainage ditches is extremely slow (Heatwole et al., 1987). In my study, N was added and monitored to ensure that the natural N:P ratio was maintained. Objectives. The goal of my study was to measure in-situ N and P retention in two drainage ditches in south Florida. Specific objectives of my study are To design an in-situ benthic mesocosm for measuring N and P retention of the drainage ditches. To quantify short-term nutrient fluxes (N and P) resulting from changes in the solute concentration of the overlying water, and hence assess the potential for drainage ditches at a commercial cattle ranch to be P sources or sinks.

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CHAPTER 2 LITERATURE REVIEW Regional Background Lake Okeechobee spans 1760 km 2 at a mean water level of 4 m above mean sea level. It contains habitat for a diverse array of species, including the federally endangered Snail Kite (Rostrhamus sociabilis). The lake supports large commercial and recreational fisheries in addition to supplying water to urban and agricultural sectors, and recharging aquifers. The Lake Okeechobee watershed spans 12,000 km 2 (Figure 2-1), with elevations ranging from 4 to 23 m above sea level. Figure 2-1 Lake Okeechobee watershed 4

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5 Agricultural operations in the Lake Okeechobee watershed have resulted in accelerated eutrophication of the lake. Eutrophication is an increase in the primary productivity of natural waters, manifested by excessive algae and aquatic plant growth. Algae generally require elements in fixed proportions to grow and reproduce, and most of these elements are abundant in freshwater ecosystems. Inorganic phosphorus (P), as in Lake Okeechobee, is the most limiting nutrient, thus regulating primary productivity (Steinman and Rosen, 2000). Lake Okeechobee received national press in 1986, when an algal bloom covering 310 km 2 was observed on the lake. Once the algae senesced, low dissolved-oxygen and high ammonia concentrations resulted in large-scale fish and invertebrate kills. In addition to fish kills, eutrophication of surface waters also can be detrimental to drinking-water supplies. Some algae and actinomycetes release organic compounds that cause drinking water to have a displeasing odor and taste (Sivonen, 1982). To reduce the eutrophication effects in the lake, a target P load of 397 T year -1 was established (South Florida Water Management District, 1989). In 2000, the Florida Department of Environmental Protection developed a TMDL for Lake Okeechobee reducing the target P load to 198 T year -1 , aiming for an in-lake P concentration of 40 g l -1 . It is hoped that reducing the external loading to Lake Okeechobee will inhibit further eutrophication. However, Moore et al. (1998) determined that internal P loading, through the release of P from bottom sediments, is roughly equivalent to external loading. Such high internal loading suggests that reducing outside sources of P may not result in decreased P concentrations in the lake.

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6 Landuse Runoff and leaching from pastures, the dominant landuse in the region, and dairies comprise most of the P loading to the lake. The watershed contains 190,000 ha improved pasture and 135,000 ha unimproved pasture supporting approximately 180,000 beef cattle (Flaig and Havens, 1995). Boggess et al. (1995) reported that 1,500 tons P year -1 , or nearly 60% of the net P imports to the Lake Okeechobee basin were from fertilizer for improved pastures. Improved pastures represent 38.7% of the area of the basin (Boggess et al., 1995). Runoff of soluble P fertilizer applied to improved bahiagrass (Paspalum notatum) pastures contributes to Lake Okeechobee eutrophication (Rechcigl and Bottcher, 1995). Higher cattle densities entail greater fertilizer and feed applications, and leachable P from dairies and pastures has been shown to increase with cattle density (Graetz and Nair, 1995). In a separate study, Steinman et al. (2003) found that cattle density had little impact on water-column nutrient concentrations in wetlands. The three most significant P imports in the basin are fertilizer for improved pastures, feed for dairy animals and rainfall. The average runoff P concentration from improved pastures and dairies in the basin ranges from 0.5 to 3.5 mg P l -1 (Haan, 1995). The runoff, containing P from both fertilizer and cattle manure, is transported downstream to Lake Okeechobee (South Florida Water Management District, 1997). Since accurately measuring flow can be difficult and expensive, the South Florida Water Management District chose to enact a limit on the runoff P concentration dependent on landuse instead of a limited P load (1989). A numeric P concentration limit for runoff from non-dairy land uses was established through a regulatory program called the Works of the District (Chapter 40E

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7 61 FAC) (Harvey and Havens, 1999). For permitted improved pastures, the limit in runoff is a TP concentration of 0.35 mg l -1 . The limit was based on water quality data collected in the 1980s. Gornak and Zhang (1999) conducted a survey of 69 surface water quality monitoring sites across 32 beef cattle ranches in the northern part of the basin. Using average data from 1989 to 1996, the researchers found that 46% of the surveyed sites were in compliance with the 0.35 mg l -1 limit. When averaging only the data points from 1996, 61% of the study sites were found to be in compliance. This indicates that the water quality of runoff may be improving from beef cattle ranches in the region. Among the contributing watersheds for the basin, the Taylor Creek-Nubbin Slough sub-watershed contributes the highest P load (29% of the load to the lake), but only contributes 4% of the water. The location of the Taylor Creek-Nubbin Slough watershed is shown in Figure 3-1. In 1982, most of the P runoff and leaching in this watershed originated from dairies, though 23% was attributed to beef cattle pastures (Allen, Jr. et al., 1982). The South Florida Water Management District reported that a 90% loading reduction from the Taylor Creek-Nubbin Slough watershed is necessary to inhibit further eutrophication in Lake Okeechobee (Rechcigl and Bottcher, 1995). Best management practice (BMP) implementation in this watershed has reduced P loads such that the Lower Kissimmee River watershed is now the leading contributor of P to Lake Okeechobee (Flaig and Reddy, 1995). Enhanced use of wetlands, natural streams and canals is one means to reduce P loads. By conducting an estimated P budget for the period 1985, Boggess et al. (1995) were able to determine that streams and wetlands in the Lake Okeechobee basin retained 60% of incoming P. Whereas both stream sediments and wetland soils have

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8 considerable long-term P retention capacities (Flaig and Reddy, 1995), the capacities of wetland soils are typically greater (Reddy et al., 1995). Nevertheless, since flow is restricted to streams and ditches on most ranches, these systems function to retain more P than wetlands in this region (Reddy et al., 1995). Soils The Kissimmee River Basin Region (KRBR), an area described in Campbell et al. (1995), consists of the Lower Kissimmee River watershed and the Taylor Creek-Nubbin Slough watershed among others. The KRBR, like all of the Lake Okeechobee Basin and most of south Florida, is characterized by flat, sandy, high-water-table soils. A subsurface horizon consisting of amorphous organic matter, aluminum, and iron oxides distinguish these flatwoods soils (or Spodosols) from other soil orders. These spodic horizons occur at varying depths ranging from 0.5 m to greater than 2 m. The principal soil associations in the Lower Kissimmee River and Taylor Creek-Nubbin Slough watersheds are Myakka-Immokalee-Waveland and Wabasso-Felda-Pompano (Campbell et al., 1995). The clay content of these soils is very low, restricting the P adsorption capacity. Typically, soil solution P concentration is not high. However, the low clay content of these soils causes P concentrations in soil water and runoff to become significant (Haan, 1995). Through isotherm experiments, Graetz and Nair (1995) found that P desorbed from the surface horizon of Spodosols in the Okeechobee basin under all tested concentrations (0 through 100 mg P l -1 ). Spodosol surface soils have an extremely limited ability to retain P. For B horizons, the researchers were able to determine that the trend in maximum P sorption and P bonding energy related to soil series was Myakka

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9 Immokalee Pomello. The P-sorption capacity for a Myakka soil from a beef pasture was 240 mg P kg -1 . Oxalate-extractable Al accounts for most of the variability in P sorption maximum (Nair et al., 1998). Oxalate extraction is a laboratory process where a reagent containing ammonium oxalate and oxalic acid is used to strip metals and nutrients from sediments or soils. Even though the lower spodic (Bh) horizons contain a relatively high Al content, they are limited in their ability to remove soluble P due to restricted deep percolation into these layers (Allen, 1988). Hydrology Rainfall in the Lake Okeechobee watershed averages 120 cm year -1 with a pronounced summer wet season and winter dry season. In the summer wet season, the water table may be within 1 m of the ground surface, and in the winter dry season, the water table may retreat to 2 m below the ground surface (Knisel et al., 1985). Extensive ditch networks are necessary for drainage in this region despite high soil hydraulic conductivity (>16 cm h -1 ) (Campbell et al., 1995). The ubiquitous ditches and low topological relief make it difficult to determine watershed boundaries and flow direction. As opposed to topology, flow direction in ditches actually may be more dependent on wind, storm type, or the depth of water in the ditch (Haan, 1995). Artificial drainage facilitates subsurface lateral movement of water and may expedite lateral P transport (Graetz and Nair, 1995). Flow from agricultural drainage ditches is routed through a network of small and primary canals with gated control structures before it is discharged into Lake Okeechobee (Reddy et al., 1996a). Sedimentation is insignificant in the region due to a lack of inorganic sediment (Flaig and Reddy, 1995). Additionally, extremely small slopes generate little to no erosion after rainfall events. Indeed, overland flow is only significant in this region when

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10 the water table reaches the surface. Once the water table reaches the surface, overland flow can quickly transport P to receiving water bodies (Campbell et al., 1995; Graetz and Nair, 1995). The extent of P loadings through surface runoff in the watershed varies with the intensity of pasture management. Surface runoff P in the region ranges from 0.7 kg P ha -1 year -1 to 27 kg P ha -1 year -1 , for low-intensity and high-intensity pastures respectively (Campbell et al., 1995). To achieve a reduction in the total P loading to Lake Okeechobee, all sources contributing runoff P need to be curtailed, especially P runoff hotspots (i.e. 27 kg P ha -1 year -1 ). Phosphorus load reduction can be achieved through BMPs. Best Management Practices Best Management Practices (BMPs) are attempts to reduce downstream nutrient losses through controlled land activities, while ensuring the financially viable operation of property-owners (Bottcher et al., 1995). In 1987, the Florida Legislature created the Surface Water Improvement and Management program (SWIM) to address non-point pollutant sources. To achieve compliance with SWIM, which limits P concentration in discharge from ranches (South Florida Water Management District, 1989), beef cattle ranchers have tried several BMPs. These management strategies have included cattle, field, and feed manipulation. By reducing the stocking rate of a field, less manure is deposited per unit area. Long-term manure applications can result in the leaching of P into groundwater in areas with shallow water tables or coarse-textured soils (Eghball et al., 1996). Rotating grazing areas or periodically moving feeders and water troughs prevents the overuse of a particular area by cattle. Otherwise the capacity of the soil to retain nutrients could be exceeded in certain areas. To reduce the P loadings from the ranches, the forage grass type could be changed to a species that retains P within the field

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11 until the plant senesces or is consumed. Lastly, reducing the P input by limiting supplemental feed or fertilizer on pasture can also help reduce the runoff P losses. However, target P loads have not yet been reached through BMP implementation alone, and chemical or biological treatment of runoff should be considered (Flaig and Reddy, 1995). The application of estuarine muck sediments to sandy soils with a high P leaching risk has been shown to reduce the amount of available P (Zhang et al., 2002). This is due to the high Al, Fe and organic matter contents of the muck, which provide additional P sorption sites. It can be inferred that sediments in agricultural ditches function in the same manner. In the Okeechobee Basin, Bottcher et al. (1995) found that irrigation and drainage management has provided a 0% P reduction in discharge, and the use of wetlands has provided a 0% P reduction. Investigating the potential for wetlands and ditches to uptake P and how to manage these systems to achieve the greatest retention can be highly beneficial to land managers. Phosphorus Pollution Pollution is the introduction of harmful substances or products into the environment, and P is only a pollutant under some circumstances. Applied nutrients, either from chemical fertilizer or animal manure, are beneficial to plants if they remain in the soil. However, when they are transported through runoff or leach in the groundwater, they become environmental pollutants (McGechan and Lewis, 2000). When P is applied to soil in excess of the retention capacity of soil and plants, it can be transported in dissolved and colloid-bound forms via storm runoff and groundwater flow. The receiving waters become eutrophic when algae, bacteria, and aquatic plants, which rapidly utilize the incoming P load, grow exponentially and affect water use and the

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12 health of the aquatic ecosystem. Though what constitutes environmental P pollution varies regionally, excessive fertilizer application seems to be exacerbating the problem nationally. A 1991 survey of eastern U.S. state soil testing laboratories indicated high P contents in the majority of tested soils (Sims, 1993). Soil P content was considered high when it exceeded regional requirements for optimum crop yields or were excessive from an environmental standpoint. Phosphorus Forms Phosphorus in surface water consists of four primary pools: soluble reactive P (SRP), dissolved organic P, particulate inorganic P, and particulate organic P (Reddy et al., 1999). To become bioavailable, dissolved organic P, particulate inorganic P, or particulate organic P must be decomposed. The SRP is readily available to plants and microbes. The SRP is also known as dissolved reactive phosphorus (DRP), Murphy and Riley reactive phosphorus (MRP), or orthophosphate. The terminology for bioavailable P relates to an analytical procedure as opposed to representing a specific chemical form. However, it is known to include dissolved monomeric inorganic phosphates such as H 2 PO -4 , HPO 4 -2 and PO 4 -3 in addition to various ion-pairs. The SRP also includes contributions from organophosphorus compounds and inorganic polyphosphates which are hydrolyzed to reactive phosphate in the measurement methodology (Burton, 1973). “Labile P” is a frequently used term describing mobile P that is currently available for plant growth or readily available due to fast kinetics. This includes soluble P and P bound to surface sorption sites (McGechan and Lewis, 2002). In stream sediments of the Lake Okeechobee basin, labile P accounts for less than 3% of the total P. Most sediment P is associated with Fe and Al oxyhydroxides (Flaig and Reddy, 1995).

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13 In agricultural soils, the amount of P contained within each pool is a result of the historical P fertilizer application and lapsed time since the last application (McGechan and Lewis, 2002). Surface soil layers typically have a higher P content than subsurface layers because of greater P sorption, biological activity, and organic matter accumulation on the soil surface (Sharpley, 1995a). Also as a general rule, an increase in the amount of P stored within a soil leads to an increase in the amount in soil solution (Busman et al., 1997). Phosphorus Cycling Phosphorus can become entrained in sediment through four processes: settling of particulate inorganic and organic P, uptake of SRP by algae and its subsequent settling, sorption of SRP or dissolved organic P onto particles which subsequently settle, and the direct sorption of SRP and dissolved organic P onto sediment (Reddy et al., 1999). Phosphorus exchange between the water-column and sediment is dependent on physical, chemical, and biological conditions of the system. Physical parameters such as temperature, wind/wave action, and flow can regulate diffusion and advection. Chemical processes include mineralization, sorption, precipitation, and dissolution. Chemical characteristics affecting P exchange include redox potential, pH, organic matter and metal content of sediments. Organisms affect P exchange through bioturbation and biotic uptake and release (Reddy et al., 1999). Mineralization Mineralization causes inorganic P to be released from organic phosphates. Though most rapid in well-drained, moist, warm soils (Busman et al., 1997), mineralization can also occur at the sediment-water interface. Mineralization of organic matter on the mineral sediment surface can rapidly release phosphate directly to the water-column

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14 (Martens et al., 1978). Mineralization can contribute 25 kg inorganic P ha -1 year -1 in temperate mineral soils and up to 160 kg inorganic P ha -1 year -1 in organic soils (Sharpley, 1995a). In central and south Florida organic soils, Reddy (1983) found that mineralization resulted in 38 to 185 kg inorganic P ha -1 year -1 and 16 to 23 kg inorganic P ha -1 year -1 respectively. If organic soils are drained and subsequently re-flooded, downstream water bodies may receive significant P loads (Sharpley, 1995a). The addition of P through fertilizer can inhibit organic P mineralization, though frequently fertilizer and organic P mineralization concurrently supply P (Sharpley, 1985). Sorption Sorption occurs when a reactive chemical becomes bound to other surfaces. These surfaces may be of immobile particles in the soil matrix, or may be otherwise harmless sediments and colloids that move with water flow. Smaller particles have larger specific surface areas, therefore finer materials have more potential sorption sites per unit volume than coarser materials. Reddy et al. (1996a) noted that over 80% of the sorption sites in moderately impacted stream sediment from the Lake Okeechobee basin are available for further P retention. The sorptive capacities of soils and sediments vary with their metals, calcium carbonate, and organic matter contents. In acid soils, the P-sorption capacity increases with metal oxide content, since these are oppositely charged particles. In calcareous soils, P sorption is limited by calcium carbonate content. Additionally, Gerke and Hermann (1992) found that the P-sorption capacity was related to organic matter content of soils. Specifically, the researchers learned that orthophosphate can be bound to humic surfaces via metal-cation bridging. However, this phenomenon is directly proportional to the Fe content of the humic material (Gerke and Hermann, 1992).

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15 Phosphorus sorption onto soil can be considered as two separate processes. The first, a reversible sorption of P onto surface sites, is considered the fast reaction, while the second, the deposition of P below surfaces of iron or aluminum oxide minerals in soil or calcium phosphate precipitation, is considered the slow reaction (Barrow, 1983; McGechan and Lewis, 2002). Using various diffusion simulations to approximate P sorption and movement through soil, Nye and Staunton (1994) found that the slow reaction was not significant for periods shorter than 10 days. However, some have suggested that the fast and slow processes are indistinct, and they are better represented as a continuum (Addiscott and Thomas, 2000). For most applications, the fast, reversible sorption reaction can be assumed to be instantaneous (McGechan and Lewis, 2002). However, diffusion of dissolved P through a water-column limits the sorption process so the reaction is not instantaneous. Sorption sites can be characterized by differing energy levels. High-energy sites are used before low-energy sites. This nonlinear relationship between adsorbed P and P in solution is frequently represented mathematically, using ‘isotherm’ logarithmic or other equations, to make linear approximations (McGechan and Lewis, 2002). Desorption Desorption is usually not the same process as sorption due to hysteresis effects. Desorption can mimic the reverse of fast sorption process (Barrow, 1979) if the slow reaction never progressed. However, under most circumstances, desorption is slower and less extreme than sorption due to the effects of slow deposition and burial. Less material is available for desorption from the surface sorption sites once surface-sorbed P is transferred within soil particles (Barrow, 1979).

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16 “Buffering capacity” is a term that includes P bound to surface sorption sites, representing the quantity of P that will rapidly desorb under dilution (McGechan and Lewis, 2002). Desorption potential increases with greater saturation of P sorption sites (Pautler and Sims, 2000). Buffering capacity is frequently high in soils containing fine materials such as clay, since these soils have relatively large surface areas. Buffering capacities tend to be highest in clay soils with large proportions of Fe or Al oxide minerals (Bowden et al., 1977). Fe and Al oxides bind P since they are oppositely charged particles (McGechan and Lewis, 2002). Applications of manure or slurry can also increase the buffering capacity of soils. These amendments will increase the colloidal content of the soil and add colloid-bound P (Dewilligen et al., 1982). Phosphorus sorption is influenced by the pH of soils. Therefore, desorption potential of calcareous soils is less than acid soils. Barrow (2002) found that desorption of previously sorbed phosphate more readily occurred at lower pH. For highly loaded stream sediments, Reddy et al. (1996a) found that 14 to 28% of P applied to the water-column of laboratory sediment cores was released once the water-column was replaced with low-P rainwater. Historical loading impacts desorption potential. In agricultural drainages, sediment sorbed P may increase over time, such that older drainage ditches have a greater potential for P desorption (Barlow et al., 2003). Movement In streams and drainage ditches, advection and dispersion control the downstream movement of P. Advection is solute movement caused by water current, and dispersion is the combination of molecular and turbulent diffusion (Barlow et al., 2004). Phosphorus can be transported downstream in numerous forms, such as orthophosphates, polyphosphates, and sediment-bound P (Sharpley and Moyer, 2000). Phosphorus

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17 typically has a long residence time in soil due to sorption, however it can be transported in colloidal and particulate form via soil water movement (McGechan and Lewis, 2002). Some research has shown that the transport of P by colloidal material within soil may play a critical role in overall P movement to receiving waters. Stamm et al. (1998) found that the concentration of P in grassland soil increased during large rainfall events, as opposed to being diluted. This study, along with other studies showing similar results (Hawkins and Scholefield, 1996; Haygarth et al., 1998), indicates that P may be moving through soil via colloids, and that this colloid-bound, yet mobile P has the ability to reach receiving waters (McGechan and Lewis, 2002). These colloids can either be scoured from rainfall impact, or introduced via manure or slurry application (Jarvis et al., 1999). Once colloids reach receiving waters, where the SRP concentration is less than in the soil matrix, colloid-bound P rapidly desorbs (McGechan, 2002). McDowell et al. (2001) states that P is most susceptible to leaching “in sandy soils, soils with a low P-retention capacity, waterlogged soils where P is mobilized under reducing conditions and promoted by the application of P input (e.g. fertilizers and manure).” The soils of the Lake Okeechobee basin satisfy all of these conditions. Once leached, P movement though soil to surface and ground waters is determined by relief, local drainage, and depth to the spodic horizon (Flaig and Reddy, 1995). Factors Affecting Phosphorus Uptake and Release Abiotic factors Hydrology. In general, the amount of P retained within wetlands and streams is proportional to the hydraulic residence time of those systems. By allowing a sufficient retention time in managed wetlands or drainages, vegetative growth and organic accumulation can aid the removal of P from discharge (Bottcher et al., 1995). In contrast,

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18 House et al. (1995b) found that increasing water velocity increased the sorption of P by sediments. Doubling water velocity through a recirculating flume effectively doubled the SRP uptake. In a recirculating flume the reaction time is essentially constant, yet for other simulation channels or for field situations, increased velocity decreases the time available for P uptake (Barlow et al., 2004). For a stream in the Lake Okeechobee Basin, Reddy et al. (1996a) concluded that high flow rate and low hydroperiod limited P adsorption by sediment. In some systems, high flow rates act to release previously bound P by resuspending sediments (Svendsen and Kronvang, 1993). Under excessive drainage, organic matter associated with wetlands and drainage ditches can mineralize, releasing associated P (Bottcher et al., 1995). Drainage is necessary to ensure the health of livestock and to promote the growth of forage crops, yet it is important that wetland soils remain wet to prevent aerobic mineralization. Land managers need to balance increasing the hydroperiod of wetlands and drainage ditches to increase P retention and reduce aerobic mineralization, and allowing adequate field drainage for agriculture. Aluminum and iron. Phosphorus is adsorbed onto metal oxides, such as those of Fe and Al, since these are oppositely charged particles (McGechan and Lewis, 2002). The ability of iron compounds to bind P may be dependent on sediment pH and redox potential (Patrick and Khalid, 1974), but P sorption with aluminum is not affected by oxygen state (Reddy et al., 1995). Acidic conditions promote retention by aluminum and iron, and low redox conditions can cause P release as insoluble ferric iron is reduced to soluble ferrous iron (Patrick and Khalid, 1974). Even though the aluminum reaction with P prevails over iron in acidic soils, both amorphous aluminum and iron phosphates are

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19 formed. Aluminum has a greater capacity to sorb P, but has a lower binding energy compared to the binding energy of iron-bound P (Hartikainen, 1982). Over time the amorphous Al and Fe phosphates are transformed to compounds such as crystalline variscite (Al phosphate) and strengite (Fe phosphate) (Busman et al., 1997). Since P retention by Al oxides dominates in the Lake Okeechobee Basin, P solubility may not be greatly affected by dissolved-oxygen concentrations in the region (Reddy et al., 1996a). P sorption, both fast sorption to surface sites and time-dependent sorption and deposition, have been related to oxalate-extractable Fe and Al (Freese et al., 1992; Slomp et al., 1998). The theoretical maximum quantity of P that can be bound to aluminum and iron oxides is equivalent to Al ox + Fe ox , on a molar basis (Schoumans, 1995). However, experimental evidence shows that the maximum sorbed P found via oxalate extraction is approximately half of Al ox + Fe ox , on a molar basis, especially for non-calcareous sandy soils (Schoumans and Groenendijk, 2000) such as those found in most of south Florida. This quantity can be further subdivided into the maximum for instantaneous, reversible surface sorption, Q m (Q m = 1/6[Al ox + Fe ox ]), and the maximum for time-dependent sorption and deposition, S m (S m = 1/3[Al ox + Fe ox ]). Reddy et al. (1996a) found that aluminum content explained 91% of the variability in P-retention capacity of stream sediments within the Lake Okeechobee Basin. Compared to other soil testing methods, Maguire et al. (2001) found that a single oxalate extraction for Al, Fe, and P was most useful for predicting long-term P release and the capacity of soils to sorb additional P. Smith et al. (2005) found that the P retention of Indiana mineral drainage ditch sediments could be temporarily increased by adding aluminum sulfate (alum) and calcium carbonate (CaCO 3 ). In this experiment, addition of alum and CaCO 3 reduced

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20 exchangeable P by 50% and reduced the equilibrium phosphorus concentration (EPC 0 ) to nearly zero. Alum addition transforms dissolved P into aluminum phosphate precipitates. Welch and Schrieve (1994) have shown that alum treatment also can be effective in lakes for periods of up to five years. Zhang et al. (2002) found that the application of estuarine muck sediments to sandy soils reduces the P available to runoff. The high aluminum and iron contents of the muck increases the P-sorption capacity of the soil. Indeed, through isotherm experiments, the average maximum P-sorption capacity of the muck was found to be 12 times greater than that in the sandy soils (Zhang et al., 2002). Calcium and magnesium. For calcareous sediments, calcium and magnesium may play a crucial role in P retention. Phosphorus is bound to calcium cation in these systems, and a decrease in pH may lead to dissolution of Ca-bound P (Patrick and Khalid, 1974). Calcium-bound P occurs in small amounts in wetlands in the Okeechobee Basin due to low pH conditions (Reddy et al., 1995). pH. Low pH promotes retention by aluminum and iron in acid soils, and high pH promotes retention by calcium carbonate in calcareous soils (Patrick and Khalid, 1974). In a field drainage ditch experiment in Zellwood, FL, it was found that the soluble P concentration of the water-column decreased once pH increased, suggesting calcium precipitation causes P removal (Reddy and Sacco, 1981). However, P precipitation with calcium requires a water pH of at least 8.0 (Diaz et al., 1994). Redox. Anoxia in the water-column can promote low redox conditions in sediment. Phosphorus release is stimulated by low redox potential (Istvanovics, 1988; Appan and Ting, 1996), because insoluble ferric iron is reduced to soluble ferrous iron

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21 thus releasing iron-bound P (Patrick and Khalid, 1974). Indeed, the P-sorption capacity of sediments may be 35% lower under anaerobic conditions than in aerobic conditions (Reddy et al., 1998). The FeOOH-PO 4 complexes constitute the majority of iron-bound P in sediment (Gachter et al., 1988). Under sulfate-reducing conditions, free sulfide may bond with iron precluding the formation of Fe-P (Kadlec and Knight, 1996). Phosphine gas (PH 3 ) can be produced in anoxic sediments, providing a method of P release to the atmosphere. However, the contribution of phosphine gas release is believed to be inconsequential (Kadlec and Knight, 1996). In an agricultural drainage ditch experiment in Zellwood, FL, oxygen status was not found to influence electrical conductivity or the concentrations of K, Mg, and Ca in the water-column (Reddy and Sacco, 1981). Although not important from the P cycling standpoint, the oxygen status of ditches does affect their use as a drinking water source for livestock. Anoxic ditch water has a poor taste and may affect the health of cattle, rendering it a poor choice for watering livestock (Janse and Van Puijenbroek, 1998). Nitrate. A surplus of nitrate may increase the sediment sorption capacity for phosphate by keeping Fe in an oxidized state (Jensen and Andersen, 1992). Indeed, nitrate additions to eutrophic, shallow lakes increased the depth of the oxidized sediment layer in one experiment, and reduced P release (Jensen and Andersen, 1992). Increased nitrate concentrations can also have the opposite effect on phosphate by stimulating Fe-reducing bacteria (Jansson, 1986) and overall microbial activity (Bostrom et al., 1988), both of which may enhance P release from sediments. Temperature. In general, increased temperature increases the rate of the P sorption or desorption from sediment, though the effect is not always significant. Quang

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22 and Dufey (1995) found that P sorption related to Fe-oxyhydroxides was seven times greater at 30C than at 20C. High water temperature has also been shown to encourage P release from sediment to the water-column (Holdren and Armstrong, 1980). High water temperatures may diminish the size of the oxidized sediment layer, consequently releasing P as Fe complexes are reduced (Jensen and Andersen, 1992). Other researchers have had contrary results. El Mahi et al. (2001) found that sorption increased with temperature at low P applications, though sorption decreased with temperature at high P applications. Another study found no relationship between temperature and P adsorption (Cerco, 1985). Kadlec and Reddy (2001) have also shown that temperature has little effect on P sorption or removal in treatment wetlands. Landuse. A study by Smith et al. (2005) has shown that the amount of readily desorbed P in drainage ditch sediments decreases with increasing area drained, likely due to a wider sediment size distribution and less organic matter. Landuse determines sediment composition in waterways and subsequently controls which sediment processes dominate P uptake (McDowell and Sharpley, 2003). Moyer et al. (1998) found that grazed stream reaches possessed greater nutrient retention than other ungrazed reaches. Since cattle activity in the channels widen the stream channels, flow velocity is slowed, and biotic nutrient uptake increases with the increased hydroperiod. Biotic factors Bioturbation. Benthic macroinvertebrates can have a considerable impact on P flux across the sediment-water interface. Due to sediment irrigation caused by the burrowing activities of benthic macrofauna, P flux may be 1 to 10 times greater than would be expected otherwise (Callender and Hammond, 1982). For a single sediment type under Lake Okeechobee, diffusion coefficients varied by as much as 470% due to

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23 varying activities of benthic macroinvertebrates (Vanrees et al., 1996). Benthic macrofauna can promote solute flux at least as large as that due to molecular diffusion alone (McCaffrey et al., 1980). Callender and Hammond (1982) found that P flux for the sites with fewer macroinvertebrates was well correlated to molecular diffusion. Vanderloeff et al. (1984) found that the effect of benthic macrofauna was reduced when dissolved-oxygen approached zero. Additionally, the burrowing activities of benthic macrofauna influence the depth of oxygen penetration into sediment (Henriksen et al., 1983). Macrophytes. Aquatic vegetation and algae temporarily retain P, and long-term retention can occur through organic matter accretion (Reddy et al., 1996b). Emergent macrophytes may release P from living tissue, though P release from plants is more pronounced after senescence and decay. In an experiment involving Eichhornia crassipes in a drainage ditch, herbicide application increased soluble N and P concentrations in the water-column, though this release may be redox-dependent (Reddy and Sacco, 1981). Macrophyte decay at the sediment surface may lower the redox potential of the sediment and cause a release of phosphorus to the water-column (Reddy et al., 1999). Additionally, decay of above-ground biomass releases roughly 80% of the stored P in the plant (Reddy et al., 1995). However, biomass decomposition half-life for Pontederia, the dominant emergent macrophyte at one of the two study sites, is 73 days, and P release during decomposition is initially slow (Reddy et al., 1995). Floating plants like Eichhornia crassipes reduce oxygen diffusion into the water-column by covering the surface. Janse and Van Puijenbroek (1998) found that duckweed (Limnaceae) coverage in drainage ditches, onset by excessive P fertilization, causes

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24 anoxia, a loss of biodiversity, and inhibits the agricultural function of the ditches. Duckweed promotes anoxia in drainage ditches by reducing oxygen diffusion through the water-column and by extracting oxygen through decomposition. Furthermore, during photosynthesis, duckweed releases oxygen to the atmosphere instead of to the water-column. Bacteria. The role of bacteria in sediment-water P exchange has typically been thought to be an indirect one. Sedimentary microorganisms decompose organic matter, consuming O 2 and NO 3 in the process. Therefore bacteria can provide the conditions necessary for ferric iron reduction and phosphate release (Martens et al., 1978; Jansson, 1987). However, Gachter et al. (1988) provides evidence that benthic bacteria, even more than phytoplankton, play a direct role in P uptake and release. The biotic response to redox potential mirrors the abiotic response: SRP is depleted under oxic conditions, and released under anoxia. Under aerobic conditions, benthic algae can retain P from the water-column, though saturation can occur at very low concentrations (<10 ppb) (Mulholland et al., 1990). Under anaerobic conditions, polyphosphates contained within bacteria are hydrolyzed to orthophosphate (Gachter et al., 1988). Additionally, P release caused by reduction is mediated through iron-reducing bacteria. To summarize, bacteria contribute to low redox potential through metabolism of carbon. Low redox potential enables iron-reducing bacteria to transform ferric iron to ferrous iron, thereby releasing P. Furthermore, bacteria can directly contribute to P release under anaerobic conditions by hydrolyzing internally stored polyphosphates (Mitchell and Baldwin, 1998). It is interesting to note that drying severely reduces the capacity of sediment to release P under anaerobic conditions. Sediment exposure to air

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25 causes a shift in the bacterial community structure, limits carbon, and transforms minerals with which P is associated (Mitchell and Baldwin, 1998). Though these affects may be short-lived, they play a role in biogeochemical P cycling. Methods of Phosphorus Flux Measurement Monitoring: Mass balance Mass balance can be used to estimate the different components of nutrient flux, frequently over large spatial and temporal scales. These nutrient inflow and outflow components typically include wet and dry deposition, surface water, groundwater, sediment nutrient flux, and point source effluent discharges (Sigua and Tweedale, 2003). All of these can be measured directly, though estimates and indirect measurement is frequently used in mass-balance calculations, especially when measurement is not feasible. Stream-scale nutrient addition experiments Nutrient uptake or temporary retention can be quantified in flowing systems through coupled nutrient and conservative tracer additions (Triska et al., 1989b; Stream Solute Workshop, 1990). Stream-scale experiments have the advantage of quantifying whole aquatic systems, incorporating sediment sorption, advection, diffusion, groundwater influences and biotic effects. The underlying process that can be explained through these experiments is hyporheic exchange (Triska et al., 1989a). The hyporheic zone can be thought of as a region of shallow groundwater involved in active bidirectional exchange with surface water. Though groundwater inputs and outflows can be significant in some systems, shallow hyporheic exchange dominates over shorter time scales. Hyporheic exchange

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26 retains water and solutes, increasing the hydraulic residence time of stream systems and proliferating a biotic community dependent on those solutes. By adding a nutrient and a conservative tracer to a flowing system, hydrology and biology can be assessed simultaneously. A frequently used method is constant injection (Kilpatrick et al., 1985). By taking samples downstream at regular intervals, the passage of the solute front can be quantified, and flow accurately determined. Also, the difference in magnitude between the added nutrient and tracer represents abiotic and biotic retention. After the system reaches equilibrium, and all hyporheic zones have theoretically become saturated with tracer, samples can be taken with distance to help spatially quantify nutrient uptake and release (Triska et al., 1989a). However, stream-scale manipulation experiments are essentially uncontrolled and unreplicatable (Hurlbert, 1984), and cannot simultaneously characterize a range of nutrient concentrations (Triska et al., 1989b). The information gleaned from stream tracer experiments can vary widely with discharge (Harvey et al., 1996), and the nutrient pulse can change the system being measured. In some cases nutrient addition causes the function of the stream to switch from a net source to a net sink (Triska et al., 1989b). Because of this, nutrient radiotracer analyses are preferred to unlabeled nutrient additions (Mulholland et al., 2002), yet radiotracers are typically unfeasible. Additionally, stream tracer studies only provide reliable information under certain conditions. Nutrient retention estimates will be unreliable if flow or solute exchange rates are too fast, or exchange timescales are too long (Wagner and Harvey, 1997), as is likely the case of slow-flowing south Florida drainages (Heatwole et al., 1987).

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27 Batch incubation: Isotherm tests Exchangeable P can be determined by shaking a wet sediment sample with an MgCl 2 solution for 1 h. After centrifuging and filtering the sample, exchangeable P can be calculated (Ruttenberg, 1992). Exchangeable P represents the labile P that would initially desorb from sediments if the sediment were to function as a P source (Smith et al., 2005). However, the most widely used method of estimating P-sorption isotherm parameters is to conduct an incubation experiment where a P solution and an absorbent are held in contact for a prolonged period of time. This frequently involves 24 hours of shaking the solution with the absorbent. Maximum P sorption is determined through batch incubation studies, though the parameters gleaned from these experiments can vary due to contact time and temperature (McGechan and Lewis, 2002). Batch incubation is typically a 24-hour test, though true phosphate sorption equilibria take weeks to years to become established (Hansen et al., 1999). A standard method involves treating 2 gram homogenized soil or sediment samples with 20 mL of 0.01M KCl solution containing various concentrations of P (0, 0.01, 0.1, 5, 10, 25, 50, 100 mg P l -1 ). The samples are shaken for 24 hours, settled for 1 hour or centrifuged, filtered through a 0.45 m filter, and analyzed for SRP. Equilibrium phosphate concentration. The equilibrium phosphate concentration, or EPC 0 (Taylor and Kunishi, 1971), can be determined from a sorption isotherm as the concentration of inorganic P (after 24 hours) which results in no net release or sorption (n a = 0). The EPC 0 can indicate if adsorption or desorption occurs, but cannot predict the direction of P flux (Reddy et al., 1995). To determine the EPC 0 of sediment, an isotherm must be performed on wet sediment samples. The EPC 0 can be calculated by

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28 performing a regression between the amount of soluble P sorbed by the sediment and the initial soluble P concentration of each sample. Most studies use a 24-hour shaking time, however Smith et al. (2005) shook samples for 1 hour. The EPC 0 may be used to determine the surface water conditions under which P will be retained or released. The calculated EPC from batch incubation, laboratory sediment column, and field mesocosm experiments will be different, however. It is important to know what type of experiment was conducted when comparing EPC values. The EPC 0 of native soils in the Lake Okeechobee basin averages 1.3 mg l -1 for surface soils and 0.1 mg l -1 for soils in the spodic horizon. For comparison, the EPC of impacted soils ranges from 5.3 to 10.6 mg l -1 for surface soils and 5 mg l -1 for soils in the spodic horizon (Graetz and Nair, 1995). High P application to sediments will increase their EPC 0 (Logan and McLean, 1973). The EPC 0 of impacted soils and sediments should decrease after the abatement of upland P load (Diaz et al., 1994). For stream sediments and wetland soils in the S-154 sub-basin, Reddy et al. (1995) determined parameters related to P sorption (Table 2-1). The average equilibrium phosphorus concentration determined for stream sediments in the S-154 basin is four times greater than for any other Lake Okeechobee drainage basin. Low P saturation indicates that there is considerable potential for further P sorption. Low buffer intensities (K d ), as shown for stream sediments, suggest high potential for P desorption into the water-column. Laboratory intact sediment cores Another approach to quantify P assimilation is to bring an intact sediment core to the lab and change the floodwater P concentration while keeping other variables constant (Reddy et al., 1996b; Nguyen and Sukias, 2002). Transparent Lucite columns are

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29 Table 2-1 Phosphorus sorption characteristics for stream sediments and wetland soils in the S-154 basin. Site K d (l kg -1 ) S o (mg kg -1 ) EPC o (mg l -1 ) S max (mg kg -1 ) k (l mg -1 P) P saturation (% S max ) S-154 Stream 8.3 32 4.76 162 0.053 20 S-154 Wetland 49.4 10.5 0.36 297 0.143 3.5 K d = P sorption coefficient or buffer intensity; S o = P present in sorbed phase under ambient condition; S max = P sorption maximum; k = Constant related to bonding energy (Reddy et al., 1995) frequently used in this capacity, since they can be used as a coring device and then as part of the laboratory apparatus. For stream sediments, Reddy et al. (1996a) determined that P retention increases linearly with P loading up to a water-column concentration of 6 mg P l -1 for hydraulic retention times greater than 4 days. Between 37 and 88% of added P was retained in these experiments. When loaded sediment cores were exposed to ambient floodwater, between 2 and 28% of previously retained P was released. The researchers noted that P retention was not affected by shading. By conducting several intact sediment core experiments using different floodwater concentrations, the EPC w can be determined. Whereas the EPC 0 , determined from batch incubation experiments, is the equilibrium phosphorus concentration for sediment and solution mixtures, EPC w is the floodwater concentration at which no net P retention or release occurs from intact cores. The EPC w of stream sediments in the Okeechobee Basin averages 0.10 mg l -1 , and the EPC w of stream sediments in the S-154 basin averages 0.19 mg l -1 (Reddy et al., 1995). Determining P-retention capacity from isotherms or laboratory intact sediment cores usually underestimates actual retention occurring under field conditions (Reddy et al., 1995). Barlow et al. (2004) suggests that laboratory sediment columns can be used to

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30 estimate parameters for rate equations (i.e. Elovich equation) which can be expanded to model P transport in fluvial systems. Hydrologic and redox fluctuations in the field can affect P retention and release. To estimate field P retention from sediment sorption data, several dynamic channel processes, including floodwater P concentration, water depth, water oxygen demand, and hydrologic transport processes must be considered. Field experiments may be a better choice to estimate P retention. Though these experiments are less controlled, the conditions are more representative of what controls actual P retention and release. In-situ benthic mesocosms Measuring nutrient fluxes in the field has several advantages and disadvantages over the laboratory intact sediment column approach. Variables such as water, air, and sediment temperature, photoperiod, dissolved-oxygen, pH, and dissolved chemical constituents in the water-column will be representative of true field conditions in the in-situ approach. Additionally, by conducting the analysis in place, the system will undergo less disturbance than if the sediment were transported to the laboratory. However, since the aforementioned system variables are not constant in the field, determining relationships between nutrient flux and specific variables may be difficult. In the laboratory, variables such as water temperature and dissolved-oxygen will be chosen and maintained at constant values. Other difficulties arise in the field such as accounting for or blocking rainfall, and ensuring hydraulic isolation between the enclosures and the surrounding system. One study found that the root-mean-square difference in nutrient flux measures conducted on laboratory cores compared to in-situ measurements was the same magnitude as the measured fluxes (Cerco, 1985). Other studies have shown that solute

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31 flux measured through an in-situ experiment may be 1 to 29 times greater than that measured through other means (McCaffrey et al., 1980; Callender and Hammond, 1982; Gomezparra and Forja, 1993; Vanrees et al., 1996). The disparity is due to bioturbation caused by benthic macrofauna, which is not considered in other measurement techniques. The previously mentioned studies clearly indicate that using in-situ benthic mesocosms is advantageous to laboratory column experiments. A disadvantage of both laboratory sediment cores and in-situ benthic mesocosms is that potential effects of advection are not considered with either method, since they are both stationary enclosures. Though some laboratory studies have included water-column mixing to replicate advection, rarely do mixing intensities match actual field conditions (Lavery et al., 2001). The errors caused by differences in advective transport for the mesocosm studies are likely to be small for the slow flowing systems of the Lake Okeechobee basin. Additionally, in either method potential interactions between the water-column or sediment and the enclosure walls can occur if bacterial colonization ensues. Including controls into experiments should help account for this possibility. By hydraulically isolating a portion of the water-column and sedimentary column, nutrient fluxes across the sediment-boundary layer can be measured more easily. Thompson et al. (2003) used portions of polyethylene drums for field-situated mesocosms, but did not use in-situ sediment. Fisher and Reddy (2001) used 0.5 m 2 acrylic chambers to enclose wetland soils in-situ. A recirculation pump was used periodically to create sufficient water movement for proper readings with an oxygen electrode. Oxygen uptake was 0.1 to 0.8 g O 2 m -2 d -1 .

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32 Porewater profiles Observed concentration gradients at the sediment-water interface can be used to calculate flux, frequently via Fick’s First Law of diffusion. Porewater gradients in south Florida have been estimated to take 1 year to establish (Kadlec and Knight, 1996), so they may essentially represent a 1 year historical record. Devol (1987) found excellent agreement between calculated flux from porewater observations and that measured through benthic chambers. Calculating flux based on porewater observations usually requires a strong understanding of the relevant transport mechanisms such as molecular diffusion, bioturbation, and benthic irrigation (Carignan and Lean, 1991). Reddy et al. (1995) suggests a porewater profile augments equilibrium phosphorus concentration information by indicating the direction of potential P flux. It is important to note that Fick’s First Law assumes laterally uniform bacterially mediated processes (Kana et al., 1998). Phosphate and ammonium fluxes are well predicted using Fick’s First Law, especially for coarse sediments. However, Fick’s First Law may overestimate flux by up to 40% for fine sediments (Lavery et al., 2001). Phosphorus Modeling For P sorption experiments, the term ‘model’ generally means the fitting of experimental sorption data to instantaneous equilibrium isotherm equations, or to equations describing the approach to equilibrium (McGechan and Lewis, 2002). Research has shown that two distinct P sorption processes occur: fast, reversible sorption of P onto particle surface-sites, and time-dependent, irreversible deposition and burial of P. The latter process is frequently termed slow sorption. Some researchers have disagreed with this separation, preferring a continuum (Addiscott and Thomas, 2000). Regardless, when modeling P sorption and desorption, it is important to understand that

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33 the two processes have different P assimilation rates, and that desorption only readily occurs from the fast-sorbed surface-bound P pool. Many studies have used the Freundlich, Langmuir or other isotherm equations to model instantaneous P sorption. Kinetic versions of these isotherms in addition to other kinetic models have been used to achieve fits of P sorption data. The kinematic models can represent the slow-sorption process, or time-dependent components of reversible sorption. It is theorized that fast, reversible sorption is not always instantaneous, since a diffusing solute is limited by access to exchange sites. For this reason, some have incorporated diffusion transport into kinematic sorption models (Staunton and Nye, 1989b). Most of the included models are empirical or semi-empirical. Though mechanistic models may be physically justified, the necessary parameters are difficult to estimate at best (Crank, 1964; Vanriemsdijk et al., 1984; House and Denison, 2002). Several more comprehensive weather-driven models such as EPIC, GLEAMS, AMINO, and DAYCENT incorporate simplistic versions of isotherm or other models to represent fast and slow P sorption. Net P Flux Calculations Nutrient flux. Nutrient flux from laboratory sediment column or in-situ benthic chamber experiments have been calculated using Equation 2-1 (Cerco, 1985; Fisher and Reddy, 2001). AtCCVJn)(0 (2-1) J = mean flux rate (g m -2 day -1 ) V = volume of water in column (m 3 ) C 0 = concentration at the start of the experiment (mg l -1 )

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34 C n = concentration at the end of the experiment (mg l -1 ) A = cross-sectional area of column (m 2 ) t = time (days) Fick’s First Law. By conducting a porewater profile analysis on sediment cores, the measured concentration gradients can be used in conjunction with Fick’s First Law of diffusion to estimate solute flux. However, calculating flux based on porewater observations usually requires a strong understanding of the relevant transport mechanisms such as molecular diffusion, bioturbation, and benthic irrigation (Carignan and Lean, 1991). 5107379.2 ZCDJs (2-2) J = diffusive flux (mg m -2 d -1 ) = sediment porosity (cm 3 cm -3 ) D s = sediment diffusion coefficient (m 2 year -1 ) C/Z = porewater concentration gradient (mg cm -4 ) 5107379.2 = unit conversion factor Several diffusion coefficients are provided in Table 2-2. Coefficients may vary because of moisture content and impedance differences (Staunton and Nye, 1989b). Table 2-2 Diffusion coefficient used with Fick’s First Law varies with solute and sediment type. All coefficients are at 25C. Solute Diffusion Coefficient (m 2 year -1 ) System Reference PO 4 -3 0.0249 Ideal values for H 2 PO -4 and HPO 4 -2 (weighted average) (Reddy et al., 1996b; Song et al., 2004) PO 4 -3 0.0267 Oceanic sediments (Li and Gregory, 1974) PO 4 -3 0.0158 Wetlands (Kadlec and Knight, 1996) NH 4 + 0.0624 Oceanic sediments (Li and Gregory, 1974) NH 4 + 0.0442 Estuarine sediments (Lavery et al., 2001) NO 3 0.5990 Oceanic sediments (Li and Gregory, 1974) NO 3 0.2682 Estuarine sediments (Lavery et al., 2001) KBr 0.0536 Soil columns (Scotter and Tillman, 1991) CaBr 0.0347 Soil columns (Scotter and Tillman, 1991)

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35 Net P flux models Temkin. The Temkin model has been used for modeling data from batch incubation studies (Barrow, 1978; Mead, 1981; Whalen and Chang, 2002), though it has not performed as well as the Freundlich or Langmuir models (Whalen and Chang, 2002). )ln(21CkkQTT (2-3) Q = quantity of P sorbed (g [P] kg -1 [soil]) C = concentration of P in solution (mg l -1 ) k T1 , k T2 = empirical coefficients Freundlich. The instantaneous equilibrium form of the model has the general form: 1bFCkQ (2-4) Q = quantity of P sorbed (g [P] kg -1 [soil]) C = concentration of P in solution (mg l -1 ) k F = coefficient This form of the model allows for good fits to sorption data from most soils, though it does not include a saturation value (McGechan and Lewis, 2002). Yuan and Lucas (1982) found that the linear Freundlich model described P sorption better than the Langmuir model for Florida sandy soils. Researchers noted that although the Freundlich model better predicted P sorption for Myakka and Pomello sands, it did not work well for Immokalee sand, which is a similar soil found in combination with Myakka throughout the flatwoods region of south Florida. The Freundlich model can be modified to include P already present in the soil (Barrow, 1978): 10bFCkQQ (2-5) Q 0 = surface-sorbed P in the soil prior to sorption test

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36 Langmuir. The instantaneous equilibrium form of the model has the general form: CkCkQQLL1max (2-6) Q max = maximum (saturation) sorption capacity (g [P] kg -1 [soil]) k L = coefficient, and all other terms as defined previously Q max represents the maximum for fast, reversible sorption, and is frequently used as a sorption index (McGechan and Lewis, 2002). The Langmuir isotherm assumes completely mixed conditions, so the solution contacts all surface sorption sites on the soil or sediment. However, under field conditions the solution does not immediately contact all surface sorption sites, and diffusion becomes the limiting factor for P retention (Staunton and Nye, 1989b; Reddy et al., 1995). The AMINO weather-driven model uses this form of the Langmuir isotherm to calculate instantaneous P sorption (Groenendijk and Kroes, 1999). For situations where the simple Langmuir model gives poor fits to sorption data, a ‘two-surface’ instantaneous equilibrium model can be applied (Holford et al., 1974; Holford and Mattingly, 1975; 1976). CkCkQCkCkQQLLLL222max,111max,11 (2-7) Q max,1 and Q max,2 are separate sorption maxima, so saturation is equivalent to Q max,1 + Q max,2 . One population of sorption sites may have much higher bonding strength than the other, so this model allows for the disparity. The shape of this isotherm is similar to that of the Freundlich isotherm, though it includes defined sorption maxima (McGechan and Lewis, 2002). Michaelis-Menton. The Michaelis-Menton model for enzyme kinetics is frequently used to describe the hyperbolic relationship between water-column nutrient

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37 concentration and algal uptake rate (Steinman and Mulholland, 1996). This model is similar to the Langmuir model used for instantaneous sorption with soil. SKSVVsm (2-8) V = nutrient uptake rate V m = maximum nutrient uptake rate S = concentration of the nutrient K s = half-saturation constant (or nutrient concentration at which nutrient uptake is half the maximal uptake rate) The maximum nutrient uptake rate can increase as a short-term physiological response to elevated nutrient concentrations, though uptake will not remain elevated. Long-term elevated nutrient concentrations will likely select for an algae community dominated by species with high maximum nutrient uptake rates (Steinman and Mulholland, 1996). Linear. For soils and sediments in the Lake Okeechobee basin with equilibrium phosphorus concentrations (EPC 0 ) less than 10 mg P l -1 , Reddy et al. (1995) found that the relationship between P sorption and solution P concentration was linear in batch incubation experiments. The linear relationship was valid under aerobic and anaerobic conditions. odSCKS (2-9) K d = buffer intensity for P sorption (l kg -1 ) C = P in solution (mg l -1 ) S o = P sorbed under ambient conditions Kinetic P flux Freundlich. Barrow (1983) describes an alternate form of the Freundlich model including time dependence. 21bbFtottCkS (2-10) S tot = sum of instantaneous and time-dependent sorption

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38 The Freundlich model defined in Equation 2-10 is similar to the power function (Kuo and Lotse, 1974; Hansen et al., 1999). Indeed, the only difference between the kinetic Freundlich model and the power function is the inclusion of water-column concentration. Since measured water-column concentrations are used in the calculation of P retention, it is not an independent parameter. Therefore, the kinetic Freundlich model would include nearly identical parameters on either side of the equation. Parabolic diffusion. The Parabolic Diffusion model has been used to model P diffusion in sediment with some success (House et al., 1995a; Pavlatou and Polyzopoulos, 1988). The model has also been termed the diffusion equation in the literature (Cooke, 1966). bRttn2/1)( (2-11) n(t) = mass of P uptake per unit area at time t R, b = constants. If different R and b constants are used, the model may also be written as a function of concentration instead of uptake (Barlow et al., 2004). Applicability of the parabolic diffusion model is generally considered evidence that diffusion is the rate limiting process (Pavlatou and Polyzopoulos, 1988). Power. The power function has also been called the Bangham equation (House et al., 1995a), since Bangham and Burt (1924) first described it for the kinetics of chemisorption. When v = 0.5, the power function is equivalent to the parabolic diffusion model. The power function was found to produce reasonable agreement with data in an outdoor experimental flume (House et al., 1995a). The success of Equation 2-12 is attributable to its two adjustable constants (Pavlatou and Polyzopoulos, 1988). Like the

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39 parabolic diffusion model, conformation to the power function is indicative of diffusion kinetics with a slow chemical reaction (Agbenin and Tiessen, 1995). vBtKtn)( (2-12) n(t) = mass of P uptake per unit area at time t K B , v = constants Linear. Reddy et al. (1995) used a linear empirical relationship to relate P retention in laboratory sediment cores with P concentration in the floodwater. 1PACPr (2-13) P r = phosphorus assimilated by soils or sediments (mg P m -2 ) P 1 = phosphorus release potential of the soil or sediment under ambient conditions (mg P m -2 ) A = phosphorus retention coefficient (l m -2 ) C = water-column P concentration (mg l -1 ) This model is similar to the linear model for net P flux previously discussed. The parameters A, and P 1 are fit through linear regression. The P retention coefficient, A, reflects the combined effects of P diffusion and P sorption with sediments. The EPC w can be determined from Equation 2-13 by setting P r to zero. After determining “best fit” parameters from 294 data sets, the researchers were able to determine Equation 2-14 and 2-15 for stream sediments and wetland soils in the Lake Okeechobee basin. Sediments: 4.12][7.127 SRPPr (r 2 = 0.949) (2-14) Wetlands: 2.54][8.117 SRPPr (r 2 = 0.709) (2-15) Elovich. The Elovich equation is a semi-empirical rate model, that assumes the P uptake rate is related to the degree of sediment saturation and the associated activation energy required for P sorption (Barlow et al., 2004). Several studies involving the interaction of P with agricultural soils have used the Elovich equation (Chien and Clayton, 1980; Pavlatou and Polyzopoulos, 1988). Indeed, in a particular experiment

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40 involving streambed sediments, SRP influx to streambed and suspended sediments was best described by the Elovich equation (House et al., 1995a). Chien and Clayton (1980) found that the Elovich equation provided better fits to experimental sorption data over different time periods than equilibrium isotherm equations or a first-order kinetic equation. Polyzopoulos et al. (1986) concluded that the Elovich equation is not suitable during initial fast sorption or long-term slow sorption, though Agbenin and Tiessen (1995) had contrary results. Barlow et al. (2004) determined that the Elovich equation best described P uptake in both recirculating flumes and laboratory sediment cores, compared to boundary layer and diffusion models. Conformation to the Elovich equation suggests that the rate limiting process is related to diffusion (Pavlatou and Polyzopoulos, 1988). The model can be described by Equation 2-16 or 2-17. )1ln(1)(abtbtn (2-16) )1ln(''AteBtn (2-17) n(t) = mass of P uptake per unit area at time t a, b, A’, and B’ are constants The physical significance of the Elovich parameters is uncertain (House et al., 1995b; Barlow et al., 2004) Boundary layer. One form of the boundary-layer model is presented in Barlow et al. (2004). In Equation 2-18, can be considered the EPC, and k can be considered a function of water depth, velocity, and diffusion. Both parameters may also be treated as empirical.

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41 )()(01ktkteectc (2-18) c(t) = P concentration at time, t c 0 = initial concentration = final concentration k = rate constant A different form of the model describes the quantity of sorbed P. Equation 2-19 is equivalent to a first-order kinetic equation (House et al., 1995a). )'(1'tketn (2-19) n(t) = mass of P sorbed per unit surface area ’ and k’ = empirical parameters Lookman et al. (1995) used a similar equation to model desorption kinetics. The ’ parameter is essentially equivalent to the equilibrium P load per unit area in solution. Barlow. An empirical three-parameter model described by Barlow et al. (2003) is similar to the boundary-layer model. It was used to describe P uptake observed in drainage ditches. The asymptote of the curve, C final , can be given or used as an empirical parameter. btfinalaeCtc)( (2-20) C final = equilibrium phosphorus concentration in solution a and b = empirical parameters Other empirical models. When studying P sorption in macropores of aggregated subsoils, Hansen et al. (1999) found that a ‘lag-linear’ model fit their data better than any standard kinetic isotherm equation. ACln , 0 < t t L (2-21) 11lnlnLttBAC , t > t L (2-22) t L = lag-time before the slow deposition reaction begins A, B = empirical coefficients However, the lag observed by Hansen et al. (1999) resulted from large solution:soil ratios in the batch incubation experiments, instead of actual soil behavior (Barrow et al., 2000).

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42 Staunton and Nye (1989a) compared three complex models for phosphate diffusion and reaction in soil columns. The authors found that only one model, which included an instantaneous reaction and a second order, reversible reaction, adequately fit observed results. Since a mechanistic reason for a second-order reaction is unknown, the model is assumed to be empirical. Aharoni et al. (1991) used an expression that is approximated by a first-order equation for short time periods (< ~30 min), the power function for intermediate time periods, and the Elovich equation for extended time periods (> ~1 day). The model was tested by other researchers (Agbenin and Tiessen, 1995; Pavlatou and Polyzopoulos, 1988), but the model requires many parameters, rendering it difficult for use to describe data (Hansen et al., 1999). Barrow and Shaw (1975) developed an empirical relationship combining the Freundlich and the Arrhenius equation, so that temperature was included. However, temperature has been shown to have little effect on P flux in wetland systems (Kadlec and Reddy, 2001). The CE-QUAL-RIV1 model uses a simple relationship for P (USACE, 1990). Phosphate is depleted through concentration dependent sorption, and 1% of algal growth or decay is subtracted or added respectively to the water-column as P. Weather driven models EPIC and GLEAMS. In the EPIC model (Erosion/Productivity Impact Calculator), “rapid” and “slow adsorption” are treated separately (Jones et al., 1984a; Sharpley et al., 1984; 1984b), however these processes are not identical to the fast and slow sorption mentioned in other studies. Rapid adsorption, in this case, is the process of labile P (both soluble and surface-sorbed inorganic P) being transformed to an “active” inorganic P pool. The active pool essentially represents that P that has undergone time-dependent, yet still reversible sorption (McGechan and Lewis, 2002). Slow adsorption,

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43 in this case, is the transfer of P from the active pool, to an irreversible pool (Jones et al., 1984a; Sharpley et al., 1984; 1984b). Much of the GLEAMS model is taken from the EPIC model. In GLEAMS, the equation for the proportion of added P remaining after incubation (P sp ) was split into three to account for different soil types. In slightly weathered non-calcareous soils, P sp is dependent on base saturation and pH, yet in highly weathered non-calcareous soils, P sp is a function of clay content (Knisel, 1993). Others. To represent the fast, reversible P sorption reaction, AMINO uses the Langmuir equilibrium isotherm (Groenendijk and Kroes, 1999). Schoumans (1995) estimated the k L coefficient in the Langmuir isotherm to be 1129 for non-calcareous sandy soils. Weather-dependent system scale models such as DAYCENT (Parton et al., 1998) and ecosys (Grant and Heaney, 1997) incorporate soil P dynamics as part of their subroutines. DAYCENT uses the fast P sorption routine of the Langmuir isotherm (Parton et al., 1998), and assumes an equilibrium between soil sorbed P and soil labile P (Lewis and McGechan, 2002). The ecosys model, which uses algorithms describing complex relationships between P sorption and numerous soil minerals such as Al, Fe, and Ca under different redox conditions (Grant and Heaney, 1997), has been tested to represent P transformations in laboratory soil column experiments (Grant and Robertson, 1997). Unfortunately, these data are not published. HSPF and QUAL2E, developed by the US EPA, are river transport models including P release routines. P release from riverine bed sediments is considered constant

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44 in these models, though different values may be specified for aerobic and anaerobic conditions (Webster et al., 2001). Sorption Indices Sorption maximum Q max , from the Langmuir isotherm, represents the maximum for fast, reversible sorption, and is frequently used as a sorption index (McGechan and Lewis, 2002). Q max , which has been used to define P saturation (Sharpley, 1995b), is determined by shaking soil samples with a solution containing a known P concentration for 24 hours. Reddy et al. (1996b) related Q max to several parameters of stream sediments and wetland soils in the Lake Okeechobee Basin, which explained 93% of the variability in Q max . 2.1][238.0][095.0][17.2max oxoxAlFeTOCQ (2-23) TOC = total organic carbon (g kg -1 ) Fe ox = oxalate extractable Fe (mg kg -1 ) Al ox = oxalate extractable Al (mg kg -1 ) Comparing the extent of P accumulation in sediments to their Q max is known as the degree of P saturation (DPS) (Nguyen and Sukias, 2002). Drainage sediments in the Delaware Inland Bays with DPS values higher than 40% have been designated at-risk for P losses (Sallade and Sims, 1997). Dutch saturation index Another saturation index can be determined from oxalate-extractable P, Al, and Fe. A Dutch saturation index greater than 25% is sufficient for P loss to occur. Specifically a D ssp of 25% has been related to an equilibrium phosphorus concentration (EPC) of 0.1 mg l -1 , which has been designated as the acceptable limit for Dutch soils and sediments (Schoumans and Groenendijk, 2000). The commonly used definition of the Dutch saturation index is as follows:

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45 oxoxoxSSPFeAlPD21 (2-24) P ox , Al ox , Fe ox = Oxalate-extractable phosphorus, aluminum, and iron respectively (mmol kg -1 ) Other researchers (Khiari et al., 2000; Pautler and Sims, 2000) have used similar [P / (Fe + Al)] ratios to predict P runoff and leaching potential. Zhang et al. (2002) found that water-extractable P in muck sediment increases with oxoxoxFeAlP . Free Al and Fe Maguire et al. (2001) suggests that the oxalate-extractable aluminum and iron not currently associated with P, or “free Al and Fe”, is equivalent to the additional P-sorption potential of soils and sediments. oxoxoxoxoxPFeAlFeAlFree 5.0 (2-25) P ox , Al ox , Fe ox = Oxalate-extractable phosphorus, aluminum, and iron respectively (mmol kg -1 ) Nitrogen Nitrogen Cycle Several nitrogen (N) sinks and sources exist in wetland systems, including the atmosphere, sediment-water interface, sedimentary column, and living and dead biomass (Soto-Jimenez et al., 2003). In the sediment-floodwater environment studied, up to six separate N transformation processes may occur. These processes include mineralization of organic N to NH 4 + , nitrification of NH 4 + to NO x , denitrification of NO 3 to N 2 , adsorption and desorption of NH 4 + with sediment, NH 3 volatilization in the water-column, and biotic uptake of N. Nitrification occurs in aerobic environments, and denitrification occurs in anaerobic environments. Different forms of N can be transported between the floodwater, aerobic sediment layer, and anaerobic sediment layer

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46 through diffusion or resuspension (Reddy and D'Angelo, 1994). Diffusion is the dominant transport process of N species through sediment. Water-column N reduction in wetlands is primarily attributed to plant uptake, ammonia volatilization, and bacterial nitrification-denitrification (Soto-Jimenez et al., 2003). Ammonia is lost from the water-column through volatilization, nitrification-denitrification and biotic uptake, and nitrate is lost through denitrification and biotic uptake. Mineralization In anoxic sediments mineralization of organic matter produces NH 4 + , while anaerobic decomposition simultaneously consumes NO 3 as electron acceptors. This aids the creation of concentration gradients for both N species. The necessary nitrate can be supplied through diffusion from the water-column or aerobic sediment layer (Soto-Jimenez et al., 2003). Though mineralization occurs in aerobic as well as anaerobic sediments, the process is most rapid at low porewater oxygen concentrations and high temperatures (Cerco, 1985). For Florida estuarine sediments, ammonium release is greater in anaerobic sediments than in aerobic sediments (Malecki et al., 2004). In one experiment NH 4 release was steady and continuous for anaerobic sediments, while water-column NH 4 -N concentrations above aerobic sediments rapidly decreased and then steadied. The observed aerobic sediment phenomenon was due to immediate nitrification of released ammonium. After one day, a large enough nitrifying bacteria population existed to maintain low ammonium concentrations. Nitrification Nitrification is an O 2– dependent process where ammonium is oxidized to nitrate (Christian, 1989). Though the ammonium generated from mineralization may be directly

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47 released to the water-column, it is often oxidized to nitrates and nitrites in the oxic sediment-water interface (Soto-Jimenez et al., 2003). The ammonium necessary for nitrification can be diffused from the water-column, or the anaerobic sediment layer, depending on concentration gradients (Reddy et al., 1976). The generated nitrate is immediately assimilated by plankton in the water-column, or is diffused downward to the anaerobic layer due to a demand for electron acceptors (Reddy and D'Angelo, 1994). Nitrification and immediate downward nitrate diffusion has been shown to consume considerable quantities of NH 4 + -N, when it was applied to overlying floodwater in wetlands (Reddy et al., 1976). Summertime anoxia of the sediment-water interface frequently results in the temporary loss of nitrification (Kemp et al., 1990). Denitrification Nitrate diffused into the anaerobic sediment layer may be used as an electron acceptor by denitrifying bacteria, subsequently releasing N 2 and N 2 O to the atmosphere (Kemp et al., 1990). Denitrification increases with temperature and decreases with oxygen concentration (Cerco, 1985). Denitrification only occurs under anoxic conditions, however both nitrification and denitrification may proceed regardless of oxygen state due to aerobic or anaerobic microzones in sediment (Kana et al., 1998). The aerobic rhizosphere of emergent macrophyte roots is an example of a microzone, where nitrification occurs in the immediate vicinity of anaerobic denitrification (Reddy et al., 1989). Simultaneous nitrification and denitrification produces a relatively instable pool of inorganic N in wetland systems (Reddy et al., 1976). Adsorption and Desorption Nitrate flow through laboratory soil columns was found to occur at the same rate as bromide (Sonon and Schwab, 2004). Nitrate is not affected by sediment sorption

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48 (Cameron and Wild, 1982). Ammonium, however, can become sorbed onto sediment and released during sediment resuspension (Reddy and D'Angelo, 1994). It has been found that slight sediment suspension does not provide a significant quantity of ammonium to the water-column (Blackburn, 1997). Furthermore, resuspension of sediments may only affect the timing of ammonium release to the overlying water, not the quantity. Volatilization Water-column ammonium is converted to ammonia under high pH conditions and high temperatures (Erickson, 1985). Algae can promote NH 3 volatilization by increasing water-column pH through CO 2 consumption (Bouldin et al., 1974). In a drainage ditch experiment, Reddy and Sacco (1981) suggest that low accumulation of NO 3 -N indicates the dominance of volatilization over nitrification. Biotic Uptake Like emergent macrophytes and algae, duckweed (Lemna minor), possesses the ability to uptake N. When nitrate is not available in the water-column, duckweed switches to ammonia as a nutrient source. The ammonia is immediately taken up and incorporated into amino acids (Kopp et al., 1974).

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CHAPTER 3 MATERIALS AND METHODS Site Description Location The study area was located within a commercial cattle ranch in Okeechobee County. The ranch is 4 km east of the Kissimmee River and 16 km north of Lake Okeechobee. The ranch is located on NW 127 th Terrace Road between the Seaboard Coast Line Railroad and State Road 70, and is an area commonly known as Yates Marsh and Popash Slough. The study site is located within the S-154, a defined sub-basin of the Lower Kissimmee River watershed (Figure 3-1). Ranch Description The ranch known as the Pelaez & Sons Ranch has an area of 620 ha. It is a low-density beef cattle ranch dominated by improved pasture laced with shallow ditches for drainage. Elevations within the ranch range from 10 to 11 m above sea level. The pastures on the ranch are planted with bahiagrass (Paspalum sp.), Floralta (Hermarthria sp.), and Starrgrass. Bahiagrass, tolerant of a wide range of soil conditions, is the most common forage type both on the ranch and in this region. Floralta, however, has a greater ability to utilize phosphorus (P) (Dinkler, 1990). The property is used exclusively for cow-calf operations. Historical land use at the ranch included vegetable (mostly tomato) production in the 1950s and early 1960s. A network of drainage ditches was dug in the 1960s to increase the crop use area. Currently, the ranch contains enough forage to support 580 animal units. Phosphorus 49

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50 inputs to the ranch originate from cattle excrement, pasture fertilization, and animal supplements. According to the fertilizer history for all fields on the Pelaez & Sons Ranch, furnished by the ranch-owner, approximately 5,990 kg of P (13,730 kg as P 2 O 5 ) and 66,000 kg N was applied to the ranch in 2003 and 2004 (Flinchum, personal communication, 2005). Figure 3-1 Lake Okeechobee Basin and contributing sub-watersheds

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51 Ranch Best Management Practices (BMPs) Herbaceous filter strips exist between areas receiving fertilizer and the protected areas such as wetlands. These are intended to intercept nutrients in surface runoff. Other BMPs currently being tested on the Pelaez & Sons Ranch as part of a UF-IFAS study include increased water retention, nutrient management, fencing cattle out of waterways, and providing alternative water sources. My study is intended to provide insight on the effectiveness of increasing water retention in drainage ditches to reduce nutrient losses. A B Figure 3-2 Photos of study ditches on the Pelaez & Sons Ranch. A) Site 4. B) Site 5. Study Site Description Two of the primary ditches were selected for my study: One ditch is dominated by Pickerelweed (Pontederia cordata) and drains a small wetland (area = 25 ha), while the second ditch with almost no emergent vegetation drains a large portion of the ranch (area = 252 ha). Here onwards, the former ditch will be referred to as Site 4, and the latter ditch as Site 5 (Figure 3-2). A map of the study ditches and drainage areas is shown in Figure 3-3. In addition to drainage area and in-stream vegetation, the two ditches also

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52 differ with regards to the drainage area fertilizer application history, forage types, soils and ditch characteristics including water depth, channel size, and physical and chemical properties of the sediment. Figure 3-3 Map of Pelaez & Sons Ranch including study site drainage basins, drainage ditches, and grassed swales. Site Soils Soils in the two drainage areas consist primarily of Immokalee fine sand and Basinger fine sand (Table 3-1, Figure 3-5).

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53 Figure 3-4 Pastures and planted forage grasses on the Pelaez & Sons Ranch. Table 3-1 Six soil series are present on the ranch and in the ditch drainage basins. Area (ha) Soil Series Site 4 Basin Site 5 Basin Ranch Immokalee fine sand 11.2 135.7 351.0 Basinger fine sand 13.6 69.6 86.7 Myakka fine sand 24.7 59.0 Valkaria fine sand 12.3 66.9 Floridana, Riveria, and Placid soils, depressional 6.0 36.8 Basinger and Placid soils, depressional 4.0 18.8 Total 24.8 252.2 619.2

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54 Figure 3-5 Soils located within the Pelaez & Sons Ranch and the study drainage ditch basins. Reddy et al. (1995) analyzed 10 stream sediments and 20 wetland soils from locations in the S-154 basin, including one stream and one wetland site on the Pelaez & Sons Ranch. Average soil parameters for the S-154 basin are included in Table 3-2.

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55 Table 3-2 Average stream sediment and wetland soil properties from 10 streams and 20 wetlands in the S-154 sub-basin compared to results from the current study site ditches. S-154 Basin * Pelaez Ranch Soil Property Stream Wetland Site 4 Site 5 pH 6.61 6.21 4.98 5.11 Total Organic Carbon (TOC) (mg g -1 ) 105.00 110.00 Organic Matter (LOI) (mg g -1 ) 285.05 32.56 Bulk Density (g cm -3 ) 0.61 0.46 0.33 1.26 Tp ox (mg kg -1 ) 502 615 140 47 Fe ox (mg kg -1 ) 2544 2616 411 487 Al ox (mg kg -1 ) 569 695 1240 224 Ca KCL (mg kg -1 ) 3319 3809 Mg KCL (mg kg -1 ) 604 463 * (Reddy et al., 1995) The sediment samples taken from the Pelaez Ranch are slightly acidic, which indicates that calcium or magnesium bound P will not be available. The bulk density of Site 5 is much higher than that of Site 4. Bulk densities are known to range from 0.1 for organic peat to 1.5 for mineral soil (Kadlec and Knight, 1996). The sediment at Site 4 is mostly organic, while at Site 5 it is mostly mineral. Though the value determined from LOI (loss on ignition) includes TOC, elemental carbon, and weight loss due to the breaking up of silicates and carbonates, the large differences in OC values clearly indicate that Site 4 sediments contain much more organic matter than those at Site 5. For the Dry Lake dairy, located in the S-154 sub-basin, Reddy et al. (1995) also presented information on P pools in stream sediments and wetland soils. Table 3-3 illustrates the relative importance of iron and aluminum bound P. P associated with humic and fulvic acids can be hydrolyzed to bioavailable forms. The calcium and magnesium bound P pool is typically unavailable due to the low pH of most soils in this region.

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56 Table 3-3 Stream sediment and wetland soil phosphorus partitions for Dry Lake Dairy, located in the S-154 sub-basin Stream sediments Wetland soils Phosphorus pool mg kg -1 mg kg -1 Labile inorganic P 18.4 0.6 Fe/Al bound inorganic P 255.2 104.6 Humic and fulvic acid organic P 52.6 49.0 Ca/Mg bound inorganic P 435.9 55.4 Resistant organic P 114.9 110.4 (Reddy et al., 1995) Ditch Vegetation The vegetation characteristics at Site 4 are similar to an emergent wetland. The dominant plant is pickerelweed (Pontederia cordata) though wild water-pepper (Polygonum hydropiperoides) is also present. When water is present, duckweed (Lemnaceae) also occurs in areas of open water. Only water hyacinth (Eichhornia crassipes) and duckweed occur at Site 5, but their presence is transitory, since water flow may carry these floating plants downstream. Janse and Van Puijenbroek (1998) suggest that duckweed dominates only in highly eutrophic drainages. The presence of this floating plant at both study sites may indicate high P loading. Ditch Cleaning To ensure water flow through drainage ditches, annual cleaning is often necessary (Janse and Van Puijenbroek, 1998). Cleaning involves removing floating and emergent macrophytes and a portion of the detrital layer from the ditch. The large drainage ditches on the study ranch are periodically cleaned, though not on an annual basis. A portion of the ditch at Site 5 was cleaned in June, 2004. A backhoe was used to remove water hyacinth and sediment. The removed material was placed 2–3 m away from the sides of the ditch.

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57 Recently dredged ditches may contain little sediment carbon, due to the removal of detritus and the top sediment layer (Nguyen and Sukias, 2002). Drain cleaning likely influences plant P uptake and P sorption with sediment (Bowmer et al., 1994). Nguyen and Sukias (2002) found that after 3 months, cleaned drains had lower P contents and retained less P than drains that had not been cleaned for 5 years. The authors attributed this to the loss of accumulated P, and the loss of sorption sites associated with organic C, Al and Fe. Weather Conditions during the Study Period The daily average temperature during the study (10/22/04 – 10/29/04) was 23C (low 17C, high 29C). No rainfall occurred during the study period. Cumulative water loss through evapotranspiration was 1.81 cm. Field Preparation The nutrient concentration of the water inside field-situated benthic mesocosms (Figure 3-2) was altered to promote P flux across the sediment-water interface. Four treatments, representing two additions and two dilutions of nutrients in the mesocosms, were tested in triplicate across two drainage ditches. Two treatments were achieved by dosing the water inside the mesocosms with a fertilizer (KH 2 PO 4 ) solution such that two increased P concentrations would be represented. The other two treatments involved diluting the water inside the mesocosm with different quantities of deionized water such that two reduced P concentrations were represented. A treatment summary is presented in Table 3-4 and Table 3-5. The four treatments were monitored over 7 days and compared to an experimental control to determine if P uptake or release occurred. A one week period was chosen because: it was believed the mesocosms would no longer be representative after that period; the typical hydraulic residence time of the

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58 ditches is shorter than one week; model results have shown that molecular diffusion alone can achieve 90% equilibration with porewater dissolved P in 3 days (Webster et al., 1998); and it was believed that the majority of P adsorption, desorption, and biological assimilation would occur in less than one week. For these reasons, it was not believed that more than one week would be necessary. Table 3-4 Summary of P spike treatments at the two drainage ditches Site Treatment SRP Mass Before Treatment (mg) SRP Mass Added (mg) SRP Mass Measured After Treatment (mg) High spike 44 255 300 Site 4 Low spike 56 145 200 High spike 23 255 280 Site 5 Low spike 21 130 155 Table 3-5 Summary of dilution treatments at the two drainage ditches Site Treatment Dilution Attempted Dilution Achieved High dilution 75% 85% Site 4 Low dilution 50% 63% High dilution 75% 74% Site 5 Low dilution 50% 50% Mesocosm Preparation A plasma cutter was used to remove the top and bottom of thirty 55-gallon steel drums. After cleaning the drums with an etching solution and a pressure hose, they were coated with Dura-Plate epoxy paint. The paint, which was strong enough to avoid becoming chipped or scratched, ensured the mesocosms were nonreactive. Both the inside and outside of the drums were painted. The finished mesocosms are shown in Figure 3-6. The cross-sectional area of each mesocosm was 0.27 m 2 (2.89 ft 2 ). Installation Each mesocosm was positioned by hand, and a backhoe was used to exert a straight downward force pushing them into the sediment 6 inches. Using a backhoe to insert mesocosms isolated a portion of the ditch-bottom without significantly disturbing it.

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59 Since the mesocosms could not be inserted into the ditch bottom by hand, metal drums were used in my study. These drums could withstand the force of the backhoe without crumpling. Visual inspection indicated that sediment was not suspended in this process. Mesocosms were positioned randomly such that they were at least 0.66 m (2 ft) from each other. The average minimum and furthest distances between mesocosms were 2.0 m and 37.7 m respectively. The mesocosm positions are shown in Figure 3-7. Figure 3-6 Mesocosms after being prepared for installation. Nutrient Additions Grab samples of ambient ditch water were taken on 9/18/04. It was assumed that the ambient SRP concentration on 10/22/04 would be similar in magnitude. Once water volume within each mesocosm was estimated on 10/22/04 through water depth measurements, the ambient SRP data from 9/18/04 was used to estimate the necessary quantity of a fertilizer solution (KH 2 PO 4 ) to add to achieve desired water-column SRP

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60 concentrations. Ammonium fertilizer (NH 4 Cl) was also added such that the N:P ratio in the water-column was maintained. The water-column was slowly mixed with a PVC rod. Figure 3-7 Mesocosm locations at the two study ditches (top, Site 4 and bottom, Site 5). The labels indicate treatments. HS = high spike, LS = low spike, D75 = high dilution, D50 = low dilution, C = control. Ambient conditions were not constant between the two dates, however. The discrepancy coupled with an initial mistake in water depth measurement resulted in starting SRP masses different from those desired. Regardless, the actual loading was sufficient to demonstrate flux across the sediment-water interface. Dilution Any difference in hydraulic head between the inside and outside of the mesocosms would promote flow through the bottom of the mesocosm and invalidate the assumption that the ditch-bottom was undisturbed. To maintain the hydraulic head during dilution, a unique dilution procedure was followed. Water in the mesocosm was displaced by deionized water in a plastic bag. Plastic tubing connected the inside and outside of the mesocosm such that the slight head difference generated by the gradual addition of deionized water would discharge the displaced water through the plastic tubing. Once

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61 equilibrium was established, the remaining water in the mesocosm was allowed to mix with the deionized water. The dilution method is illustrated in Figure 3-8. A comprehensive analysis conducted by National Testing Laboratories, Ltd. indicated no detectable metals, nutrients, or other inorganic chemicals in the deionized water used for dilution. Figure 3-8 Process used to dilute the water inside the mesocosms Unfortunately, the plastic bag was slightly torn while performing this procedure for one of the replicates for a treatment at Site 4 (50% dilution replicate). By releasing the deionized water before full displacement, not only was the actual dilution amount unknown, but the head difference between the inside and outside of the mesocosm was

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62 large enough that water likely flowed out of the bottom of the mesocosm. The assumption of an isolated, undisturbed benthic layer was violated, so the data from this mesocosm were not included in the data analysis. Tracer Addition By adding a conservative tracer to the water-column of all experimental mesocosms, the assumption of hydraulic isolation could be tested. If water from outside the mesocosm seeped inside, the conservative solute concentration would become diluted over time. By quantifying the dilution amount, other nutrient concentrations could later be adjusted if necessary. Bromide was chosen as the best choice for a conservative tracer (see Appendix). A 2000 mg l -1 bromide stock solution was created in the lab using photographic grade potassium bromide (KBr) and deionized water. Water depth in the field was used to estimate volume and the quantity of stock solution necessary to elevate mesocosm bromide concentrations to 5 mg l -1 . Sampling Five water-column samples were taken from each mesocosm and the ditch over the course of seven days (t = 0, 1, 2, 4, 7 days). Samples were collected by hand using 40 mL syringes. The syringes were washed three times with site water before each sampling. Water was drawn from several locations within each mesocosm for each sampling, since taking composite samples would decrease any minor variability within each mesocosm. The water samples were analyzed for soluble reactive phosphorus (SRP), total phosphorus (TP), total Kjeldahl nitrogen (TKN), nitrate/nitrite (NO x ), ammonium (NH 4 ), and bromide (Br). Water quality samples to be analyzed for SRP, NOx, and NH 4 were passed through 0.45 m filter papers, and acidified. One drop of concentrated H 2 SO 4 was added for every 20 mL of sample water. Water quality samples

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63 to be analyzed for TP and TKN were acidified, but not filtered. Bromide water quality samples were neither filtered nor acidified. Filtering and acidification took place in the field immediately after samples were taken. Several coolers filled with ice were used to store samples for the study period. Ice was replenished daily, and the samples were moved to a 4C cooler room once in Gainesville. All water samples were analyzed for SRP, TP, TKN, NO x , and NH 4 within 28 days from the time they were sampled. Site Characterization After seven days the plants inside each mesocosm were clipped and sorted according to above-water biomass and below-water biomass. Biomass below the sediment surface was not collected. Soil cores were taken from inside each mesocosm to determine bulk density, water content, soil pH, organic matter, water-extractable P, TP, and oxalate-extractable P, Al, and Fe contents. Laboratory Analyses Water Quality Analysis Water total phosphorus (TP) TP of water samples was determined by adding 0.5 mL 11 N H 2 SO 4 and 0.15 g potassium persulfate (K 2 S 2 O 8 ) to 10 mL aliquots of each sample. Samples were digested in an autoclave at 121C and 15 psi for 60 minutes. The digested solutions were stored in 20 mL scintillation vials at room temperature until being analyzed with a Technicon Autoanalyzer (EPA Method 365.1). For every 20 samples or less, one sample was digested twice and one sample was rerun with an added known quantity of nutrient to ensure consistent analysis (EPA, 1993).

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64 Water soluble reactive phosphorus (SRP) Samples that were filtered in the field with 0.45 m filter paper were analyzed for SRP using a Technicon Autoanalyzer (EPA Method 365.1) (EPA, 1993). Total Kjeldahl nitrogen (TKN) 0.3 g Kjeldahl salt catalyst and 0.5 mL concentrated H 2 SO 4 were added to 10 mL of each unfiltered water sample. The samples were placed on a digestion block set to 160C for 2 hours, and then set to 360C for 30 minutes. Before the temperature increase, glass funnels were placed on the digestion tubes to allow for sulfuric acid fume recirculation. After digestion, 10 mL of deionized water was mixed with each sample. TKN of the digested samples was determined using a Technicon Autoanalyzer (EPA Method 351.2). For every 20 samples or less, one sample was digested twice and one sample was rerun with an added known quantity of nutrient to ensure consistent analysis (EPA, 1993). Ammonium (NH 4 ) and nitrate and nitrite (NO 3 +NO 2 ) Samples that were filtered in the field with 0.45 m filter paper were analyzed for ammonium (EPA Method 350.1) and nitrate and nitrite (EPA Method 353.2) (EPA, 1993). pH Water samples were stirred and pH was read with a calibrated pH meter (ORION SA 720, Fisher AR50). Analysis took place in the lab one week after sampling. Bromide Water samples were stored at 4C until they could be analyzed to prevent evaporative losses. Bromide was analyzed using high-pressure liquid chromatography using a Dionex RFIC Ion-Pac AS4A-SC column and an ultraviolet-visible (UV-Vis)

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65 detector with a detection wavelength of 205 nm. A 20 mM sodium borate (Na 2 B 4 O 7 0H 2 O) solution was used for the mobile phase, and the flow rate was 1.0 mL min -1 . Other studies have shown this method to be accurate (Annable et al., 1998; Martinez and Wise, 2003). The lowest standard tested was a 200 ppb solution, and the response was clearly visible. The bromide concentration in the field samples was 1 to 2 orders of magnitude higher than the lowest standard. Repeated analysis of samples showed variability less than 200 ppb. An example of the sample response to bromide is shown in Figure 3-9. Figure 3-9 Water sample bromide response using a Dionex RFIC Ion-Pac AS4A-SC column.

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66 Sediment Analysis Moisture content and bulk density The moisture content was determined for sediment samples collected from each of the 30 mesocosms. Each sample was homogenized, and approximately 40 g of each wet sediment sample was placed into aluminum weighing pans. Each tin was weighed with and without the sediment sample. The samples were reweighed after drying in a 70C oven for 72 hours. Moisture content was calculated as the weight difference before and after drying divided by the wet sample weight. Bulk density was calculated as the ratio of dry versus wet sample weights, multiplied by the wet sediment core weight, and divided by the volume of the sediment core. pH For each sample, 10 g sediment and 20 mL deionized water were mixed and allowed to equilibrate for 30 minutes. Samples were stirred and pH was read with a calibrated pH meter (ORION SA 720, Fisher AR50) (Hanlon, 1994; Thomas, 1996). Organic matter (LOI) For each sample, 0.5 g dried ground sediment was weighed and placed in a muffle furnace. The furnace temperature was maintained at 250C for 30 minutes, then was raised and maintained at 550C for 4 hours. Organic matter, as determined by loss on ignition (LOI), is the percent difference in the ash and original sediment sample weights (Andersen, 1976). Total phosphorus (TP) 20 mL 6 M HCl was added to the ash samples generated from loss on ignition. These samples were dried on a hot plate at 120C. The samples were cooled, filtered through Whatman #41 filter paper, and mixed with 50 mL deionized water. Samples

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67 were digested using the method described above for water TP. A Technicon Autoanalyzer was used to analytically determine the total P concentrations in the digested solutions (EPA Method 365.1) (Andersen, 1976; Jackson, 1962; EPA, 1993). Water-extractable phosphorus For each wet sediment sample, 2 g dry weight equivalent sediment was mixed with 20 mL deionized water such that a 1:10 soil (g) water (cm 3 ) solution was created. The samples were shaken for 1 hour, centrifuged at 6000 rpm for 10 minutes, and passed through 0.45 m filter papers. The filtrates were analyzed for P using a Technicon Autoanalyzer (EPA Method 365.1) (Luscombe et al., 1979; EPA, 1993). Water-extractable P represents the reversibly surface-sorbed P and is roughly equivalent to labile P (McGechan, 2002). Oxalate-extractable iron, aluminum, and phosphorus Oxalate extractions were conducted on sediment samples using standard methods (McKeague and Day, 1966; Sheldrick, 1984). Sediment samples with a 0.5 g dry equivalent were shaken in the dark for 4 hours with 20 mL of oxalate reagent. The oxalate reagent contained ammonium oxalate and oxalic acid and had a pH of 3.0. After shaking, the samples were centrifuged at 6000 rpm for 10 minutes. The samples were filtered in the dark with 0.45 m filter paper. The oxalate extractions were immediately given to the Analytical Research Laboratory in Gainesville and analyzed within 24 hours. Iron, aluminum, and P in the extractions were measured with an ICP (modified EPA Method 200.7) (EPA, 1983). Biomass Analysis Submersing the vegetation collected below the water line into demarcated buckets filled with water and measuring the volume of water displaced provided a measure of

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68 vegetation volume. Dry biomass was determined by weighing the vegetation after it had been placed in a drying room for 29 days. Data Adjustment Several techniques were employed to adjust the raw nutrient concentration data gleaned from the water samples. The nutrient data were adjusted to compensate for evapotranspiration, dilution from outside the volume enclosed by the mesocosm, and water loss. Since the effects of these processes were measured, compensating the raw data is logical and provides realistic results. Figure 3-10 illustrates one instance where the raw nutrient data were adjusted to provide more meaningful results. A brief description of these adjustments follows. 0.000.200.400.600.801.001.200.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Load (mg) Unadjusted Compensated for ET,Dilution & Water Loss Figure 3-10 Example of nutrient loads corrected for ET, dilution from outside the volume enclosed by the mesocosm, and water loss (Site 4 high spike treatment). The effects of these three processes can be removed since the relative contribution of each is known.

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69 Evapotranspiration During the study period (10/22/04 to 10/29/04), the reference evapotranspiration computed by the modified Penman method was 0.713 inches (1.81 cm). The evapotranspiration was estimated from weather parameters at a nearby UF-IFAS weather station in Ona. Daily values are listed in Table 3-6. Table 3-6 Measured daily evapotranspiration at the ONA weather station. Date ET (in) ET (L) * 10/22/04 0.107 0.684 10/23/04 0.101 0.667 10/24/04 0.102 0.687 10/25/04 0.107 0.684 10/26/04 0.101 0.674 10/27/04 0.104 0.641 10/28/04 0.091 0.628 Total 0.713 4.664 * Since the cross sectional area of the mesocosms is known to be 0.268 m 2 , the volume of water lost to ET can be quantified. Each volume is the average quantity of water lost to ET between the listed and the next day. Evapotranspiration would be expected to increase the concentration of dissolved solutes in the mesocosms. Since the amount of ET is known, the extent to which the measured nutrient concentrations would increase can be determined accurately. The measured nutrient concentrations can be adjusted to remove the effect of ET. The effect of ET is apparent in Figure 3-11, where the measured concentration of bromide, a conservative solute, is compared to the concentration calculated if ET were the only influencing factor. At Site 5, the observed increase in bromide concentration appears to be due to ET. Data in Figure 3-11 substantiates the adjustment of all nutrient values for ET, since ET affects all dissolved solutes to the same degree.

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70 55.566.577.580.01.02.03.04.05.06.07.0Time Elapsed (days)Br Concentration (mg L-1) Average Measured [Br] in Site 5Mesocosms Average [Br] expected in Site 5Mesocosms due to ET Figure 3-11 Comparison of measured bromide concentrations and those expected to occur from ET losses at Site 5. Error bars represent one standard deviation. Dilution from outside the Volume Enclosed by the Mesocosm Insertion of the mesocosm with a backhoe to 6 in (15 cm) in the ditch bed minimized its movement. Since bromide is a conservative tracer in water, the concentration would decrease if water from the outside moved into the volume enclosed by the mesocosm, but would remain unchanged if no water were exchanged (inflow or outflow). At Site 5 (Figure 3-11), it appears that ET explains most of the Br concentration change, indicating that water exchange through the mesocosm bottom was minimal. In contrast to Site 5, considerable water exchanges (inflow) occurred at Site 4 (Figure 3-12). ET-adjusted Br concentrations showed a slight increase while actual measured concentrations showed continued decline. By comparing the measured Br concentration to that expected if ET were the only influencing factor, the degree of dilution can be calculated for each mesocosm.

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71 345678910110.01.02.03.04.05.06.07.0Time Elapsed (days)Br Concentration (mg L-1) Average Measured [Br] inSite 4 Mesocosms Average [Br] expected in Site4 Mesocosms due to ET Figure 3-12 Comparison of measured bromide concentrations and those expected to occur from ET losses at Site 4. Dilution from water outside the mesocosm is evident. Error bars represent one standard deviation. For each mesocosm at Site 4, the dilution computed through the measured Br concentration occurred steadily over the study period. The dilutions estimated from the Br data were plotted to develop a dilution trend for each mesocosm. Each trendline was used to determine the daily dilution amount. The daily dilution amount was used to adjust the measured nutrient concentration. Dilution effects could be separated out from the measured data, since the daily ambient nutrient values in the ditches were known. It should be noted that the initial nutrient concentration remained unchanged. The concentration for the second sampling event was adjusted through Equation 3-1. The concentration for the last sampling period was adjusted through Equation 3-2. For brevity, equations for the other two sampling periods are not shown. These equations compensate for the effects of water entering the volume enclosed by the mesocosm and the effects of evapotranspiration.

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72 iDCoECCa2222* (3-1) iDEECoEECoEECoECoCCa)(4553442332255 (3-2) iiiBrETBrD (3-3) (3-4) iiDE1 Ca i = Nutrient concentration compensated for dilution and ET on the ith sampling event Ci = Measured nutrient concentration on the ith sampling event Co i = Average ambient concentration in ditch during ith sampling event D i = Bromide dilution amount by ith sampling event Br i = Bromide concentration from linear trend for ith sampling event BrET i = Hypothetical bromide concentration for ith sampling event if ET were the only influencing factor E i = Ambient water exchange amount by ith sampling event An example of dilution and ET compensation is shown in Figure 3-13. At Site 4, dilution due to water entering from outside the mesocosms occurred, which caused the measured SRP concentrations to be lower than that without dilution. Examination of Br data (not shown) indicates that the dilution was highest on the second sampling event and decreased with time. The disparity was expected since the concentration gradients would be highest right after addition of nutrient solution. Adjusting for dilution and ET allows one to obtain a better understanding of the extent of changes in nutrient concentrations resulting from the different physical, chemical, and biological processes. Water Loss To adequately assess nutrient uptake or release, the mass or load of nutrient needs to be compared to the area of resident bottom sediment in the mesocosms available for physical, chemical, and biological processes. Nutrient load is determined by multiplying the concentration by the volume of water in the mesocosm.

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73 0.01.02.03.04.05.06.00.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Concentration (mg L-1) Average Measured SRP Average Compensated SRP Figure 3-13 Effects of evapotranspiration and dilution can be removed from the measured nutrient data since the relative contribution of each is known (Site 4 high spike treatment). 01020304050607080901000.01.02.03.04.05.06.07.0Time Elapsed (days)Water Volume (L) Site 5 Mesocosms Site 4 Mesocosms Figure 3-14 Water level inside each mesocosm dropped steadily with time. Average volumes of all mesocosms are presented. The volume of water in the mesocosms decreased over time (Figure 3-14). Therefore a large nutrient load reduction can be attributed to water leaving the system.

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74 This mass can be excluded from the calculated load. The quantity of water leaving from the bottom of each mesocosm was computed by subtracting the ET losses from the total losses. The nutrient concentration of the water leaving the system each day was assumed to be the same as the measured concentrations within the mesocosm. Therefore, the mass of nutrients that left the system was added to the nutrient load compensated for ET and dilution.

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CHAPTER 4 RESULTS Measurements Effectiveness of Mesocosm As described in the previous section, certain issues arise when using this type of in-situ measurement strategy. Evaporation will act to increase solute concentrations, but this quantity is known so it can be excluded. Since water inside the mesocosm was diluted from outside, it appears that the assumption of low hydraulic conductivity at a sediment depth of 6 in (15 cm) is invalid. Using bromide as a conservative tracer, the effect of dilution was separated from those caused by different processes within the mesocosm. Water lost from below the mesocosm also occurred in all mesocosms. Since the daily water level was recorded, the lost nutrient load was calculated and added to the calculated nutrient load each day. The only means to prevent water exchange, either dilution or water loss, is to seal the bottom of the mesocosm. However, sealing the bottom is difficult if undisturbed sediment is desired. As a means to isolate a portion of the sediment bottom without greatly disturbing it, the mesocosm proved effective. Sediment suspension was not observed during installation, and the mesocosms maintained their integrity under the force of the backhoe. The Dura-Plate epoxy paint, which coated the steel drum cylinders, did not chip, crack, or wear off. The mesocosms walls appeared to remain inert. Furthermore, the nutrient concentrations in control mesocosms nearly mimicked the nutrient concentrations 75

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76 measured in the ambient ditch. Four figures (Figure 4-1–Figure 4-4) are included to show that the isolated portions of the ditch within the mesocosms closely resembled ambient conditions observed in the ditch. Figure 4-1 and Figure 4-2 show the similarities in measured SRP between the control mesocosms and the outside ditch. Figure 4-3 and Figure 4-4 show the similarities in measured TKN between the control mesocosms and the outside ditch. 0.00.10.20.30.40.50.60.70.80.91.00.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Conc (mg L-1) Ambient Control Figure 4-1 SRP measured in control mesocosms at Site 4 resembled SRP measured from ambient ditch water. The variability in ambient water samples may be an indication of variable conditions within the ditch. Error bars represent one standard deviation.

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77 0.00.10.20.30.40.50.60.70.80.91.00.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Conc (mg L-1) Ambient Control Figure 4-2 SRP measured in control mesocosms at Site 5 resembled SRP measured from ambient ditch water. The water depth may have been greater at the ambient water sampling locations than the control mesocosms. Error bars represent one standard deviation. 0.01.02.03.04.05.06.07.08.09.010.00.01.02.03.04.05.06.07.0Time Elapsed (days)TKN Conc (mg L-1) Ambient Control Figure 4-3 TKN measured in control mesocosms at Site 4 resembled TKN measured from ambient ditch water, supporting the notion that the mesocosms were effective. Error bars represent one standard deviation.

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78 0.01.02.03.04.05.06.07.08.09.010.00.01.02.03.04.05.06.07.0Time Elapsed (days)TKN Conc (mg L-1) Ambient Control Figure 4-4 TKN measured in control mesocosms at Site 5 resembled TKN measured from ambient ditch water. Error bars represent one standard deviation. Phosphorus Uptake and Release Four treatments, representing two additions and two dilutions of nutrients in the mesocosms, were tested in triplicate at each study site (Table 3-4 and Table 3-5). The four treatments were monitored over 7 days and compared to an experimental control to determine if P uptake or release occurred. The nutrient loadings achieved in the mesocosms were sufficient to demonstrate flux across the sediment-water interface. Phosphorus uptake over time Phosphorus (P) retention is evident for the two treatments where the mesocosm water was spiked with a KH 2 PO 4 solution. Table 4-1 summarizes the spike treatment results for both study ditches.

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79 Table 4-1 Net uptake for all spike treatments and controls. Standard deviations between replicates are included. Site 4 Treatment Site 5 Treatment Parameter High Spike Low Spike Control High Spike Low Spike Control Initial Concentration (mg l -1 ) 4.930 0.145 3.010 0.771 0.548 0.100 2.932 0.090 1.587 0.079 0.215 0.014 Initial Load (mg m -2 ) 1119.04 150.98 743.09 203.78 132.59 16.59 1065.00 116.87 581.00 43.03 70.32 7.02 Final Load (mg m -2 ) 524.23 13.04 400.55 105.42 60.23 27.47 922.39 154.20 476.36 81.15 46.69 13.60 Uptake / Release (mg m -2 ) 594.81 342.54 72.36 142.61 104.64 23.63 % Uptake / Release 53.2 46.1 54.6 13.4 18.0 33.6 Fifty-three percent of the original SRP load was retained by adsorption, diffusion, and biological uptake at Site 4 (Figure 4-5). Since the influences of ET, dilution, and water loss through the bottom of the mesocosm have been excluded (see previous section on Data Adjustment), P diffusion, sorption and desorption, and biotic uptake are the only processes that could have resulted in the clear decline in P as shown in Figure 4-5. The last data point (7 days) shows 525 mg SRP m -2 remaining in the water-column, and it appears that retention may be reaching an asymptote of approximately that value, indicating that SRP concentrations in the mesocosm are close to a new equilibrium. Surely not a true asymptote, further P retention after 7 days likely will be much slower. It is interesting to note that the standard deviation between the three replicates for this treatment reduces over time. The change in standard deviation suggests that a common floodwater SRP load may be reached regardless of initial loading.

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80 02004006008001000120014000.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Load (mg m-2) High Spike Control Figure 4-5 High nutrient spike and experimental control phosphorus loads over the course of the experiment at Site 4. Error bars represent one standard deviation. 02004006008001000120014000.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Load (mg m-2) Low Spike Control Figure 4-6 Low nutrient spike and experimental control phosphorus loads over the course of the experiment at Site 4. Error bars represent one standard deviation. For the low spike (66% of high spike SRP load), SRP load declined considerably over time as shown in Figure 4-6. The last data point (7 days) shows 400 mg SRP m -2

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81 remaining in the water-column, indicating a net reduction of 46% of the initial SRP mass in the mesocosm. As with the previous treatment, the decline in water-column SRP load is rapid during the first half of the study period followed by a gradual decline. The observed rate of SRP load reduction started at 61 mg m -2 d -1 between the first two measurements, and dropped to 21 mg m -2 d -1 by the last two measurements. The observed rate of SRP load reduction for the high P spike treatment began and ended at 194 and 39 mg m -2 d -1 , respectively. It appears that the SRP reduction rate is proportional to the SRP load in the water-column. Using the data from the high P spike treatment at Site 4, reduction rate is related to initial SRP load by Equation 4-1: 175.33 Load) 0.3279(SRP = RateReduction (R 2 = 0.9976) (4-1) where Reduction Rate is in mg m -2 d -1 and SRP Load is in mg m -2 . Using the data from both P spike treatments, Equation 4-2 was developed: 101.82 Load) 0.2511(SRP = RateReduction (R 2 = 0.8882) (4-2) 02004006008001000120014000.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Load (mg m-2) High Spike Low Spike Control Figure 4-7 High and low nutrient spike and experimental control phosphorus loads over the course of the experiment at Site 5. Error bars represent one standard deviation.

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82 The SRP load reduction observed at Site 5 is less dramatic than those observed at Site 4. Figure 4-7 shows the observed load reduction over time for both loading treatments compared to the experimental control. Approximately 15.5% of the initial SRP load was retained over 7 days for both high and low P spike treatments at Site 5. The reasons for the difference in retention between Site 4 and Site 5 are discussed in a later section. Phosphorus release over time The results from the two dilution treatments (high and low), were analyzed to determine the P release over time at the two ditches. The water in the mesocosms was diluted with deionized water (SRP = 0.0 mg l -1 ) approximately 50 and 75% to implement two dilution treatments. A summary of both dilution treatments at both study ditches is shown in Table 4-2. At Site 4 P release to the water-column from sediment was rapid immediately after dilution and then slowed after 1 to 2 days (Figure 4-8, Figure 4-9). Since the first water samples were collected 4 hours after treatment, a calculated initial load is also shown in Figure 4-8 through Figure 4-11. The initial load calculation is based on measured loads before dilution and the quantity of deionized water used for displacement. For the low dilution (approximately 50%) treatment at Site 4, the net release of SRP into the water-column was almost 45% of the original load in the mesocosm (Figure 4-8). It is also apparent that the SRP load in the experimental control is declining over time (Figure 4-8). The control indicates that P uptake was occurring in the ditch under ambient conditions during the study period. Results indicate that SRP load in the treatment mesocosms may not be expected to return to the pre-treatment values.

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83 Table 4-2 Net uptake / release for all dilution treatments. Site 4 Treatment Site 5 Treatment Parameter Low Dilution(~50%) High Dilution (~75%) Low Dilution (~50%) High Dilution (~75%) Initial Concentration (mg l -1 ) 0.287 0.088 0.135 0.082 0.139 0.030 0.089 0.020 Initial Load (mg m -2 ) 50.57 31.43 39.32 20.27 Load after 4 days (mg m -2 ) 100.79 56.17 110.27 32.53 49.12 9.09 38.66 3.50 Final Load (mg m -2 ) 110.48 36.94 102.57 33.43 37.35 12.46 15.65 7.69 Uptake / Release (7 day) (mg m -2 ) -59.91 -71.14 1.97 4.62 Uptake / Release (4 day) (mg m -2 ) -50.23 -78.84 -9.80 -18.39 % Uptake / Release (7 day) -43.4 -33.0 2.5 6.0 % Uptake / Release (4 day) -36.4 -36.6 -12.4 -23.9 Standard deviations between replicates are included. The initial load was estimated from the pre-treatment concentration, water volume, and displaced water volume. P uptake is positive, and release is negative. Percent uptake / release is relative to pre-treatment measurements. Net uptake / releases after 4 days and after 7 days are included for comparison. For the high dilution (approximately 75%) treatment at Site 4, the net release of SRP into the water-column accounted for a third (33%) of the total initial mass of SRP in the mesocosm before dilution (Figure 4-9). Though the magnitude of P release was greater for the high dilution treatment than for the low dilution treatment, the water-column SRP load returned to the same value (approximately 106 mg m -2 ) under both dilution treatments at Site 4 (Figure 4-8 and Figure 4-9). It appears that a single equilibrium is reestablished in the mesocosms after dilution regardless of dilution amount. Results from the two dilution treatments also indicate that the magnitude of P release is proportional to the starting load at Site 4.

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84 The similar final SRP mass for both treatments reveals that the drainage ditch system is expected to return to this equilibrium for similar flow and nutrient loading regimes. Similar equilibriums indicate that the maximum short-term P release limit had been reached after almost 2.5 days. The short-term limit may be related to conditions observed in the field. Hurricane level rainfall in September 2004 flooded the ranch, and water in the drainage ditches was still moving imperceptibly slowly by late October. Though hurricane level rainfall is not annual in the region, heavy late summer rains are typical. By mid to late summer, most of the nutrients have typically been flushed out of the system. The P diffusion / desorption observed may be typical under similar late summer conditions. 0204060801001201401601802000.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Load (mg m-2) Control Low Dilution Estimated Initial Load Figure 4-8 Phosphorus release over time observed at Site 4 after ~50% dilution. Values from the experimental control are included for comparison. An initial load immediately after dilution was calculated from the pre-treatment concentration, water volume, and displaced water volume. Error bars represent one standard deviation.

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85 0204060801001201401601802000.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Load (mg m-2) Control High Dilution Estimated Initial Load Figure 4-9 Phosphorus release over time observed at Site 4 after ~75% dilution. Values from the experimental control are included for comparison. An initial load immediately after dilution was calculated from the pre-treatment concentration, water volume, and displaced water volume. Error bars represent one standard deviation. 01020304050607080901000.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Load (mg m-2) Control Low Dilution Estimated Initial Load Figure 4-10 Phosphorus release over time observed at Site 5 after ~50% dilution. Values from the experimental control are included for comparison. An initial load immediately after dilution was calculated from the pre-treatment concentration, water volume, and displaced water volume. Error bars represent one standard deviation.

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86 01020304050607080901000.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Load (mg m-2) Control High Dilution Estimated Initial Load Figure 4-11 Phosphorus release over time observed at Site 5 after ~75% dilution. Values from the experimental control are included for comparison. An initial load immediately after dilution was calculated from the pre-treatment concentration, water volume, and displaced water volume. Error bars represent one standard deviation. Phosphorus release at Site 5 was not as dramatic as that observed at Site 4. Both release and uptake occurred under ambient conditions (Figure 4-10 and Figure 4-11). Uptake appears to have confounded the quantification of P release. After 4 days, the released SRP mass was approximately 12 and 24% of the SRP load before dilution under the low and high dilution treatments, respectively. The calculated initial loads were used for the release calculation. However, after 7 days the SRP load in the mesocosms declined to values lower than the initial treatment loads for both dilution treatments indicating a net uptake of nutrients. The release observed at Site 5 (Figure 4-10 and Figure 4-11) does not mimic the release observed at Site 4 (Figure 4-8 and Figure 4-9), where the majority of release occurred after 1 to 2 days. It is possible that P release was inconsequential at Site 5. Regardless, the results from Site 5 indicate that the uptake and release processes are transitory in nature. Phosphorus release to the water-column may

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87 be controlled by hydraulic retention time as much as starting P load. Under short hydraulic residence times, P may be released to the water-column, where P may be adsorbed again if the residence time were extended. Implications of these results are discussed later. Uptake and release over time relative to initial concentrations Whereas the magnitudes of P retention over time are considerably different between the spike and control treatments, comparisons on a similar scale provide some interesting insights. For each treatment, loads were divided by the initial measured load such that a unitless scale value could be compared between treatments. The actual retention between the high and low spike and control are different (Figure 4-5 and Figure 4-6), but the relative trends are nearly identical (Figure 4-12). Since relative uptake is similar, it may be possible to infer uptake rates for other potential starting loads as long as they are within the range of loads studied at Site 4 (133, 743, and 1119 mg m -2 ). The relative P uptake trends at Site 5 are similar as seen in Figure 4-13. However, the relative uptake in the spike treatments are not as closely related to uptake observed in the control as was the case at Site 4. Though uptake at Site 5 (Figure 4-7) was less dramatic than Site 4, it is still interesting to see that the relative uptake is similar between the two spike treatments at Site 5. The initial measured loads for these treatments were 70, 581, 1065 mg m -2 for the control, low and high spike treatments respectively. Phosphorus release relative to initial loads was also compared between treatments. For each treatment, SRP loads at several sampling events were normalized by dividing them with the initial measured load. The unitless values obtained were used to compare between treatments. The initial estimated loads for the dilution treatments (as seen in Figure 4-8–Figure 4-11) were not used. Though relative uptake rates are similar for each

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88 site, relative release rates are not. The trends in P release are different between dilution treatments at Site 4 (Figure 4-14). Relative P release trends are also different at Site 5 (Figure 4-15). As stated before, the trends in P retention for Site 4 are consistently increasing while for Site 5 they are bi-directional. Bi-directional trends for Site 5 indicate that depending on the residence time, the benthic system at Site 5 can act as a net sink or source of P. These differences demonstrate the need for separate approaches when modeling P uptake and release for the two ditches. 0.00.20.40.60.81.01.20.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Load / Initial SRP Load High Spike Low Spike Control Figure 4-12 Measured loads at Site 4 from both nutrient spike treatments and the experimental control relative to each initial condition.

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89 0.00.20.40.60.81.01.20.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Load / Initial SRP Load High Spike Low Spike Control Figure 4-13 Measured loads at Site 5 from both nutrient spike treatments and the experimental control relative to each initial condition. 0.00.51.01.52.02.53.03.50.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Load / Initial SRP Load Low Dilution High Dilution Control Figure 4-14 Measured loads at Site 4 from both dilution treatments and the experimental control relative to each initial condition.

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90 0.00.20.40.60.81.01.21.40.01.02.03.04.05.06.07.0Time Elapsed (days)SRP Load / Initial SRP Load Low Dilution High Dilution Control Figure 4-15 Measured loads at Site 5 from both dilution treatments and the experimental control relative to each initial condition. Sediment characteristics Most sediment properties were measured from composite samples with equal contributions from all 15 sediment cores taken from the mesocosms at each site. Water content was measured gravimetrically for all cores and composite samples. The average water contents from all samples at each site were nearly identical to the water contents of the composite samples. Bulk density was measured for all samples. The sediment at Site 4 consists of mostly organic peat, while the sediment at Site 5 is mostly mineral. The difference is visually evident in Figure 4-16. The Site 4 drainage ditch has the same ecological structure as an emergent wetland and contains many emergent macrophytes. The Site 5 drainage ditch does not support emergent plants, which is reflected by a less organic sediment. Bulk density, water content, and loss on ignition measurements (Table 4-3) support the previous characterization. The bulk density of Site 5 is much higher than that of Site 4. Bulk densities are known to

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91 range from 0.1 for organic peat to 1.5 for mineral soil (Kadlec and Knight, 1996). The water content of sediment at Site 4 is over twice that of Site 5. The organic material may act as a sponge, holding more water than the silts and sands at Site 5. Though the value determined from LOI (loss on ignition) includes TOC, elemental carbon, and weight loss due to the breaking up of silicates and carbonates, the large differences in OC values clearly indicate that Site 4 sediments contain much more organic matter than those at Site 5. A B Figure 4-16 Soil cores. A) Site 4. B) Site 5. The sediment samples taken from the Pelaez Ranch are slightly acidic, which indicates that calcium or magnesium bound P will not be biologically available (Table 4-3). Total P, water-extractable P, and oxalate-extractable P are higher at Site 4 than Site 5. The oxalate-extractable aluminum content is also higher in Site 4 sediments. Acidic conditions promote retention by aluminum (Patrick and Khalid, 1974). Reddy et al. (1996b) noted that P retention by Al oxides is the dominant retention mechanism in the Lake Okeechobee Basin. Site 4 sediments contain more P due to either their greater retention capacity, greater historical loading to the ditch, or both. Indeed, the unit area P

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92 fertilizer application was over twice as high in the Site 4 drainage basin in 2003 and 2004 compared to the Site 5 drainage basin (see Study Site Description in Materials and Methods). Table 4-3 Drainage ditch sediment characteristics for Sites 4 and 5. Parameter Site 5 Site 4 Bulk Density (g cm -3 ) average 1.263 0.326 Water Content (%) average 32.74 73.35 Water Content (%) composite 33.50 73.80 Loss on Ignition (LOI) (%) composite 3.26 28.50 Soil pH composite 5.11 4.98 TP (mg kg -1 ) composite 72.78 364.93 Water-extractable P (mg kg -1 ) composite 0.66 2.16 Oxalate-extractable P (mg kg -1 ) composite 46.76 140.36 Oxalate-extractable Fe (mg kg -1 ) composite 487.20 411.20 Oxalate-extractable Al (mg kg -1 ) composite 224.40 1240.40 Oxalate-extractable P (mmol kg -1 soil) composite 1.51 4.53 Oxalate-extractable Fe (mmol kg -1 soil) composite 8.72 7.36 Oxalate-extractable Al (mmol kg -1 soil) composite 8.32 45.97 Sorption indices Several sorption indices have been developed to relate soil and sediment test properties with maximum P uptake or the potential for P release to runoff. The Dutch saturation index (D ssp ), “Free Al and Fe,” and Q max (from the Langmuir isotherm) are discussed here. The Dutch saturation index can be determined from oxalate-extractable P, Al, and Fe. A D ssp greater than 25% is sufficient for P loss to occur (Schoumans and Groenendijk, 2000). Specifically a D ssp of 25% has been related to an equilibrium phosphorus concentration (EPC) of 0.1 mg l -1 , which has been designated as the acceptable limit for Dutch soils and sediments (Schoumans and Groenendijk, 2000). The commonly used definition of the D ssp is Equation 4-3.

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93 100*21oxoxoxSSPFeAlPD (4-3) where P ox , Al ox , and Fe ox are the oxalate-extractable phosphorus, aluminum, and iron respectively (mmol kg -1 ). The D ssp was calculated to be 17.72 and 16.99% for Site 5 and Site 4 sediments, respectively. The index values suggest that the P loss potential of the drainage ditches is less than the critical value for problematic P release to runoff. The index also suggests that the P loss potential is similar for both drainage ditches, even though the relative quantities of P, iron, and aluminum are different between the two sites. “Free Al and Fe” is a measure of P-sorption potential described by Maguire et al. (2001). The index is based on the principle that the oxalate-extractable aluminum and iron not currently associated with P, or “free Al and Fe”, is equivalent to the additional P-sorption potential of soils and sediments. oxoxoxoxoxPFeAlFeAlFree 5.0 (4-4) where P ox , Al ox , and Fe ox are the oxalate-extractable phosphorus, aluminum, and iron respectively (mmol kg -1 ). The free[Al ox +Fe ox ] for Sites 4 and 5 were 22.14 mmol kg -1 soil (686 mg kg -1 soil), and 7.01 mmol kg -1 soil (217 mg kg -1 soil), respectively. The measure indicates P-retention capacity of Site 4 sediments is 3.15 times greater than Site 5 sediments. The index values compare well with observed P retention in my study. The average P retention measured from both spike treatments at Site 4 is 3.8 times greater than the same quantity measured at Site 5. When P retention relative to initial loads (= P Retention / Initial P Load) is compared between sites, the average P retention at Site 4 is

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94 3.2 times greater than at Site 5. The P-uptake capacity at the study ditches seems to be closely related to oxalate extractable P, Fe, and Al. Q max , from the Langmuir isotherm, represents the maximum for fast, reversible sorption, and is frequently used as a sorption index (McGechan and Lewis, 2002). Q max , which has been used to define P saturation (Sharpley, 1995b), is determined by shaking soil samples with a solution containing a known P concentration for 24 hours. Schoumans and Groenendijk (2000) found that Q max could be estimated as one-sixth the sum of oxalate-extractable aluminum and iron for non-calcareous sandy soils in the Netherlands. Using this method of estimation, the Q max at Site 4 and 5 is 87.97 and 275.33 mg kg -1 , respectively. Another empirical method has been provided by Reddy et al. (1996b). The authors related Q max to several parameters of stream sediments and wetland soils in the Lake Okeechobee Basin, explaining 93% of the variability in Q max . Equation 4-5 is preferred, since the soils and sediments are more closely related to my study. 2.1][238.0][095.0][17.2max oxoxAlFeTOCQ (4-5) TOC = total organic carbon (g kg -1 ) Fe ox = oxalate extractable Fe (mg kg -1 ) Al ox = oxalate extractable Al (mg kg -1 ) TOC was estimated through LOI measurements in my study. Using the empirical formula presented in Equation 4-5, the Q max for Site 4 and 5 was calculated to be 951.63 and 169.14 mg kg -1 respectively. Q max was not determined explicitly in my study since batch incubation of sediment samples was not conducted. However, the empirical values of 951.63 and 169.14 mg kg -1 does provide a means to compare P-retention potential at Site 4 and 5 to those in other P assimilation studies.

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95 Biomass measurements At Site 4, where Pickerelweed (Pontederia cordata) is the dominant macrophyte, mesocosms were situated to isolate equal stands of vegetation. To ensure the experimental mesocosms were similar, the vegetation was collected at the end of the study period. The macrophytes were clipped above the mesocosm water level and again above the sediment surface, and the samples were sorted accordingly. Macrophytes were not present in Site 5 mesocosms, therefore no vegetation samples were collected. The volume of vegetation collected between the sediment surface and the water level was measured by displacing water in a demarcated bucket. All collected samples were placed in a drying room for 29 days, and then weighed to determine dry biomass. Average values are included in Table 4-4. Table 4-4 Average biomass above the sediment surface within each mesocosm at Site 4. Measurement Average Standard Deviation Below Water Level Vegetation Volume (L) 3.38 1.74 Below Water Biomass (g) 96.93 62.62 Total Biomass above Sediment Surface (g) 284.14 124.44 Pontederia, the dominant emergent macrophyte at Site 4, has been found to store 5 to 9 kg P ha -1 . However, the biomass decomposition half-life for Pontederia is 73 days, and P release during decomposition is initially slow (Reddy et al., 1995). Therefore, nutrient contributions to the water-column from decomposition were assumed to be negligible. Nitrogen Results The data do not illustrate definitely specific nitrogen (N) transformation processes which may have occurred in the study mesocosms. However, a summary of observed N data and possible explanations is included here.

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96 The measured nitrate and nitrite concentrations of all water samples taken during the experiment are negligible. The lack of soluble nitrate indicates that nitrification is severely hampered, or that biotic uptake, volatilization, and denitrification processes are much more significant. Reddy and Sacco (1981) suggest that low accumulation of NO 3 -N in drainage ditches indicates the dominance of volatilization over nitrification. However, the measured pH in the water-column is too low for volatilization to be substantial (Erickson, 1985). If the sediment-water interface were anoxic, nitrification would be severely reduced (Kemp et al., 1990), and optimal conditions would exist for denitrification. Another explanation would be that NO 3 -N generated from nitrification at the oxic sediment-water interface is immediately diffused downward, and none is released to the water-column. 02004006008001000120014000.01.02.03.04.05.06.07.0Time (days)NH4 Load (mg m-2) Control High Spike Low Spike Figure 4-17 High and low nutrient spike and experimental control ammonium loads over the course of the experiment at Site 4. Error bars represent one standard deviation.

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97 050010001500200025000.01.02.03.04.05.06.07.0Time (days)NH4 Load (mg m-2) Control High Spike Low Spike Figure 4-18 High and low nutrient spike and experimental control ammonium loads over the course of the experiment at Site 5. Error bars represent one standard deviation. The TKN concentrations measured outside of the mesocosms and in the control mesocosms are essentially unaltered over time, as is evident in Figure 4-3 and Figure 4-4. The average ambient TKN concentrations observed during the study period at Site 4 and 5 were 3.36 and 5.58 mg l -1 , respectively. At Site 4 it appears that some initial TKN uptake occurred from the spiked treatments, but the variability between replicates obscures any trend that may have otherwise been evident. There does not appear to be any TKN uptake from the spiked treatments at Site 5. The dilution treatments at both sites show that after reduction in the TKN concentration, the concentration remains unchanged for the remainder of the study period. Variability between replicates also clouds the effect of dilution on NH 4 -N at either study ditch. However, it is interesting to see how NH 4 -N behaves in the mesocosms where an NH 4 Cl solution was added. Elevated ammonium loads drop dramatically in two days at Site 4 (Figure 4-17). However, the same effect was not realized at Site 5, where elevated ammonium loads did

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98 not change considerably over time (Figure 4-18). Biotic uptake, either from emergent macrophytes, duckweed (Lemna minor), algae, or bacteria, may be responsible for the rapid ammonium decline at Site 4. It is also possible that the ammonium was nitrified to nitrate, but the nitrate was immediately diffused into the anoxic sediment layer. Ammonium adsorption due to cation exchange is another possibility. Simulation The P data from the mesocosm experiment can be analyzed in two ways: either by comparing net uptake over the course of the 7-day experiment to initial SRP concentrations, or by examining the SRP trends over time for each treatment individually. Net uptake and release are the parameters usually compared in batch incubation and laboratory sediment column experiments. The use of these parameters is justified, since the maximum uptake or release potential of soils or sediments is the desired measure. Kinetic P modeling is important because aquatic systems are rarely allowed to reach full equilibrium. The hydraulic residence time of wetlands, streams, and other waterways limits the amount of contact time between sediment and the water-column. By applying a kinetic model, it may be possible to make P uptake or release predictions based on known initial conditions and residence times. Modeling Net P Flux after 7 Days Many studies have used the Freundlich, Langmuir or other isotherm equations to model instantaneous P sorption in batch incubation studies. When used in this capacity, parameters such as the maximum P-sorption capacity of a unit mass of sediment (Q max ) from the Langmuir model, can be obtained. Though isotherm equations are typically not used for field experiments or laboratory sediment column studies, their applicability was tested with data from my study. Nonlinear regression was used to determine best-fit

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99 parameters for six models: the Freundlich isotherm, the Freundlich isotherm accounting for existing P in the sediment (Barrow, 1978), the Langmuir isotherm, the Temkin model, the Michaelis-Menton model, and a linear function used by Reddy et al. (1995). The difference between the first post-treatment measurement and the last (7 days) was used as the net P flux for each treatment. All four treatments and the experimental control were included in the analyses. The units for the model parameters as they were used are listed in Table 4-5. Table 4-5 Units for the model parameters used for net P flux analysis. Model Parameter Units k F no units b 1 no units Freundlich Q o mg m -2 Q max mg m -2 Langmuir k L m 2 mg -1 A no units Linear P 1 mg m -2 V m mg m -2 Michaelis-Menton K s mg m -2 k T1 no units Temkin k T2 no units Site 4 The six adsorption models fitted well to the observed data at site 4. The best-fit parameters for the models are listed in Table 4-6. Figure 4-19 shows how the six models compared to the observed data at Site 4. For the ranges of P flux and initial SRP concentrations observed at Site 4, most of the models were linear in nature, even though the models were non-linear. The Temkin model is the only model that does not plot as a near-straight line, though the goodness of fit is less than for the other models. The Freundlich model with an extra term (ETF) best fitted the measured data at Site 4 (R 2 = 0.99). If the ETF model is valid, it suggests that 111 mg m -2 of surface-sorbed P is

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100 present under ambient conditions. The nearly linear fit demonstrated by the Michaelis-Menton model likely indicates that the model parameters do not hold much value. The Langmuir model fit is nearly linear for this data set, indicating that the predicted P saturation value is much larger than the observed sorption. It is important to note that the Freundlich, Langmuir, and Michaelis-Menton models cannot model P release (negative sorption). In the range of SRP flux and initial concentrations of my study, the behavior of most models is almost linear. The linear response to initial SRP concentration was also observed by Reddy et al. (1995) for laboratory sediment columns. A P 1 value of 61.5 mg m -2 shown in Table 4-6 represents the P-release potential of the sediment under ambient conditions. The X-intercept of 0.458 mg l -1 for the linear model represents the EPC w , or the water-column SRP concentration at which P flux does not occur, at Site 4. The ETF model is the most appropriate model based on regression statistics. Table 4-6 Net P flux at Site 4: Best-fit parameters and goodness of fit for six models fit to net P flux data. Model R 2 SSR Parameters Intercep t Freundlich 1bFCkQ 0.974 12229.85 k F = 82.825 b 1 = 1.244 0.0 Freundlich with extra term (ETF) obFQCkQ1 0.988 3959.29 k F = 212.973 b 1 = 0.739 Q o = 111.35 0.416 Langmuir CkCkQQLL1max 0.984 15465.05 Q max = 34181 k L = 0.003 0.0 Linear 1PACPr 0.984 5279.55 A = 134.030 P 1 = 61.452 0.458 Michaelis-Menton SKSVVsm 0.984 320.86 V m = 3.477E+16 K s = 2.036E+15 0.0 Temkin )ln(21CkkQTT 0.930 22761.75 k T1 = 179.811 k T2 = 3.372 0.297

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101 -200-10001002003004005006007000.01.02.03.04.05.06.0Initial Measured SRP Conc (mg L-1)P flux (mg m-2) Observations Temkin Freundlich Freundlich (extra term) Langmuir Linear Michaelis-Menton Figure 4-19 Data and fitted models comparing net P flux to initial SRP concentration at Site 4. Site 5 Similar to Site 4, the Temkin model provides the worst fit, whereas the ETF and Michaelis-Menton models best fit the measured data at Site 5 (R 2 = ~0.99) (Table 4-7, Figure 4-20). The ETF model suggests that 19 mg m -2 of surface-sorbed P is present under ambient conditions. The V m parameter of the Michaelis-Menton model indicates a maximum uptake of 251 mg m -2 (Table 4-7). The Michaelis-Menton model has been used for modeling uptake by benthic algae in streams (Steinman and Mulholland, 1996), and may not be appropriate for the agricultural ditches in my study. The maximum uptake determined from the Michaelis-Menton model is in sharp contrast to the maximum sorption of 15247 mg m -2 predicted by the Langmuir model.

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102 Table 4-7 Net P flux at Site 5: Best-fit parameters and goodness of fit for six models fit to net P flux data. Model R 2 SSR Parameters Intercept Freundlich 1bFCkQ 0.983 264.373 k F = 70.566 b 1 = 0.680 0.0 Freundlich with extra term (ETF) obFQCkQ1 0.986 206.316 k F = 95.245 b 1 = 0.503 Q o = 19.07 0.041 Langmuir CkCkQQLL1max 0.964 912.348 Q max = 15247 k L = 0.004 0.0 Linear 1PACPr 0.963 552.813 A = 47.739 P 1 = -11.623 -0.243 Michaelis-Menton SKSVVsm 0.989 3.392 V m = 251.375 K s = 2.234 0.0 Temkin )ln(21CkkQTT 0.957 638.009 k T1 = 38.120 k T2 = 11.463 0.087 0204060801001201401601800.00.51.01.52.02.53.03.5Initial Measured SRP Conc (mg L-1)P flux (mg m-2) Observations Temkin Freundlich Freundlich (extra term) Langmuir Linear Michaelis-Menton Figure 4-20 Data and fitted models comparing net P flux to initial SRP concentration at Site 5. Even though other models provide better fits, the R 2 value for a linear fit is 0.963. As is evident in Table 4-7, the X-intercept for the linear model is -0.243 mg l -1 . This would represent the EPC w , or the water-column SRP concentration at which P flux does

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103 not occur, at Site 5. A negative EPC w is calculated since P uptake was observed after 7 days for all treatments, including dilution. The EPC w determined from the Temkin model and the 3-parameter Freundlich model is 0.087 and 0.041 mg l -1 , respectively. Overall, based on the regression statistics and the nature of processes that resulted in sorption for my study, the ETF model is the best to simulate the P sorption in the two drainage ditches, though a linear model may also be appropriate for the SRP concentration range in my study. Kinetic P Flux Modeling Though many kinetic models are intended for batch incubation studies, some are versatile enough for use with my study. Since soil-solution systems vary widely, it is not expected that a single kinetic model will be universally valid (Pavlatou and Polyzopoulos, 1988). Therefore, several models were tested in my study. The kinetic version of the Freundlich model described in Barrow (1983), having the form is not included in the analysis because it was believed to be repetition of the power function. Hansen et al. (1999) considered a model equivalent to the power function, which they regarded as a modified Freundlich model. Indeed, the only difference between the kinetic Freundlich model and the power function is the inclusion of water-column concentration. Since measured water-column concentrations are used in the calculation of P retention, it is not an independent parameter. Therefore, the modified kinetic Freundlich model includes a parameter on the left-hand side of the equation derived from a parameter on the right-hand side. The power function, where time is the only independent parameter, was considered more applicable to my study. 21)(bbFtCktn

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104 The power function has also been called the Bangham equation (House et al., 1995a), since Bangham and Burt (1924) were the first to describe this model. The boundary layer model used in the analysis (House et al., 1995b; House and Denison, 2002; Barlow et al., 2004) has also been termed first-order kinetics in other studies (House et al., 1995a; Toor and Bahl, 1999). The parabolic diffusion model and the Elovich equation have been used in combination in a variety of studies (Agbenin and Tiessen, 1995; House et al., 1995a; GarciaRodeja and GilSotres, 1997; House and Denison, 1997; Toor and Bahl, 1999; Barlow et al., 2004). In most cases, these studies concluded that the Elovich equation better fits observed data. Site 4 Site 4 high P spike treatment. The plots in Figure 4-21 and the R 2 values in Table 4-8 show that kinematic P uptake can be successfully simulated using the Elovich equation, power function, boundary layer, or parabolic diffusion models. The boundary layer model best fits the observed P uptake from the high P spike treatment at Site 4. The parameters for the four models listed in Table 4-8 are largely empirical (Barlow et al., 2004). Toor and Bahl (1999) propose that the suitability of the parabolic diffusion model (defined in the Modeling section of Literature Review and in Table 4-8) indicates that sorption is a diffusion-controlled process, since cumulative P sorption (n(t)) and t 1/2 are linearly related. The power function (also defined in Table 4-8) essentially becomes the parabolic diffusion model if v approaches 0.5. It is important to note that only the boundary layer model can predict the maximum sorption. The other three models allow for sorption to continue ad infinitum, though the sorption predicted from the Elovich equation reduces considerably over time. The capability of predicting the short-term sorption potential makes the boundary layer model

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105 a better choice than the Elovich equation, power function, or parabolic diffusion model for some purposes. If the experiment were allowed to continue longer than 20 days, the maximum sorption predicted from the boundary layer model for this treatment is 660 mg m -2 or ’. Therefore, 47%, 72%, and 90% of the predicted maximum sorption had already occurred after 2, 4, and 7 days, respectively. It is also possible to model P sorption by observing the change in the water-column concentration or load over time, as opposed to observing sorption. Hansen et al. (1999) provides four reasons why it is better to model the observed solution concentration. First, the solution concentration is the measured quantity, whereas sorption is calculated as the difference between the initial and measured values. Second, the solution concentration is unambiguous, but the initial adsorbed P is an unknown quantity. Third, the solution concentration can vary over several orders of magnitude, so the loss of phosphate from solution can be followed better with measured quantities. Lastly, the solution concentration is of prime practical interest in phosphate uptake transport studies. Both the boundary layer and Barlow et al.’s (2003) model (Barlow model) fit the observed data very well (R 2 = 1.00) (Table 4-9, Figure 4-22). The Barlow model was fit to observed data by allowing C final to vary and assuming that no further retention would occur. The two methods were employed to observe the differences between using a two parameter and a three parameter model. The three parameter Barlow model best fits observed data, and it predicts that the system would reach sorption / desorption equilibrium at a measured SRP load of 123 mg m -2 . The value from the boundary layer model (Table 4-9) represents the equilibrium SRP mass (mg m -2 ).

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106 Table 4-8 Kinetic P sorption modeling at Site 4 (high spike): Best-fit parameters and goodness of fit statistics for four kinetic models fitted to the P sorption data from the high P spike treatment at Site 4. Model Equation R 2 SSR Parameters Elovich )1ln(''AteBtn 1.00 442.99 B' = 296.246 A' = -0.034 Boundary Layer )'(1'tketn 1.00 34.93 ' = 660.101 k' = 0.333 Parabolic Diffusion bRttn2/1)( 0.99 2126.68 R = 234.882 b = 13.604 Power vBtKtn)( 0.99 1886.21 K b = 213.875 v = 0.544 010020030040050060070001234567Time (days)Sorption (mg m-2) Observations Power Elovich Boundary Layer Parabolic Diffusion Figure 4-21 Kinetic P sorption modeling at Site 4 (high spike): Cumulative observed and predicted phosphorus sorption using five kinetic models. Table 4-9 Kinetic P load modeling at Site 4 (high spike): Best-fit parameters and goodness of fit statistics for three kinetic models fit to observed P load data from the high P spike treatment at Site 4. Model Equation R 2 SSR Parameters Boundary Layer )()(01ktkteectc C o =299.96 1.00 2.51 = 123.020 k = 0.334 Barlow (2 parameters) C btfinalaeCtc)( final =140.5 1.00 105.02 a = 161.401 b = 0.415 Barlow btfinalaeCtc)( 1.00 2.29 a = 176.811 b = 0.331 C final = 122.706 Power BtKtc)1()( 0.99 226.37 K = 306.493 B = 0.354

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107 10015020025030035001234567Time (days)Load (mg) Observations Boundary Layer Barlow (2 parameter) Barlow (3 parameter) Power Figure 4-22 Kinetic P load modeling at Site 4 (high spike): Decline in observed and predicted phosphorus load using three kinetic models. The scale on the Y-axis is reduced to show detail. Site 4 low P spike treatment. All the models fit the sorption data closely, though the boundary layer model best models the observed P retention from the low P spike treatment at Site 4 (Figure 4-23). The boundary layer model predicts that the system would have reached equilibrium in over 30 days at a measured load of 457 mg m -2 . Hence, 77% of the predicted maximum sorption had already occurred after 7 days. The difference in P retention after 7 days between the low spike and high spike treatment suggests that it may take longer to reach equilibrium from smaller nutrient disturbances. The order of fit for the four kinetic sorption models at Site 4 for the high and low spike treatments (Table 4-8 and Table 4-10) is: boundary layer > Elovich > Power > Parabolic Diffusion. For modeling SRP load instead of sorption, both the boundary layer model and the Barlow model fit the observed data very well (R 2 = 0.99), but the Barlow model provides

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108 a better fit (Table 4-11, Figure 4-24). The Barlow model was fit to observed data by allowing C final to vary, and by assuming further retention would not occur. The two methods were employed to observe the differences between using a two parameter and a three parameter model. The three parameter Barlow model predicts that the system would reach equilibrium at a measured load of 81.8 mg m -2 . The value from the boundary layer model also represents the equilibrium load (76.6 mg m -2 ). Table 4-10 Kinetic P sorption modeling at Site 4 (low spike): Best-fit parameters and goodness of fit statistics for four kinetic models fitted to the P sorption data from the low P spike treatment at Site 4. Model Equation R 2 SSR Parameters Elovich )1ln(''AteBtn 0.98 1807.37 B' = 282.347 A' = -1.003 Boundary Layer )'(1'tketn 0.99 1311.26 ' = 457.328 k' = 0.212 Parabolic Diffusion bRttn2/1)( 0.94 4664.32 R = 140.892 b = 30.376 Power vBtKtn)( 0.97 2893.89 K b = 93.238 v = 0.700 05010015020025030035040001234567Time (days)Sorption (mg m-2) Observations Elovich Power Boundary Layer Parabolic Diffusion Figure 4-23 Kinetic P sorption modeling at Site 4 (low spike): Cumulative observed and predicted phosphorus sorption using five kinetic models.

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109 Table 4-11 Kinetic P load modeling at Site 4 (low spike): Best-fit parameters and goodness of fit statistics for three kinetic models fit to observed P load data from the low P spike treatment at Site 4. Model Equation R 2 SSR Parameters Boundary Layer )()(01ktkteectc C o =199.19 0.99 94.25 = 76.590 k = 0.212 Barlow (2 parameters) C btfinalaeCtc)( final =104.95 0.97 205.86 a = 97.477 b = 0.373 Barlow btfinalaeCtc)( 0.99 80.31 a = 120.713 b = 0.238 C final = 81.822 Power BtKtc)1()( 0.94 371.08 K = 207.972 B = 0.294 50709011013015017019021023001234567Time (days)Load (mg) Observations Boundary Layer Barlow (2 parameters) Barlow (3 parameters) Power Figure 4-24 Kinetic P load modeling at Site 4 (low spike): Decline in observed and predicted phosphorus load using three kinetic models. The scale on the Y-axis is reduced to show detail.

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110 Site 5 Site 5 High P Spike Treatment. Modeling P retention kinetics for the high P spike treatment was difficult due to the occurrence of both sorption and release during the study period. A small quantity of P was released before P uptake was observed (Figure 4-25, Figure 4-26). The result was unexpected, and the P models included in Table 4-12 and Table 4-13 do not account for the observed flux very well. Though the observed flux after 7 days is still conducive to net P flux modeling (Figure 4-23), it is difficult to fit the data to kinetic P sorption models. Nevertheless, nonlinear regression was still performed to assess how each model fits the data. The best fit is provided by the power function, though as can be seen in Figure 4-25, it is unlikely the model represents the actual nature of P sorption at Site 5. The behavior of the Elovich and boundary layer models was linear. Similar to sorption models, kinetic models did not fit the water-column SRP concentration or load data (Table 4-13). Figure 4-26 illustrates the difficulty in applying a predictive P sorption model based on the observed P flux from the high P spike treatment at Site 5. The parameter values listed in Table 4-13 likely do not hold much value. However, the parameters from the two-parameter Barlow model may fit the data at Site 5, because the model is forced to approach the last observation. The two parameters from the Barlow model can be compared to the other sorption treatment at Site 5.

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111 Table 4-12 Kinetic P sorption modeling at Site 5 (high spike): Best-fit parameters and goodness of fit statistics for four kinetic models fitted to the P sorption data from the high P spike treatment at Site 5. Model Equation R 2 SSR Parameters Elovich )1ln(''AteBtn 0.80 7782.73 B' = 52702.399 A' = -8.170 Boundary Layer )'(1'tketn 0.80 7785.04 ' = 35899.521 k' = 0.000 Parabolic Diffusion bRttn2/1)( 0.51 9766.88 R = 50.860 b = 48.323 Power vBtKtn)( 0.96 1564.72 K b = 0.044 v = 4.190 -100-5005010015001234567Time (days)Sorption (mg m-2) Observations Power Elovich & Boundary Layer Parabolic Diffusion Figure 4-25 Kinetic P sorption modeling at Site 5 (high spike): Cumulative observed and predicted phosphorus sorption using five kinetic models. Table 4-13 Kinetic P load modeling at Site 5 (high spike): Best-fit parameters and goodness of fit statistics for three kinetic models fit to observed P load data from the high P spike treatment at Site 5. Model Equation R 2 SSR Parameters Boundary Layer )()(01ktkteectc C o =285.47 0.80 559.41 = 9552.551 k = 0.000 Barlow (2 parameters) C btfinalaeCtc)( final =247.25 0.66 516.15 a = 48.257 b = 0.170 Barlow btfinalaeCtc)( 0.80 291.08 a = 5965.011 b = 0.001 C final = -5669.003 Power BtKtc)1()( 0.51 705.45 K = 297.490 B = 0.059

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112 20022024026028030032001234567Time (days)Load (mg) Observations Boundary Layer Barlow (2 parameter) Barlow (3 parameter) Power Figure 4-26 Kinetic P load modeling at Site 5 (high spike): Decline in observed and predicted phosphorus load using three kinetic models. The scale on the Y-axis is reduced to show detail. Site 5 Low P Spike Treatment. In contrast to the high P spike treatment, the data set for the low P spike treatment (Figure 4-27) did not suffer from the problem of early P release observed in the high spike treatment (Figure 4-25). However, the data from the treatment is different than that observed for site 4, because retention appears to start slowly. Diffusion or adsorption models expect P flux to be rapid soon after a change in the floodwater nutrient load. The model fits shown in Table 4-14 are fairly good, but it is unknown if they represent the actual behavior of the system. Similar to the results for the Site 5 high spike treatment, the shape of the Elovich and boundary layer model response was nearly linear. When the models were fitted to the water-column load (SRP mass) for the low spike treatment, the shape of the model response was nearly linear. It is likely that mesocosm sampling at a higher frequency or for a longer duration than 7 days would

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113 have allowed a better fit. For the high P spike treatment, the a parameter in the two-parameter Barlow model is 1.65 times greater than the value observed for the low P spike treatment. The same ratio of the a parameter was also observed for the P spike treatments at Site 4. Table 4-14 Kinetic P sorption modeling at Site 5 (low spike): Best-fit parameters and goodness of fit statistics for four kinetic models fitted to the P sorption data from the low P spike treatment at Site 5. Model Equation R 2 SSR Parameters Elovich )1ln(''AteBtn 0.87 912.07 B' = 34049.792 A' = -7.812 Boundary Layer )'(1'tketn 0.87 912.48 ' = 24411.087 k' = 0.001 Parabolic Diffusion bRttn2/1)( 0.74 1744.07 R = 35.710 b = 12.685 Power vBtKtn)( 0.89 810.78 K b = 8.148 v = 1.302 -2002040608010012001234567Time (days)Sorption (mg m2 ) Observations Elovich & BoundaryLayer Power Parabolic Diffusion Figure 4-27 Kinetic P sorption modeling at Site 5 (low spike): Cumulative observed and predicted phosphorus sorption using five kinetic models

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114 Table 4-15 Kinetic P load modeling at Site 5 (low spike): Best-fit parameters and goodness of fit statistics for three kinetic models fit to observed P load data from the low P spike treatment at Site 5. Model Equation R 2 SSR Parameters Boundary Layer )()(01ktkteectc C o =155.74 0.87 65.56 = -6291.440 k = -0.001 Barlow (2 parameters) C btfinalaeCtc)( final =127.69 0.77 114.77 a = 29.116 b = 0.210 Barlow btfinalaeCtc)( 0.87 65.33 a = 11724.643 b = 0.000 C final = -11568.618 Power BtKtc)1()( 0.72 134.59 K = 158.512 B = 0.079 1201251301351401451501551601650123456 7 Time (days)Load (mg) Observations Boundary Layer Barlow (2 parameter) Barlow (3 parameter) Power Figure 4-28 Kinetic P load modeling at Site 5 (low spike): Decline in observed and predicted phosphorus load using three kinetic models. The scale on the Y-axis is reduced to show detail. Kinetic modeling of dilution treatments The data from the four dilution treatments are too scattered to successfully apply a kinetic model. However, when the last data point (Day 7) is omitted, it is interesting to see how well the P release data from the Site 4 high dilution treatment compare to the boundary layer model (Figure 4-29A). Whereas the boundary layer fits well for one treatment, it does not for the other three (Table 4-16). For completeness, plots of the three other model simulations (Figure 4-29B, C, D) are included.

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115 Table 4-16 Boundary layer model applied to high and low dilution treatment data sets at Site 4 and 5: Best-fit parameters and goodness of fit. The last data point (Day 7) was omitted from the analysis. Site 4 ~75% Dilution Site 4 ~50% Dilution Site 5 ~75% Dilution Site 5 ~50% Dilution R 2 1.00 0.52 0.11 0.64 SSR 0.67 49.86 129.3 39.8 = 76.589 = 8.815 = -4.583 = 986.635 Parameters k = 1.629 k = 1.886 k = 80.631 k = 0.002 010203040506070809000.511.522.533.5 4 Time (days)Desorption ( mg m -2 ) A Figure 4-29 Cumulative phosphorus releases observed and predicted using the boundary layer model. A) high dilution treatment at Site 4. B) low dilution treatment at Site 4. C) high dilution treatment at Site 5. D) low dilution treatment at Site 5. The last data point (Day 7) is omitted from all plots.

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116 024681012141600.511.522.533.54Time (days)Desorption (mg m2 ) B Figure 4-29. Continued -14-12-10-8-6-4-2024600.511.522.533.54Time (days)Desorption (mg m-2) C Figure 4-29. Continued

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117 -6-4-20246800.511.522.533.5 4 Time (days)Desorption (mg m-2) D Figure 4-29. Continued Modeling Summary Several existing models were fitted to the data to test their applicability to drainage ditches of south Florida. The Elovich equation, power function, parabolic diffusion, boundary layer, and Barlow kinetic models were tested with observed uptake. With the exception of the Parabolic Diffusion model, most kinetic models matched observed data fairly well as indicated in Table 4-17. The power function best describes the observed P retention over time from the four P spike treatments. However, best-fit parameters to the low P spike treatment at Site 5 suggest exponential increase in P retention, which is not reasonable. Additionally, the power function never reaches equilibrium, which also is not reasonable. The function presented in Barlow et al. (2003) to represent P retention in drainage ditches provided the best representation of observations in the study ditches (R 2 = 0.993 and 0.832 for Sites 4 and 5, respectively). None of the kinetic models consistently simulated P release in the study ditches.

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118 Table 4-17 R 2 coefficients for the tested models. Average values between high and low P spike treatments are shown. Model Dependent Parameter Site 4 Average Site 5 Average Both Site Average Power Sorption 0.9787 0.9221 0.9504 Barlow Load 0.9932 0.8319 0.9126 Boundary Layer Load 0.9929 0.8321 0.9125 Boundary Layer Sorption 0.9929 0.8321 0.9125 Elovich Sorption 0.9887 0.8322 0.9104 Parabolic Diffusion Sorption 0.9672 0.6277 0.7974 Power Load 0.9621 0.6170 0.7896 Since the relative P retention trends are similar, a general equation for P uptake at Site 4 can be determined, even though the actual retention between treatments is different. Equation 4-6 was determined for SRP uptake at Site 4 using the model developed by Barlow et al. (2003). It is valid for water-column SRP loads ranging from 133 to 1120 mg m -2 (corresponding to SRP concentrations ranging from 0.55 to 4.93 mg l -1 ). Equation 4-6 matched the observed data well (R 2 = 0.995). )2994.0(*6217.04113.0)(tiiePPtP (4-6) P(t) = SRP load in the water-column at time, t (mg m -2 ) P i = Initial SRP load in the water-column (mg m -2 ) Equation 4-6 predicted an equilibrium SRP load of 0.4113*Pi. Under typical field conditions, the hydraulic residence time is too short for long-term equilibrium to establish. The kinetic relationship in Equation 4-6 is valid for hydraulic residence times less than a week in drainage ditches with sediment characteristics similar to Site 4. A similar relationship was determined for Site 5, but the regression coefficient (R 2 ) was low. Several existing equations were fitted to net P flux data to test their applicability to in-situ experiments in south Florida drainage ditches. Two versions of the Freundlich equation, the Langmuir isotherm, the Temkin model, the Michaelis-Menton model, and a

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119 linear function used by Reddy et al. (1995) were tested against net P uptake and release measured after 7 days. The Freundlich model best represented the data, though a linear model was also adequate. The Freundlich model was used to establish Equation 4-7 and 4-8 for net P uptake or release at the study ditches. The relationships matched observed net P flux very well. At Site 4 where the sediment was primarily composed of organic matter, the fitted Freundlich model (R 2 = 0.988) was as follows: 35.111212.973739.0CQ (4-7) Q = SRP flux (mg m -2 ) C = water-column SRP concentration (mg l -1 ) For Site 5, where the sediment contained less organic matter than Site 4, the fitted Freundlich model (R 2 = 0.986) was Equation 4-8: 07.19206.316503.0CQ (4-8) These equations can be used to calculate the water-column concentration at which no net P flux is observed (EPC). The predicted EPC at Sites 4 and 5 were 0.416 and 0.041 mg l -1 , respectively. The EPC at Site 5 was very low because P retention was observed under all treatments after 7 days. Although non-linear models fitted the data well, a simple straight line fitted the data equally well for Sites 4 and 5. Site 4: (R 452.6103.134CQ 2 = 0.984) (4-9) Site 5: (R 623.11739.47CQ 2 = 0.963) (4-10) One of the major outcomes from the linear model was that it predicted a negative EPC for Site 5, indicating that after 7 days P release is unlikely under any circumstance.

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120 If an effort was made to detain the water in the ditch for 7 days as part of a BMP, uptake according to Equation 4-9 and 4-10 can be expected.

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CHAPTER 5 SUMMARY AND CONCLUSION Summary A study was undertaken to quantify the in-situ nitrogen (N) and phosphorus (P) retention in agricultural drainage ditches in south Florida. Benthic mesocosms, constructed from the cylinders of thirty 55-gallon steel drums and coated with a strong, nonreactive epoxy-paint, were pushed into the ditch sediment, isolating undisturbed portions of the benthic surface. The nutrient concentrations of the water inside the mesocosms were altered to promote P flux across the sediment-water interface. Four treatments, representing four P concentration levels, were tested in triplicate across two drainage ditches. One ditch (Site 4) drains a small wetland (area = 25 ha), while the second ditch (Site 5) drains a large portion of the ranch (area = 252 ha). The treatments were achieved through nutrient additions and water dilution. Water-column N and P concentrations in each mesocosm were measured periodically over 7 days. The nutrient data were adjusted to compensate for evapotranspiration, dilution from outside the volume enclosed by the mesocosm, and water loss. The extent of P retention and release was quantified through data analysis and modeling. Phosphorus Retention Results from the mesocosm study at both ditches showed considerable P retention. P retention at Site 4 was much higher than Site 5. SRP retention after P loading averaged 50% of the spiked load at Site 4 and 16% at Site 5. Since the influences of ET, dilution, and water loss were excluded from the data, P diffusion, sorption, and 121

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122 biotic uptake were the only processes that resulted in the reduction of P in the water-column. The difference in P retention between sites is largely due to sediment characteristics. Sediment and vegetative characteristics show the dissimilarities between the two study ditches. The Site 4 ditch is essentially a long emergent wetland, and the Site 5 ditch is an earthen channel with almost no vegetation and mineral sediments. Though the sediments at Site 4 contain higher total P, water-extractable P, and oxalate-extractable P concentrations than Site 5, the oxalate-extractable aluminum content is also higher. Site 4 sediments contain more P, but have a greater P-retention capacity. It is believed that the P content of Site 4 sediments is higher because of greater historical loading to the ditch and greater retention capacity. The unit area P fertilizer application was over twice as high in the Site 4 drainage basin in 2003 and 2004 compared to the Site 5 drainage basin. An index of aluminum and iron not associated with P (free[Al ox +Fe ox ]) indicates that Site 4 sediments possess over three times (x 3.15) more capacity to retain P than Site 5 sediments. When the ratios of observed P retention and initial loads for the two sites were compared, the average P retention at Site 4 was 3.2 times greater than at Site 5. There appears to be a clear relationship between the sediment characteristics (P, Al, and Fe) and observed P retention. Phosphorus Release Phosphorus release measured in my study is mostly due to sediment porewater diffusion and desorption from sediment. At Site 4, approximately 60 and 71 mg m -2 was released to the water-column after the low and high dilution treatments, respectively, but

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123 the same quasi-equilibrium (approximately 106 mg m -2 ) was established for both treatments. P release at Site 4 was initially rapid but slowed after 1 to 2 days. At Site 5, P release to the water-column after 4 days was equivalent to approximately 12 and 24% of the starting ambient load under the low and high dilution treatments, respectively. However, after 7 days the effect of P release was inconsequential. It appears that P uptake and release is transitory at low water-column P concentrations. For drainage ditches similar to Site 5, it appears that P release to the water-column may be controlled by hydraulic retention time and starting P load. After short hydraulic residence times, P may be released to the water-column, though with an extended residence time, P may be adsorbed again. The sediment characteristics measured at both study ditches indicate that the P-release potential of both study ditches is similar. The Dutch saturation index, a measure of P runoff potential, was calculated to be 17.72 and 16.99% for Site 5 and Site 4 sediments, respectively. After extended hydraulic residence times, the P release may be similar between the ditches. However, P release is much more rapid at the ditch with mostly organic sediment (Site 4) than the ditch with mostly mineral sediment (Site 5). Phosphorus Modeling Several existing models were fitted to the data to test their applicability to drainage ditches of south Florida. The Elovich equation, power function, parabolic diffusion, boundary layer, and Barlow kinetic models were tested with observed uptake, and the Barlow model best represented observations (R 2 = 0.993 and 0.832 for Sites 4 and 5, respectively). Since the relative P retention trends were similar, a general equation for P uptake at Site 4 was determined, even though the actual retention between treatments was different. The relationship matched the observed data well (R 2 = 0.995).

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124 Under typical field conditions, the hydraulic residence time is too short for long-term equilibrium to establish. The empirical kinetic relationship can be used for hydraulic residence times less than a week in drainage ditches with sediment characteristics similar to Site 4. A similar relationship was determined for Site 5, but the regression coefficient (R 2 ) was low. Several existing equations were fitted to net P flux data to test their applicability to in-situ experiments in south Florida drainage ditches. Two versions of the Freundlich equation, the Langmuir isotherm, the Temkin model, the Michaelis-Menton model, and a linear function used by Reddy et al. (1995) were tested against net P uptake and release measured after 7 days. The Freundlich model best represented the data (R 2 = 0.988 and 0.986 for Sites 4 and 5, respectively), though a linear model was also adequate (R 2 = 0.984 and 0.963 for Sites 4 and 5, respectively). The net P flux equations can be used to calculate the water-column concentration at which no net P flux is observed (EPC). The predicted EPC at Sites 4 and 5 were 0.416 and 0.041 mg l -1 , respectively. The EPC at Site 5 was very low because P retention was observed under all treatments after 7 days. One of the major outcomes from the linear model was that it predicted a negative EPC for Site 5, indicating that after 7 days P release is unlikely under any circumstance. If an effort was made to detain the water in the ditch for 7 days as part of a BMP, uptake according to the determined empirical relationships could be expected. Nitrogen The lack of nitrate in the ditch water-column for all treatments suggests that any NO 3 -N generated from nitrification at the oxic sediment-water interface is immediately diffused downward and is not released to the water-column. It is also possible that the

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125 sediment-water interface is anoxic and denitrification is dominant over nitrification. Biotic uptake, either from emergent macrophytes, duckweed (Lemna minor), algae, or bacteria, may be responsible for the rapid ammonium decline at Site 4. It is also possible that the ammonium was nitrified to nitrate, but the nitrate was immediately diffused into the anoxic sediment layer. The N results indicate that N transformation processes were taking place in the 7-day experiment, but the data do not illuminate the respective processes conclusively. Conclusion The capacity for ditch sediment to retain or release P and N is not uniform, and site-specific analyses are necessary. However, the data show that P uptake may be greater and release more rapid in drainage ditches with organic sediment and emergent macrophytes compared to other ditches. The magnitude of P retention is related to sediment aluminum and iron contents. Since P uptake and release is not instantaneous, it appears that diffusion and sediment porewater exchange are the rate-limiting processes that control the water-column P-concentration changes over time. The hydraulic residence time of wetlands, streams, and other waterways limits the amount of contact time between sediment and the water-column. By applying the Barlow model, which best represented the data, P uptake or release can be predicted for known initial SRP loads and residence times. Therefore, if the typical residence time of ditches on a ranch is 2 days, a land manager can calculate the additional expected P retention by retaining water in ditches for 1 or 2 more days. Results from my study clearly indicate that ditch water retention can be an effective BMP for reducing net discharge of P from cow-calf operations. Similar benefits can be expected for other agricultural systems such as dairy or row crop production.

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126 Dilution treatment results for Site 5 suggest that if the residence time is between 1 to 4 days some P release is expected. However, if the water can be retained for more than 4 days, net uptake of P is likely to occur. It can be concluded that if water is retained for 1 to 4 days in ditches, where the sediment is already saturated and the runoff P concentration is very low, there will be a net release of P. Very low P concentrations in runoff are possible after successive rainfall events typical of late summer. Spike treatment results also indicate that P release is possible if the residence time in the ditches is between 1 to 4 days. Once the residence time is extended, however, a net P uptake is expected. Therefore, if ditch water retention is to serve as a BMP, the water needs to be retained for at least 4 days before discharging it downstream. Compared to laboratory studies, several challenges arise when measuring nutrient flux in field-situated mesocosms. The measured nutrient data were affected by evapotranspiration, dilution from outside the control volume, and water loss. However, ET was known for the study period, dilution was determined through bromide tracer analysis, and net water loss was measured. Therefore, masking effects such as ET could be quantified, and the data could be adjusted to compensate. The nutrient concentrations inside the control mesocosms showed no considerable differences from the ambient ditch water, indicating that enclosure did not have an adverse impact over the experimental period. Further research is needed to evaluate the effects of land use, emergent vegetation type, channel water depth, and season on in-situ P retention or release capacity. A comparison between open-bottomed benthic mesocosms and close-bottomed field-situated mesocosms may illuminate the superior strategy for measuring P flux in-situ.

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127 Conducting an in-stream study with coupled tracer and nutrient additions would also be beneficial for determining the diffusive, sorptive as well as advective P-retention capacity of an entire channel.

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APPENDIX CHOICE OF CONSERVATIVE TRACER Many different nonreactive, hydrologic tracers have been used in streams and wetlands, each with some success. The choice of a particular hydrologic tracer depends on environmental variables, experimental setup, and available resources. For this in-situ benthic mesocosm study, bromide (specifically KBr) has been chosen as the best available tracer. Bromide is an attractive hydrologic tracer since it is nonreactive, is relatively easy to analyze, is present at low concentrations in most natural systems, and has low toxicity (Davis et al., 1980; Bowman, 1984). Bromide has been used successfully as a conservative tracer in streams and wetlands in climates ranging from arctic to tropical, and from varied topography to areas of little relief (Chestnut and McDowell, 2000; Edwardson et al., 2003; Harvey and Fuller, 1998; Lin et al., 2003; Martinez and Wise, 2003; Moyer et al., 1998; Valett et al., 1996; Zellweger, 1994). In an experimental stream, Jones and Jung (1990) found that bromide was a more reliable tracer than Rhodamine WT or Li + . Rhodamine WT is a commonly used fluorescent dye, however it can be sorbed by streambed sediments (Bencala et al., 1983; Munn and Meyer, 1988), and loses fluorescence under low pH conditions (Stream Solute Workshop, 1990). Indeed, under acidic conditions (pH<6), Jones (1987) has concluded that Rhodamine WT is not conservative. Using the lithium ion for a conservative tracer may not be ideal for the stream experiments because it may sorb to organic matter (Bencala et al., 1983; Cooper, 128

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129 1994; Smart and Laidlaw, 1977; Stairs, 1993), though sediment adsorption may not be problematic under acidic conditions (Zellweger, 1994). Chloride is another commonly used tracer. Like bromide, chloride can be measured by ion chromatography or can be monitored with an ion specific electrode (Stream Solute Workshop, 1990). Though typically conservative, chloride may be sorbed by stream sediments under acidic conditions (Feth, 1981; Kennedy et al., 1984). Additionally, the background concentration of chloride in the stream may be elevated, further reducing the appeal of this tracer. Isotopic hydrologic tracers such as deuterium, or tritium could be considered the best hydrologic tracers because their behavior is nearly identical to water (Stream Solute Workshop, 1990), however cost and legal restraints make them unfeasible. Though adsorptive losses of bromide have been shown to be negligible (Jones, 1987), plant uptake of the tracer has been a problem in some experiments. In long term agricultural experiments (including sorghum, orchardgrass, Kentucky bluegrass, ryegrass, corn, and a potato crop), plant uptake of bromide ranged from 32% to 85% of the applied tracer (Chao, 1966; Owens et al., 1985; Kung, 1990; Jemison and Fox, 1991; Schnabel et al., 1995; Eckhardt et al., 1996). Most of these experiments took place over the course of a growing season. In a wetland tracer study in Arizona, plant uptake was concluded to account for nearly 50% loss in added bromide (Whitmer et al., 2000). The nominal hydraulic detention time during this experiment was between 4 and 5 days, so it is possible that plant uptake is only an issue over long time scales. However, other wetland tracer studies with comparable residence times (Lin et al., 2003; Martinez and Wise, 2003) showed bromide to be conservative. Sonon and Schwab (2004) successfully used bromide to monitor water movement through laboratory sediment columns. All

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130 commonly used hydrologic tracers are conservative under certain environmental conditions. Bencala et al. (1990) argues that “the definition of ‘conservative tracer’ ultimately becomes operational; a chemical is conserved in the transport of solutes if, in a given situation, concentration changes cannot be detected beyond those known to be attributable to inflow addition or dilution.” Regardless of a few unsuccessful experiments, bromide still appears to be the best available and feasible hydrologic tracer.

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BIOGRAPHICAL SKETCH Steven Collins was born on October 8 th , 1981 in Baltimore, MD. In 1992 he moved to Shrewsbury, PA and graduated from Susquehannock High School in 1999. He obtained his Bachelors of Science degree in biological systems engineering from Virginia Tech in 2003. In August 2003, he married Anne Marie Hewitt near their hometown in Pennsylvania. He then entered the graduate program at the University of Florida and earned a Master of Engineering degree from the Department of Agricultural and Biological Engineering in August of 2005. Steven has held a lifelong passion for nature, and his experiences in the Appalachian Mountains of Virginia and the lowlands of Florida have been unforgettable. He is eager to further pursue his wildlife interests including birds, dragonflies, butterflies, and robberflies. 149