Animal Waste Lagoon Water Quality Study

A Research Report by Kansas State University

June 23, 1999

Principal Investigators

J.M. Ham, Department of AgronomyL.N. Reddi, Department of Civil Engineering

C.W. Rice, Department of Agronomy

Submitted in partial fulfillment of a contract between Kansas State University and the KansasWater Office, Topeka, KS.

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Executive Summary

Animal Waste Lagoon Water Quality Study

J.M. Ham, L.M. Reddi, and C.W. RiceKansas State University

Report Period: May, 1998 to June, 1999

Anaerobic lagoons are used to collect, treat, and store waste at many concentrated animaloperations (CAOs) in Kansas. Lagoons contain nutrients, salts, and other soluble chemicals that, in manycases, are eventually applied to crops as fertilizer. While waste is stored and treated in the lagoons,seepage losses from the sides and bottom of the containment could potentially affect soil and groundwater quality. Of primary concern, is possible movement of nitrate-nitrogen into aquifers used to supplydrinking water. Bacteria, which also are present in the waste, are another potential source forcontamination. A comprehensive environmental assessment of lagoons requires three focus areas: (a)toxicity – what are the constituents in the lagoon waste that pose a threat to water quality and publichealth? (b) input loading – at what rate does waste seep from a lagoon under field conditions? and (c)aquifer vulnerability – how do soil properties, geology, and water table depth affect the risk of wastemovement from the lagoon to the ground water? Researchers at Kansas State University (KSU), incooperation with the Kansas Water Office, are conducting research to examine these issues. The long-term goal is to determine the best management practices for siting, building, and operating lagoons toadequately protect ground water resources near CAOs. The KSU research project includes: (1) a survey oflagoon effluent chemistry at swine production facilities, cattle feedlots, and dairies; (2) refinement of newmeasurement techniques to measure whole-lagoon seepage under field conditions; (3) measurement oflagoon seepage and subsurface nitrogen movement at commercial swine and cattle CAOs; (4) laboratorystudies of permeability and contaminant transport in soils used to construct lagoon liners; and (5)preliminary computer modeling of water and waste movement in soils beneath lagoons. This reportsummarizes current research findings in these areas. However, new issues continue to arise as more databecomes available. Thus, this report documents the state of an ongoing project, and certain topics willrequire additional research before firm conclusions can be reached.

1. Survey of Lagoon Effluent Chemistry. Samples of lagoon effluent were collected from fiveswine-waste lagoons and four cattle-feedlot runoff lagoons across Kansas (Appendix A). Samples weresometimes collected several times throughout the year to examine seasonal trends. Analysis includedtwenty-five chemical and physical characteristics. Ammonium-nitrogen (NH4

+-N) accounted for over 99% of the soluble nitrogen and averaged 673 mg/L (ppm) at swine waste lagoons and 98 mg/L (ppm) at thecattle sites. Ammonium-N typically ranged from 550 to 900 mg/L (ppm) at swine sites and from 20 to200 mg/L (ppm) at cattle feedlots. The highest ammonium-N concentration, 2000 mg/L (ppm), wasobserved at swine site in the first stage basin of a two-stage lagoon system (concentration was muchlower in the second stage lagoon). Nitrate concentrations were less than 3 mg/L (ppm) at all locations.Total phosphorous averaged 45 mg/L (ppm) across all samples and was similar at the cattle and swinelagoons. On average, sodium was 148 mg/L (ppm) at the cattle feedlots and 270 mg/L (ppm) at the swinesites. Chloride was 275 and 569 mg/L (ppm) at the swine and cattle sites, respectively. Concentrations ofnutrients did not vary substantially with depth in the liquid zone above the bottom-sludge layer.However, the organic sludge in the bottom of lagoons did contain higher concentrations of phosphorus.In most cases, strong seasonal patterns in waste chemistry were not evident. At some swine sites,ammonium-N in spring tended to be about 200 mg/L (ppm) higher than that observed in late fall. Resultsshow that waste chemistry is species dependent, with nitrogen concentrations at swine sites being aboutsix times higher than those at cattle feedlots. Conversely, chloride tended to be higher in cattle-feedlotrunoff lagoons. The design and management of the waste treatment system (e.g., single-stage vs.multistage lagoons, lagoon volume vs. size of runoff watershed) also affected waste chemistry. The largesite-to-site variation in chemical concentrations could affect the risk of ground water contamination andinfluence decisions regarding the land application of waste.

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2. Refinement of New Measurement Techniques. Tests were conducted to verify the accuracyof field techniques for measuring whole-lagoon seepage using water balance methods (Chapter 1).Seepage was calculated as the difference between waste level changes (depth) and evaporation when allother lagoon inflows and outflows were precluded. Precision water level recorders, evaporation pans,floating meteorological buoys, and evaporation models were developed and tested to measure the waterbalance. Results showed that seepage could be measured to within ±0.5 mm/day (0.02 inch/day) over abrief study periods (5 to 10 days) when the evaporation was less than 6 mm/day (0.23 inch/day) Duringthe winter months, when evaporation was small, seepage was estimated to within 0.2 mm/day (0.01inch/day). Data show that much can be learned about the performance of a lagoon by simply measuringchanges in depth over time during the winter.

3. Measurement of Lagoon Seepage and Subsurface Nitrogen Movement. Whole-lagoonseepage rates were measured from seven swine-waste lagoons and two cattle-feedlot runoff collectionlagoons (Chapter 2). The earthen lagoons ranged in size from 0.2 to 2.5 ha (0.1 to 5.5 acres) and hadwaste depths between 1.5 and 6 m (5 to 18 ft.) Seven of the lagoons had waste depths in excess of 5 m(16 ft.). Most lagoons had compacted soil liners between 0.3 and 0.5 m (12 and 24 inch). The averageseepage rate from the lagoons was 1.2 mm/day, or 0.05 inch/day (approx. 1/20 inch/day). Amonglagoons tested, seepage ranged from 0.2 to 2.4 mm/day (Chapter 3). At some locations, seepage resultswere combined with data on lagoon geometry and construction methods to estimate the in-situpermeability of the liner. In lagoons built with silt loam liners (no bentonite), permeability's on a whole-lagoon basis were about five times less than those measured from soil cores collected prior to the additionof waste. Results imply that permeability was reduced by organic sludge on the bottom of the lagoons.Field measurements showed that the organic sludge layer was 0.38 m (15 inches) thick in a four-year-old,swine-waste lagoon.

Despite the low rates of seepage, calculations showed that subsurface ammonium-N losses fromthe bottom and sides of swine-waste lagoons could exceed 3000 kg/ha·yr (2,640 lbs./acre·yr) (Chapters 2and 3). Over twenty years of operation, nitrogen losses at a 2-ha (5-acre) swine-waste lagoon couldpossibly exceed 110,000 kg (250,000 lbs.) Seepage losses of ammonium-N from cattle feedlot lagoonsare much lower because the soluble nitrogen in the effluent is less concentrated.

Soil cores were collected in a 6-m zone (20 ft.) beneath an eleven-year-old cattle feedlot lagoonthat had been emptied, dried, and cleaned (i.e., sludge removed). Ammonium-N concentrations were near400 mg/kg, or ppm, near the lagoon “floor” and then deceased rapidly with depth (Chapter 2). About 90% of the nitrogen found beneath the lagoon was within 3.6 m (12 ft.) of the lagoon. No nitrate-nitrogenwas found in any of the soil samples. Data show that ammonium-N, a positively charged ion, was beingadsorbed by negatively charged soil particles (i.e., clay minerals). Soils with a large cation exchangecapacity, (CEC, a measure of soil ion adsorptive capacity), can retard the movement of ammonium-N anddecrease the risk of ground water contamination. However, ammonium-N is not stable and could convertto nitrate, especially if a lagoon is emptied and dried following abandonment or closure. Nitrate is a verymobile in the soil and could potentially move to deeper depths (toward ground water), especially inregions with high rainfall. Additional research is needed to determine the long-term fate of ammonium-Nadsorbed by soil directly beneath lagoons. Best management practices should be developed forremediation and closure of lagoon sites.

4 and 5. Laboratory Studies of Soil Permeability and Computer Modeling. Laboratory andmodeling studies were conducted to examine the leachability characteristics of compacted soil samplesspecific to Kansas, and to assess how the properties of a compacted soil liner may affect the movement ofammonium-N in waste seeping from earthen lagoons. Soils were compacted in permeameters in thelaboratory and exposed to a lagoon effluent for 2 to 5 months in a leaching experiment (Chapter 4). Thewaste used was liquid from the upper portion of the lagoon, not the organic bottom-sludge. In some cases,the seepage rate through the soil samples decreased slightly over time. However, biological cloggingfrom microbial exudates did not appear to be a significant factor affecting soil permeability. Data supportthe premise that the waste-induced reductions in permeability, often observed in these studies, is causedby physical clogging of the soil pores rather than by microbial action. Seepage may be more prevalentalong the side embankments of lagoons where organic sludge may not accumulate.

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Analytical and numerical simulations were used to simulate ammonium-N movement in field-scale liners and to estimate the upper bounds for travel times and end concentrations in the underlyingsoils (Chapter 5). Results showed that liner thickness and CEC had drastic effects on how fast nitrogenmoved through the liner. For example, in one simulation increasing liner thickness from 0.15 to 0.9 m(0.5 to 3 ft.) caused a nine fold reduction in the concentration of ammonium-N exiting the bottom the soilliner and increased the time required for ammonium-N to penetrate the liner from 5 to 65 years. Theextent of possible retardation, decay, and saturation levels of ammonium-N, observed in this study,suggests that properties such as CEC and microbial uptake, which influence mass transport ofammonium-N, should be given important consideration in designing liners for animal waste lagoons.

Some of the important results and implications of the research project are:• The concentration of ammonium-N was six times higher in swine-waste lagoons than in

cattle-feedlot runoff lagoons. Thus, the rate of input loading and the potential for subsurface nitrogencontamination is species dependent. Conversely, phosphorous, the element that often affects the rateat which effluent can be land applied, was the same at cattle and swine facilities.

• Field, laboratory, and simulation studies suggest that most animal-waste lagoons in Kansas willhave seepage rates less than 2.5 mm/day (1/10 inch/day), well below the historical deign standard of1/4 inch/day used by the Kansas Dept. of Health and Environment. Lagoons that have engineeredsoil liners greater than 0.46 m thick (18 inch) often seep at rates near 1 mm/day (less than 1/20th

inch/day) even when waste depth exceeds 5 m (16 ft.). However, even at low seepage rates, datashow that significant amounts of ammonium-N can be deposited and stored in the soil beneath thelagoons. When lagoons are closed, emptied, and dried, soil-bound ammonium-N could convert tonitrate and more readily move towards the ground water. At many locations, the period followinglagoon closure may pose the greatest risk of ground water contamination. Best management practicesshould be developed for lagoon closure and site remediation.

• The rate at which nitrogen is adsorbed and retarded beneath a lagoon is highly dependent on thesoil cation exchange capacity (CEC). The CEC of the compacted liner and the underlying native soilshould be considered when siting and designing a waste lagoon. Increasing the thickness of soilliners with high-CEC clays could help trap ammonium-N, prevent its downward migration, andsimplify closure and remediation procedures (by trapping contaminants close to the surface). Moreresearch is needed on the fate and transport of chemicals and bacteria that penetrate the liner.

• Future research should focus on chemical and physical factors in the soil that affecttransformation and movement of chemicals and microbes between the bottom of the lagoon and thewater table. This research could ultimately lead to models of the lagoon system that consider toxicity,input loading, and aquifer vulnerability. Because of the tremendous variation in the physicalenvironment (e.g., depth to water table, soils, climate, etc.) and types of livestock operations, anaccurate risk assessment of lagoon use in Kansas must be site and species specific.

Respectfully Submitted,

Jay M. Ham, Ph.D.June 23, 1999

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Table of Contents

Executive Summary

Table of Contents

Preface

Chapter 1 Measuring Evaporation and Seepage Losses from Lagoons Used to Contain Animal WasteJ.M. Ham

Chapter 2 Field Evaluation of Animal-Waste Lagoons: Seepage Rates and Subsurface Nitrogen TransportJ.M. Ham and T.M. DeSutter

Chapter 3 Seepage Losses and Nitrogen Export From Swine-Waste Lagoons: A Water Balance StudyJ.M. Ham and T.M. DeSutter

Chapter 4 Liner Performance – Experimental InvestigationsL.N. Reddi, H. Davalos, and M. Bonala

Chapter 5 Liner Performance – Modeling InvestigationsL.N. Reddi, H. Davalos, and M. Bonala

Appendix A Survey of Waste Chemistry in Anaerobic Lagoons at Swine Production Facilities and Cattle Feedlots.T.M. DeSutter, J.M. Ham, and T.P. Trooien

Appendix B References On Animal Waste Lagoons and Related TopicsT.M. DeSutter and J.M. Ham

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Preface

This report was completed in partial fulfillment of a contract between Kansas StateUniversity and the Kansas Water Office. The current report covers the period between May1998 and June 1999. A second year of research has been planned and will be documented in areport scheduled for release in June 2000. Thus, some of the research topics examined in thisreport will be updated and refined as new data become available.

Results from this project build on previous work completed in cooperation with theKansas Department of Health and the Environment (KDHE). Results from this early work werepresented in a report entitled “Evaluation of Lagoons for the Containment of Animal Waste”submitted to KDHE in April 1998.

Some of the research findings in Chapters 1, 2, 4 and 5 of this report have been acceptedfor publication in peer-reviewed scientific journals (Journal of Environmental Quality, andTransactions of Amer. Soc. Agric. Engineers). Some portions of the report have been submittedfor publication to Amer. Soc. Civil Engineers Journal of Geotechnical and GeoenvironmentalEngineering.

Because each chapter was completed separately, there may be small chapter-to-chaptervariations in certain calculated parameters. Calculations were refined as improved methods andnew data became available.

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Publication Version (SW-3416)

CHAPTER 1

Measuring Evaporation and Seepage Losses from

Lagoons Used to Contain Animal Waste

Jay M. Ham

May 24, 1999

Article was submitted for publication in February 1999 and approved for publication bythe Soil and Water Div. of ASAE in May 1999.

Mention of product name is for information only and does not imply endorsement.

Contribution no. 99-326-J from the Kansas Agric. Exp. Stn., Manhattan, KS.

The author is Jay M. Ham, ASAE Member, Associate Professor, Dept. of Agronomy,Kansas State University, Manhattan, KS 66506.; e-mail snafu@ksu.edu

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ABSTRACT. Seepage (S) from animal-waste lagoons was estimated using a water balanceapproach by measuring changes in waste level (i.e., depth) (∆D) and evaporation (E) over briefperiods (e.g., 6 days) when all other inflow and outflow were precluded. Data were collected atcommercial swine and cattle feedlots in southwestern Kansas. Precision waste level recorders,floating evaporation pans, and meteorological models were used to measure each lagoon’s waterbalance. Different strategies for calculating E and S were compared. Initial work at a 2.5-haplastic-lined lagoon (S = 0, E ≈ 5.1 mm d-1) showed that E over 6- to 11-day periods could bemeasured to within ±0.5 mm d-1 with floating evaporation pans using a pan coefficient of 0.81.A bulk-transfer evaporation model, which incorporated real-time measurements of lagoonsurface temperature, predicted E to within 6 % when using a transfer coefficient of 2.8x10-3.Evaporation models that did not include surface temperature resulted in significant errors (e.g.,>50 %) under certain environmental conditions. The water balance of a soil-lined, cattle-feedlotlagoon over an 11-day period was: ∆D=2.1; E=1.9, and S= 0.2, all in mm d-1. Additional workover a 6-day period at a soil-lined, swine-waste lagoon resulted in a water balance of: ∆D = 5.4;E=4.5, and S = 0.9, all in mm d-1. Data suggest that S from lagoons can be determined to within± 0.5 mm d-1 by making precision water balance measurements over short periods (5 to 10 days),if E is less than 6 mm d-1. Keywords. Feedlot, Instrumentation, Pan Evaporation, Swine, WaterBalance.

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IntroductionEarthen-lined lagoons have been used extensively since the 1960s to collect, treat, and

handle waste from concentrated animal operations (CAOs) (Humenik et al., 1980). In 1992,there were more than 6,600 CAOs in the United States that had more than 1000 animal units, andmost of these facilities used lagoons as part of their waste management plan (Kosco and Hall,1999). The liquid waste in lagoons contains high concentrations of nutrients and salts and, inmany cases, is applied to farmland as fertilizer. However, while waste is being stored in thelagoon, seepage losses from the sides and bottom of the basin can impact soil and groundwaterquality (Miller et al., 1976; Culley and Phillips, 1989; Huffman and Westerman, 1995;Westerman et al., 1995). Unfortunately, measuring or predicting the rate at which solutes aretransported from a lagoon is difficult. Attempts to predict seepage through field-installed earthenliners using laboratory measurements of soil permeability have been disappointing (Daniel,1984). A host of factors, such as variation in construction methods, weathering of sideembankments, and organic sludge (manure) deposits all impact the long-term, in-situ seepagerate (Hills, 1976; Barrington and Madramootoo, 1989; McCurdy and McSweeney, 1993). Areview of the literature on this topic is provided by Ham and DeSutter (1999). Although solutetransport from a lagoon is a complex process, knowledge of seepage is necessary to calculatechemical flux and nutrient loading. These parameters, coupled with the effect of aquifervulnerability, are crucial for assessing the site-specific impact of a lagoon on local groundwaterquality (Nolan et al., 1997). Additionally, many regulatory agencies have mandated that lagoonsmust be designed to limit seepage to within a specified range. Thus, improved techniques for therapid determination of whole-lagoon seepage would benefit both academic and practical aspectsof lagoon design and use.

Several researchers have estimated seepage from existing animal-waste lagoons usingwater balance approaches (Hart and Turner, 1965; Davis et al., 1973; Robinson, 1973; Clark,1975). Typically, seepage was calculated as the difference between changes in waste level andevaporation when waste inputs and outputs were precluded or quantified. Much of this previouswork was conducted on miniature, pilot-scale lagoons and may not be representative of the largelagoons used at many modern CAOs. Furthermore, the resolution of the techniques used inmany earlier studies was such that water balances had to be conducted for long periods (>30days) to obtain a useful estimate of seepage. Unfortunately, withholding waste inputs forextended periods is not logistically feasible at many commercial CAOs, because waste must beflushed from the barns (e.g., swine and dairy) on a routine schedule. Recently, Ham andDeSutter (1999) estimated the water balances of three commercial swine-waste lagoons bymeasuring depth changes and evaporation over measurement cycles as brief as 5 days.Combining these data with measurements of nutrient concentrations in the effluent, they wereable to calculate subsurface nutrient export from each facility. Also, seepage results werecoupled with data on liner thickness and basin geometry to calculate the apparent in-situpermeability of the compacted soil liner.

The objective of this research was to evaluate water-balance strategies for determiningwhole-lagoon seepage using data collected over brief measurement periods (e.g., 6 days). In awater balance approach, seepage is calculated as a residual, and the adequacy of the methodoften hinges on the accuracy and resolution of the water level and evaporation measurements.Although there are many ways to measure water level, determining evaporation from smallisolated water bodies (i.e., lagoons) is challenging from both theoretical and instrumentationstandpoints (Webster and Sherman, 1995). Thus, this study emphasized the measurement of

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evaporation from lagoons, exploring the use of custom-built floating evaporation pans andmeteorological models. Data from plastic- and soil-lined animal waste lagoons were used toquantify the expected resolution to which seepage can be determined from a short-term waterbalance experiment.

METHODS AND EQUATIONSDescription of the Lagoons

The three lagoons used for the study, hereafter referred to as A, B, and C, were locatedwithin 40 km of Ulysses, KS (table 1). Lagoon A , built in 1996, serviced a swine finishing unitand had a 1-mm thick plastic liner over 0.3 m of compacted soil. Lagoon B, located within 3 kmof Lagoon A and built in 1995, also serviced a swine finishing unit but had a 0.46-m-thickcompacted soil liner. Compaction was performed in 0.15-m lifts by means of six passes with asheepsfoot roller. Bentonite (9.8 kg m-2) was mixed into the initial 0.15-m compacted layer,followed by 0.3 m of compacted silt loam soil obtained from a barrow area. Lagoon C collectedrunoff from a cattle feedlot and had a compacted soil liner between 0.46 and 0.6 m thick. Likethe swine lagoons, compaction was performed in multiple lifts with a sheepsfoot roller. LagoonC was 11 years old, but it had been cleaned and a new compacted liner had been constructedthree months prior to water balance tests. The capacity (i.e., depth) of the lagoon was increasedas part of the cleaning process, so any residual effects on soil hydraulic properties (i.e., sludgeeffects) probably were negated. The coefficients of permeability for the compacted soil liners atLagoons B and C were evaluated from cores collected from the bottom and sides of each basin.Six cores from Lagoon B and four cores from Lagoon C were obtained prior to the addition ofwaste. Permeability was measured using an ELE flexible wall permeameter (Soiltest ProductsDivision, ELE International Inc., Lake Bluff, IL) following ASTM Designation D 5084-90(1991) (table 1). Dry densities of the soil liners, as determined from the cores, averaged 1887and 1670 kg m-3 at Lagoons B and C, respectively.

Water BalanceSeepage and evaporation from each lagoon was determined by quantifying the water

balance, Q + S+ E =D + P + Q outin ∆ (1)

where Qin is waste inflow; P is precipitation, E is evaporation; S is seepage loss; Qout is wasteoutflow (i.e., pumping); and ∆D is the rate change in storage, all in mm d-1. In equation (1), allvariables are considered positive with the exception of ∆D , which is negative when waste levelsare increasing and positive when declining. During periods used for analysis, waste inflow andoutflow were stopped and precipitation did not occur (Qin = Qout = P = 0); thus, S from theearthen lagoons (B and C) was calculated as the difference between E and ∆D (S = ∆D - E). Atthe plastic-lined lagoon (Lagoon A), S was assumed to be negligible, so ∆D was equal to E.Therefore, work at the plastic-lined Lagoon A was used to test methods for measuring E, andwork at soil-lined Lagoons B and C was used to evaluate the combined effect of ∆D and E on thecalculation of S.

Meteorological Instrumentation and Floating Evaporation PansMuch of the instrumentation used in these experiments was similar to that described by

Ham and DeSutter (1999). An abbreviated description is provided here. Evaporation in eachlagoon was measured using two floating evaporation pans (figure 1). An instrument raft, 1.5 m

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wide and 2.7 m long, was built from two low-profile flotation panels (Superdeck Marketing,Minneapolis, MN) held together by aluminum channel. An area between the flotation panelssupported a square evaporation pan (1.09 m by 1.09 m by 0.591 m) made from 0.8-mm-thickgalvanized sheet metal or aluminum. The floating pan had the same surface area as a Class-Aevaporation pan. When installed, the pan held 0.23 m of waste with a 0.15-m rim extendingabove the waterline. Waste levels in the pans were monitored continuously using a float-baseddetector housed in a 0.15-m diameter wet well mounted in the corner of the pan (see figure 2 inHam and DeSutter, 1999 for a mechanical drawing of the recorder). A linear displacementtransducer (LX-PA25, Unimeasure Inc., Corvallis, OR), consisting of a retractable leader andpotentiometer, was used to sense changes in float height. A vibrator was attached permanentlyto the LX-PA25 and activated automatically every 30 min to overcome static friction in the reelmechanism. Water pumps were mounted inside and outside the pans so waste could be added orremoved by remote control. Four 0.3-m diameter wheels were mounted on the underside of thefloating platform so it could be rolled up or down the lagoon’s side embankment to facilitateinstallation and retrieval.

Waste-level changes, ∆D, in each lagoon were measured with a float-based recorderidentical to the one used in the pans. For work at Lagoon C, a Unimeasure model LX-PA50 wasused to measure ∆D. The recorders were attached to permanent staff gauges already present ineach lagoon (usually a vertical steel pipe set in concrete). Meteorological conditions 1 m above the waste surface were monitored using sensorsattached to a small mast on one of the floating platforms. Instrumentation included: a three-cupanemometer and wind vane (Wind Sentry, RM Young, Traverse City, MI); a shielded, airtemperature and humidity probe (CS500 or HMP35C, Campbell Sci. Inc., Logan, UT); and apyranometer (LI200, Li-Cor Inc., Lincoln, NE). Water temperatures 0.1 m below the surfacewere measured inside and outside the evaporation pan with thermistors (107 Probe, CampbellSci. Inc). Water surface temperatures inside and outside one of the evaporation pans weremeasured with infrared transducers (IRT, model 4000A, Everest Interscience, Logan, UT). AllIRTs were calibrated using the method of Sadler and Van Bavel (1982) and corrected for surfaceemissivity and downwelling atmospheric radiation using the approach of Ham and Senock(1994). At Lagoons A and C, a single IRT was mounted on an actuator that alternately aimed thetransducer at waste inside and then outside one of the evaporation pans on a one minuteexchange cycle. Using this approach, the pan’s effect on waste surface temperature could bemeasured without instrument bias. Sensors on each floating platform were sampled every 10 s,and data were stored as 30-min averages using a datalogger (CR10X, Campbell Sci. Inc.). Thedatalogger was housed in a weatherproof enclosure on the flotation deck and was powered by a12-volt battery connected to a 10- or 20-W solar panel. A cellular telephone and modem wereused to transfer data from each platform to laboratories in Manhattan, KS. The telephoneinterface also allowed remote control of the water pumps, which were used to keep the wastesurface in the pan to within 25 mm of the lagoon’s surface. The resolution of the water levelmeasurements in the pans and at the staff gauge was 0.16 mm when sampled by the CR10X,except at Lagoon C where the resolution of ∆D was 0.32 mm.

Two floating evaporation pans, the lagoon waste level recorder, and the associatedmeteorological equipment were deployed at each site. The positions of the floating pans weredetermined by mapping the lagoon surface into two zones of equal area and then placing a pan inthe center of each zone. The floating pans were tethered to the side embankments using steelcables and were at least 50 m from the shoreline in all directions. Waste inputs to the lagoons

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were stopped periodically for 6 to 11 day periods by capping the waste inlet pipes at the swinesites or by damming the lagoon inlet channel at the cattle feedlot.

Evaporation ModelsEvaporation from the lagoons also was estimated using four meteorological models. An

approach that has been used widely to estimate E from open water is the bulk aerodynamictransfer model (hereafter referred to as BT model)

)( * asre qqUCE −= ρ (2)where E is evaporation (kg m-2 s-1); ρ is air density (kg m-3); qs* is the saturated specific humidityat water surface temperature (kg kg-1), qa is the specific humidity of the air (kg kg

-1), Ur is theaverage wind speed at some reference height (m s-1), and Ce is the bulk aerodynamic transfercoefficient for vapor transport (dimensionless). An approximation of equation 2 expressed interms of vapor pressure is

( ) erassd

CUeeTR

E −= *622.0

(3)

where es* is the saturation vapor pressure at the temperature of the water surface (Pa), ea is the

vapor pressure of the air (Pa), Rd is the gas constant (287.04 J kg-1 K-1), Ts is the temperature of

the surface (K) and 0.622 is the ratio of the molecular weights of water and dry air. Equations 2and 3 have been used extensively to estimate E from lakes and ponds (Lakshman, 1972; Quinn1979; Bill et al., 1980; White and Denmead, 1989). Field studies are often conducted todetermine Ce empirically by measuring (es

*-ea) and Ur under conditions where E is measured bysome other method. Values of Ce range from 1.0x10

-3 to 2.0x10-3 when Ur and ea are measured2 to 3 m above the surface (Brutsaert, 1982). However, Ce is dependent on measurement heightof Ur and ea, and increases as the reference height decreases.

Penman (1948) introduced a combination model for predicting E from open water thatavoided the need for Ts

eraaad

CUeeTRL

GRnE )(

622.0 * −

+∆

+

+

+∆∆

=γ

γγ

(4)

where ∆ is the slope of the saturation vapor pressure curve (Pa K-1), γ is the psychrometricconstant (Pa K-1), Rn is net radiation (W m-2), G is conduction in the water (W m-2), L is thelatent heat of vaporization (J kg-1), Ta is air temperature (K), and ea

* is the saturation vaporpressure at Ta (Pa). The sign convention for Rn and G is given in equation 8. The advantage ofthe Penman model is that it can be approximated using basic meteorological data collected in theboundary layer of the surface of interest. However, the determination of Rn+G for shallow waterbodies can be difficult. For the lagoons, Rn was approximated as

4986.0 −= RsRn (5)where Rs is global shortwave irradiance (W m-2). This relationship was determined empiricallyfrom simultaneous but independent measurements of Rs and Rn over an animal waste lagoon(Ham et al., 1998). The net change in heat storage in the lagoon waste was assumed to benegligible between the start and end of a multiple-day measurement cycle. Thus, G was set tozero in the computations, negating the effect of diurnal patterns in G, but hopefully stillpreserving the long-term energy balance.

Priestley and Taylor (1972) proposed a model for E from extended wet surfaces where theinternal boundary layer reached equilibrium with the surface

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+

+∆∆

=L

GRnE

γα (6)

where α is the empirical Priestley-Taylor coefficient (1.26). Like the Penman equation, Rn wasapproximated with equation 5 and G was assumed to be negligible over multi-day periods. Eventhough equation 6 was developed for expansive surfaces where no advection occurs, Stewart andRouse (1976) used equation 6 to approximate E from small ponds. The Priestley-Taylor modelonly requires a measurement of Rs and Ta.

The last model tested was that of DeBruin (1978) which is a hybrid of the Penman andPriestley-Taylor equations

eraaad

CUeeTR

E )(622.0

1* −

+∆∆

−=

γαα

(7)

This approach eliminates the need for the troublesome determination of Rn+G and requiresmeasurements of wind speed, temperature, and humidity. However, equation 7 is sensitive to α,which has been shown to vary seasonally.

Evaporation was calculated with each model using environmental data obtained from thefloating instrument rafts. When the bulk transfer and DeBruin models (equations 3 and 7) wereused, E was calculated every 30 minutes using the short-time-interval meteorological data.Results were then summed over 24 hr to estimate daily E. However, when using the Penman andPriestley-Taylor models (equations 4 and 6), E was calculated on a daily basis using the 24-hraverage of Ta, U, and ea

*-ea in combination with total Rn accumulated over the same period.

Surface Energy BalanceFor evaluation of E, it is helpful to quantify the surface energy balance, often expressed

as0=+++ HLEGRn (8)

where H is sensible heat flux (W m-2). As shown here, all fluxes toward the surface areconsidered positive whereas all those away from the surface are negative. For example, LE isnegative (unless condensation occurs), and G is positive when conduction is upwards toward thesurface (e.g., water cooling at night) and negative when conduction is downward (e.g., daytimewater heating). The magnitude of H can be modeled with a bulk transfer approach like that usedfor water vapor in equation (2).

hrsap CUTTcH )( −= ρ (9)where cp is the specific heat of air (J kg

-1 K-1) and Ch is the bulk aerodynamic transfer coefficientfor heat transfer. To solve equation 9 at the lagoons, Ch was assumed to be equal to Ce, which isa common procedure in these types of studies (Quinn, 1979; Bill et al., 1980). Once H wascomputed from equation 9 and Rn and E were calculated using equations 3 and 5, G wascalculated as a residual using equation 8.

Equations 2 through 9 include several variables ( e*, ea, ∆, γ, ρ, cp, L) that must becalculated from real-time environmental data. Appendix 1 provides suitable equations forcalculating these variables using computerized, data acquisition equipment.

RESULTS AND DISCUSSIONData were collected at the plastic-lined Lagoon A to evaluate the performance of the

floating evaporation pans and the evaporation models. Assuming that S was zero, actual E fromthe whole lagoon was the rate change in lagoon depth (∆D) as measured by the waste-level

1.8

recorder on the staff gauge. The waste level recorders were rigorously tested by Ham andDeSutter (1999) and found to be extremely accurate and stable (e.g., ± 0.16 mm). However, theoutput from the recorders at any given time can be biased by short-term changes in wind speedand direction. Wind drag can cause water levels to rise near the downwind embankment and fallon the upwind side of the lagoon. Sample calculations using the approach of White andDenmead (1989) indicated that errors in ∆D caused by wind drag would be less than 1 mm.Nevertheless, comparisons between ∆D , evaporation from the floating pans, and output from themodels were made on a cumulative basis or over multi-day periods to minimize bias anddiscretization error (i.e., effect of instantaneous sensor resolution). Table 2 shows environmentalconditions and the cumulative depth changes (or E) at Lagoon A for 9- and 11-day measurementperiods in October 1998.

Performance of the Floating Evaporation PansTable 3 shows E from Lagoon A and the two floating evaporation pans as totaled over

six, 3-day periods. The period between day of year (DOY) 284 and 285 was omitted becausehigh wind gusts (>15 m s-1) may have caused some incursion into the pans from large waves.Evaporation in the pans was significantly greater than that in the lagoon. The pan coefficient(Kp), defined as the ratio of lagoon E and pan E (Kp=Elagoon/Epan), ranged from 0.69 to 0.94during the study. The lowest Kp occurred between DOY 258 and 260, which was a period ofhigh solar irradiance and low wind speeds. Conversely, the largest Kp occurred when windspeeds where higher and global irradiance was slightly lower (DOY 286-288). The coefficientsfor the two pans were similar in any given period, and both pans had an overall average Kp of0.81. Figure 2 shows cumulative E from the lagoon and the two pans during the twomeasurement cycles at Lagoon A. When depth changes in the pans were multiplied by a Kp of0.81, the pan estimates of E were in excellent agreement with the whole-lagoon measurements.Cumulative E estimated by the pans (Pan Result x Kp) was typically within 5 % of that measuredfor the lagoon, especially when summed over periods greater than 5 days.

The finding that Kp was less than unity but varied according to environmental conditionswas consistent with other studies where on-shore, Class-A evaporation pans were compared toactual lake evaporation (Brutsaert, 1982). However, pans floating in a water body shouldexperience a more natural microclimate and have a Kp closer to unity. In this study, thetemperature and humidity of air flowing over the waste in the floating pans were essentially thesame as those for air over the lagoon. Furthermore, the pan being in direct contact with thelagoon waste should have helped keep waste temperature (and vapor pressure) in the pan closerto lagoon temperature. Figure 3 shows the temperature regime during the first measurementperiod at Lagoon A. Daytime surface temperatures of the waste in the evaporation pans weregreater than those in the lagoon, sometimes by as much as 4 C (figure 3b). The exception wasbetween DOY 264 and 265, when air temperatures dropped as a cold front passed through andconditions were overcast. At night, the pan temperatures were often 2 C less than the lagoon.Pan and lagoon waste water temperatures at 10 cm had a similar pattern (not shown). Divergencein pan and lagoon temperatures was probably caused by a combination of radiant heating andconvection on the 0.15-m sidewall of the pan that extended above the water line. Furthermore,the waste water in the pan it did not experience the natural mixing caused by wave action andthermal gradients. Wind speed, which affected convection and surface mixing, was correlatedwith Kp. For example, between DOY 281 and 288, the average wind speed was 4.7 m s

-1 and Kpaveraged 0.91. Conversely, between DOY 258 and 260 and between DOY 278 and 280, the

1.9

average wind speed was 2.3 m s-1 and Kp averaged 0.73. A mixture of radiation, convection, andsurface mixing effects probably accounted for the variation in Kp observed in table 3. Regardless,because evaporation is strongly governed by the vapor pressure at the surface (equation 2), theelevated pan temperatures during the day caused overall pan evaporation to be greater thanlagoon evaporation.

Performance of the Evaporation ModelsThe first step in applying the evaporation models was to empirically determine Ce by

solving equation 3 using measured values of E, Ur, and (e*s - ea) from the plastic-lined Lagoon A.

Least squares analysis showed that the best choices for Ce were 2.81x10-3 between DOY 258-267

and 2.83x10-3 between DOY 283-289. These values are higher than reported in similarexperiments over lakes (Brutsaert, 1982). However, Ur and ea at the lagoons were measuredmuch closer to the surface than in previous studies (1 m as compared to 2 or 3 m); thus, anincrease in Ce would be expected. Furthermore, equation 3 as well as all other methods used toestimate E, did not account for horizontal advection which can increase E from fetch-limitedwater bodies like lagoons (Itier et al., 1994; Webster and Sherman, 1995). This effect may haveamplified Ce. A constant Ce of 2.81x10

-3 was used for all calculations involving equations 3, 4,6, and 7.

Table 4 compares actual E from the plastic-lined Lagoon A with that predicted using fourdifferent meteorological models. Data between DOY 278 and 282 were not used because theIRTs were accidentally turned off disallowing the evaluation of equation 3. Of the modelstested, the BT model (equation 3) provided the best estimate of E, having a maximum error of±0.6 mm d-1 within any 3-day period and an overall error of only 0.1 mm d-1. On average, thePenman model (equation 4) also was accurate to within 0.1 mm d-1; however, errors of –3.6 and2.1 mm d-1 occurred for the measurement periods starting on DOY 264 and 286, respectively.The Priestley-Taylor model (equation 6) tended to underestimate E on most days. The DeBruinmodel (equation 7) produced mixed results but severely overestimated E between DOY 283 and288, which was a period of high wind speeds (table 2). Because of this undesirable result,further analysis of the DeBruin model is not presented.

Performance of the other models was evaluated further by examining the energy balanceof Lagoon A (table 5). Large period-to-period variation occurred in the energy fluxes, especiallyin H and G, terms that were both sources and sinks of energy. Comparisons of the periodsstarting on DOY 261 and 264 were particularly interesting, because a transition occurred fromwarm clear conditions to cool cloudy weather. Average daily Rn decreased from 168 to 61 Wm−2 as expected under cloudy skies; however, LE remained essentially constant. Results showthat LE between DOY 264 and 266 was driven by massive upward conduction of the heat storedwithin the liquid waste (G=173.7). Figure 3a shows that the waste temperature was up to 10 Chigher than the air temperature, which helped create the upward gradient. Both the Penman andPriestley-Taylor models severely underestimated E during this period as a result of theassumption that G was zero. Conversely, when a warming trend occurred, and G was downward(DOY 286-288), the Penman model overestimated E. Tables 4 and 5 show that energy-basedmodels like the Penman and Priestley-Taylor may result in significant errors during short-termexperiments unless G is measured directly.

When a water balance is performed to determine S, cumulative E, not daily E, is mostcritical. Figure 4 shows cumulative E for the BT, Penman, and Priestley-Taylor models duringboth measurement cycles at Lagoon A. The BT model tracked the pattern of cumulative E with

1.10

remarkable accuracy. After at least 4 days into each measurement cycle, the BT model alwayspredicted cumulative E to within 6 %. The Penman model underestimated E during the cloudyconditions occurring after DOY 265 (figure 4a) as mentioned earlier and overestimated E nearthe end of the second cycle (figure 4b). The Priestley-Taylor model consistently underestimatedE, with the most severe errors occurring during cloudy weather. Data suggest that the BT modelis the best choice for predicting E over short periods. Because equation 3 is driven by the vaporpressure difference between the surface and the air, it correctly accounts for the sometimes largedifferences between the air and lagoon temperatures. The disadvantage of the BT model is thatresults are sensitive to errors in the measurement of lagoon surface temperature, Ts. Forexample, E was recalculated using the data in figure 4 after assuming 1.0 C bias (overestimate)in the measurement of Ts. Results showed that the model overestimated cumulative E by 25 %.Given the complexity of calibrating and correcting an IRT, errors of this magnitude could occurroutinely in the field. Another possible option would be to suspend a contact thermometer justbelow the lagoon surface (e.g., 20 mm) to approximate Ts (White and Denmead, 1989).

Estimating Seepage from Soil-Lined LagoonsResults from the plastic-lined Lagoon A indicated that the floating evaporation pans and

the BT model were the best techniques for measuring E; however, both approaches wereessentially calibrated to Lagoon A through the selection of Kp and Ce. The next step was to testthe evaporation methods as components of a water balance experiment at two soil-lined lagoons.The water balance of Lagoon B is summarized in table 6 and figure 5. The two pans and the BTmodel produced almost identical estimates of E, which resulted in S values of 0.67, 0.93, and0.74 mm d-1, respectively (table 6). The Penman and Priestley-Taylor models overestimated E,resulting in negative S. Figure 5 shows cumulative ∆D and E as computed by the variousmethods. Sample calculations showed that using the pans and the BT model would haveproduced similar estimates of S after 4 days into the measurement period. Some disparitiesoccurred earlier in the measurement cycle, demonstrating how wind drag, sensor resolution, andmeasurement errors can bias results if the measurement period is too short. However, Ham andDeSutter (1999) did show that a reasonable approximation of S could be made in a single winternight under ideal weather conditions.

At the cattle feedlot (Lagoon C), Pan 1 and the BT model results were in good agreement,resulting in calculated S values of about 0.2 mm d-1 (table 6, figure 6). However, E estimatedfrom Pan 2 was larger, resulting in an S of zero. Mechanical problems with the float-recorder onDOY 326 may have affected Pan 2. Also, weather at Lagoon C was characterized by clear skiesand low wind speeds, which were the same conditions that caused low Kp values at Lagoon A.Thus, Kp may have been closer to 0.73 during the test, rather that 0.81. Nevertheless, S was verysmall, and the two pans and the BT model produced results that agreed to within 0.2 mm d-1.The Penman model overestimated E, resulting in a negative S value of -0.52 mm d-1. ThePriestley-Taylor model produced the lowest E estimate, which resulted in a S value of 0.61 mmd−1 (figure 5b, table 6).

At all lagoons, the float-based water-level recorders performed extremely well andwithout failure. In many cases, measuring ∆D alone can indicate if a lagoon is performingwithin specification. For example, ∆D at Lagoon B, which was near capacity, was 5.4 mm d-1,which was less than the state-mandated guideline for S (i.e., 6.4 mm d-1). The rate change indepth at Lagoon C was only 2 mm d-1. Thus, much can be learned about the performance oflagoons by simply measuring ∆D during periods of low evaporative demand.

1.11

1.12

CONCLUSIONSFloating evaporation pans are a reliable method for estimating E from animal waste

lagoons provided the appropriate value for Kp can be identified. In this study, a Kp of 0.81produced good results in most cases. However, Kp was affected by environmental conditionsand ranged between 0.69 and 0.93. Floating pans have the advantage of being adaptable tolagoons of different sizes and shapes and require no assumptions about aerodynamic conditions(e.g., Ce) and energy flux (e.g., G = 0). This could be important when the lagoon surface isseveral meters below the surface of the surrounding land. Floating pans have the disadvantage ofbeing adversely affected by waves. At lagoons used by Ham and DeSutter (1999) and at LagoonB in this study, the pans were flooded by waves when the average wind speed was greater than10 m s-1 and there was more than 75 m of up-wind fetch available for waves to develop. Whenthis occurred, the pans had to be pumped down to normal levels and the water balance restarted.Pans also tend to trap dust and small debris that can coat the water surface and alter evaporation.

The BT model (equation 3) in combination with short-time interval environmental datawas an excellent method for modeling E from lagoons. This approach performed well in all threelagoons using a constant Ce of 2.81x10

-3. However, Ce can be affected by lagoon geometry,atmospheric stability, and other factors, so it cannot be assumed constant at all locations. On theother hand, because the BT model uses a measurement of Ts to directly measure the vaporpressure difference between the surface and the atmosphere, it properly accounts for thesometimes large temperature differences between the lagoon and the air. This proved to be itscritical advantage over the other models tested. Unfortunately, infrared thermometry is notroutine, and small errors in Ts can cause large errors in cumulative E. Also, floating scumoccasionally develops on the lagoon surface and adversely affects the measurement of Ts, .

The Penman model tended to overestimate E in most cases (e.g., Lagoon B), butunderestimated E on some occasions. The Priestley-Taylor model almost always underestimatedE. The performance of both models was affected by the changes in heat storage within the liquidwaste. As used here, the models assumed that G was zero over a multi-day measurement period.However, results showed that the lagoon liquid could act as a strong sink or source for surfaceenergy. An alternative would be to measure G directly and incorporate these data into the modelto more accurately quantify available energy (Rn+G). In general, the Penman or Priestley-Taylor models, as used here, allowed calculation of E and S to within ± 2.5 mm d-1.

In summary, S from lagoons can be estimated from measurements of ∆D and E over 6- to11-day periods. The reliability of this approach depends on both the accuracy and magnitude ofthe E measurement. Given that S from many lagoons will often be near 1 mm d-1 (Ham andDeSutter, 1999), performing a water balance test when E is large (e.g., 10 mm d-1) is undesirablebecause a 10 % error in E could cause a 100 % error in S. In this study, where E was always lessthan 6 mm d-1, the floating evaporation pans and the BT model both measured E to within about0.5 mm d-1, but were often accurate to within 0.2 mm d-1. Data suggest that a water balanceexperiment could be used to determine if S from a lagoon was less than 0.79 mm d-1 (1/32 in. d-1

) under ideal weather conditions and could easily discern if S was less than 1.6 and 3.2 mm d-1

(1/16 or 1/8 in. d-1 , respectively).

1.13

ACKNOWLEDGEMENTSResearch was supported in part by the Kansas Center for Agricultural Resources and the

Environment, the Kansas Department of Health and the Environment, and the Kansas WaterOffice. Technical support was provided by T.M. DeSutter and F.W. Caldwell.

1.14

REFERENCESBarrington, S. F. and C. A. Madramootoo. 1989. Investigating seal formation from manure

infiltration into soils. Transactions of the ASAE 32:851-856.Bill, R.G., A.F. Cook, L.H. Allan, and J.F. Bartholic. 1980. Predicting fluxes of latent and

sensible heat of lakes from surface water temperature. J. Geophys. Res. 85:507-512.Brutsaert, W. 1982. Evaporation Into the Atmosphere. D. Reidel Publishing, Boston.Clark, R. N. 1975. Seepage beneath feedyard runoff catchments. In Proceedings of the Third

International Symposium on Livestock Wastes, 289-295. ASAE, St. Joseph, MI.Culley, J. L. B. and P. A. Phillips. 1989. Retention and loss of nitrogen and solids from unlined

earthen manure storages. Transactions of the ASAE 32:677-683.Daniel, D. E. 1984. Predicting hydraulic conductivity of clay liners. J. Geotech. Eng. 110:285-

300.Davis, S., W. Fairbank, and H. Weisheit. 1973. Dairy waste ponds effectively self-sealing.

Transactions of the ASAE 16:69-71.DeBruin, H.A.R. 1978. A simple model for shallow lake evaporation. J. Appl. Meteorol.

17:1132-1134.Ham, J.M. and T.M. DeSutter. 1999. Seepage losses and nitrogen export from swine waste

lagoons: A water balance study. J. Environ. Qual. (in press)Ham, J.M., L. Reddi, C.W. Rice, and J.P. Murphy. 1998. Evaluation of lagoons for the

containment of animal waste. Kansas Center for Agric. Resources and the Environment.Kansas State University, Manhattan, KS.

Ham, J.M. and R.S. Senock. 1994. On the measurement of soil surface temperature. Soil Sci.Soc. Am. J. 56:370-377.

Hart, S.A. and M. E. Turner. 1965. Lagoons for livestock manure. J. Water Pollut. Cont. Fed.37:1578-1596.

Hills, D. J. 1976. Infiltration characteristics from anaerobic lagoons. J. Water Pollut. Cont. Fed.48:695-709.

Huffman, R. L. and P. W. Westerman. 1995. Estimated seepage losses from established swinewaste lagoons in the lower coastal plains of North Carolina. Transactions of the ASAE

38:449-453.Humenik, R.L., M.R. Overcash, J.C. Barker, and P.W. Westerman. 1980. Lagoons: State of the

Art. In Livestock Waste: A Renewable Resource, Proceedings of the 4th InternationalSymposium on Livestock Wastes. 211-216. ASAE, St Joseph, MI.

Itier, B., Y. Brunet, K.J. McAneney, and J.P. Lagouarde. 1994. Downwind evolution of scalarfluxes and surface resistance under conditions of local advection. Part I. Reappraisal ofboundary conditions. Agric. Forest Meteorol. 71:211-225.

Kosco, J.A. and W. Hall. 1999. Joint strategy targets farm waste. Resource, ASAE, St Joseph,MI . 6:11-12.

Lakshman, G. 1972. An aerodynamic formula to compute evaporation from open water surfaces.J. Hydrology. 15:209-225.

McCurdy, M. and K. McSweeney. 1993. The origin and identification of macropores in anearthen-lined dairy manure storage basin. J. Environ. Qual. 22:148-154.

Miller, M. H., J. B. Robinson, and D. W. Gallagher. 1976. Accumulation of nutrients in soilbeneath hog manure lagoons. J. Environ. Qual. 5:279-282.

Murray, F.W. 1967. On the computation of saturation vapor pressure. J. Appl. Meteorol. 6:203-204.

1.15

Nolan, B. T., B. C. Ruddy, K. J. Hitt, and D. R. Helsel. 1997. Risk of nitrate in groundwaters ofthe United States-A national perspective. Environ. Sci. Technol. 31:2229-2236.

Penman, H.L. 1948. Evaporation from open water, bare soil, and grass. Proc. Roy. Soc. LondonA193:120-146.

Priestley, C.H.B. and R.J. Taylor. 1972. On the assessment of surface heat flux and evaporationusing large-scale parameters. Monthly Weather Rev. 100:81-92.

Quinn, F. 1979. An improved aerodynamic evaporation technique for large lakes withapplication to the international field year for the great lakes. Water Resour. Res. 15:935-940.

Robinson, F.E. 1973. Changes in seepage rate from an unlined cattle waste digestion pond.Transactions of the ASAE 16:95-96.

Sadler, E.J. and C.H.M. Van Bavel. 1982. A simple method to calibrate an infrared thermometer.Agron. J. 74:1096-1098.

Stewart, R.B., and W.R. Rouse. 1976. A simple method for determining the evaporation fromshallow lakes and ponds. Water Resource. Res. 12:623-628.

Webster I.T., and B.S. Sherman. 1995. Evaporation from fetch-limited water bodies. Irrig. Sci.16:53-64.

Westerman, P. W., R. L. Huffman, and J. S. Feng. 1995. Swine-lagoon seepage in sandy soil.Transactions of the ASAE 38:1749-1760.

White, I., and Denmead, O.T. 1989. Point and whole basin estimates of seepage and evaporationlosses from a saline groundwater-disposal basin. In Comparisons in AustralHydrology:Hydrology and Water Resources Symposium. 361-366. University ofCanterbury, Christchurch, New Zealand.

1.16

Appendix 1The following equations are required to calculate environmentally dependent variables

appearing in the evaporation models (equations 3-7).Saturation vapor pressure, e*, in kPa can be approximated at temperature, T, in C, using

the equation of Murray (1967)

+=

TT

Te3.237

269.17exp61078.0)(* (A1.1)

Actual vapor pressure of the air, ea, in kPa, is the product of the e* at air temperature and asimultaneous, collocated measurement of relative humidity. The slope of the saturation vaporpressure curve, ∆, in kPa K-1, can be calculated as the partial derivative of equation A1.1

+−

+=∆

TT

TTe

3.2371

3.237

269.17)(* (A1.2)

noting that e*(T) is the result from equation A1.1. Atmospheric pressure, P, in kPa, can beapproximated from altitude, A, in m, and air temperature, Ta, in C, as

+

−=

−

15.2731042.3

exp3.1012

aTAx

P (A1.3)

The latent heat of vaporization, L, in J kg-1, can be approximated as)15.273(10359.2105005.2 26 +−= aTxxL (A1.4)

Heat capacity of air, cp, in J kg K-1, can be expressed as

+= 1

522.07.1004

P

ec ap (A1.5)

Density of moist air, ρ, in kg m-3, is

−

+=

P

e

TRP a

ad

378.01

)15.273(ρ (A1.6)

where Rd is the gas constant (287.04 J kg K-1). The psychrometric constant, γ, in kPa K-1, can be

approximated as

L

Pc p61.1=γ (A1.7)

1.17

Table 1. Description of the lagoons used for the study.

LagoonCharacteristic A B C

Period of study Sept.-Oct. April Nov.-Dec.

Type Swine waste Swine waste Cattle feedlot

Max. capacity, m3 110,000 110,000 96,000

Surface areaduring study, ha 2.1 2.1 1.8

Depth duringstudy, m 5.8 5.3 2.3

Liner type or thickness, m plastic* 0.46 0.46-0.6

Liner texture Silty clay + loambentonite

Liner permeability, cm s-1 4.44 x 10-8 7.54 x 10-8

Depth to water table, m 30 58 85

* 1.0-mm thick, high density polyethylene.

1.18

Table 2. Environmental conditions and cumulative evaporation during two measurement cycles

at the plastic-lined Lagoon A. Included are minimum and maximum air temperatures (Ta) and

vapor pressure deficit (ea*-ea), average water temperature at 0.1 m (Tw), average wind speed (U),

and daily global irradiance (Rs). Also provided is the cumulative change in depth (i.e.,

evaporation, ΣE) over each cycle.

DOY Tair ea*-ea Tw U Rs ΣE

Min Max Min Max(C) (kPa) (C) (m s-1) (MJ m-2) (mm)

258 13.6 25.2 0.0 1.7 22.6 2.3 17.5 4.7

259 13.1 27.9 0.1 2.2 24.6 1.4 20.3 8.9

260 13.7 29.4 0.1 2.7 23.8 2.1 21.0 13.2

261 16.2 31.3 0.2 3.3 23.3 3.8 21.7 18.9

262 16.4 34.9 0.3 4.7 23.4 3.8 21.9 26.5

263 14.2 27.2 0.1 1.9 22.4 2.9 21.8 31.0

264 9.5 20.1 0.0 0.6 21.6 4.3 12.5 36.7

265 8.6 13.2 0.0 0.3 9.4 3.5 5.0 44.3

266 11.1 28.7 0.0 2.1 20.2 4.8 15.8 48.5

278 5.4 17.0 0.1 1.3 17.1 2.8 11.3 5.30

279 3.5 20.0 0.1 1.8 16.6 2.9 19.3 10.6

280 4.5 22.6 0.1 1.9 17.6 2.3 18.4 14.3

281 8.2 26.3 0.2 2.6 17.6 5.0 18.0 21.0

282 10.7 27.3 0.4 2.7 16.9 3.6 17.8 25.5

283 9.9 28.8 0.2 3.0 16.8 5.0 17.6 31.8

284 9.7 22.6 0.1 2.1 16.1 3.6 18.1 38.5

285 3.6 22.2 0.1 1.6 16.0 5.0 17.1 42.4

286 11.4 27.1 0.1 4.2 18.2 3.1 16.9 44.7

287 10.1 32.8 0.0 2.0 17.8 4.9 15.7 48.0

288 15.2 28.2 0.2 2.5 17.0 7.6 15.0 54.5

1.19

Table 3. Comparison of total evaporation (E) from the plastic-lined Lagoon A to evaporation

from two floating evaporation pans (Epan). Also included are the pan coefficeints, Kp.

Pan 1 Pan 2Period E Epan Kp Epan Kp(DOY) (mm) (mm) (mm)

258-260 13.2 17.6 0.75 19.2 0.69

261-263 17.8 22.8 0.78 22.3 0.80

264-266 17.5 21.9 0.80 21.7 0.81

278-280 14.3 19.0 0.75 19.5 0.73

281-283 17.5 19.5 0.90 19.2 0.91

286-288 12.1 13.8 0.88 12.9 0.94

Avg. 15.4 19.1 0.81 19.1 0.81

1.20

Table 4. Comparison of actual evaporation (E) from the plastic-lined Lagoon A to that predicted

using four different models. Data are shown as average daily evaporation in mm d-1 for five,

3−day periods. The numbers in parenthesis represent model error (Emodeled -Eactual) for each

block-model combination, also in mm d-1.

Evaporation Model*

Period E EBT Epen EPT EDB(DOY) (mm d-1)

258-260 4.4 3.8 (-0.6) 4.5 (0.1) 4.6 (0.2) 3.8 (-0.6)

261-263 5.9 6.3 (0.6) 6.7 (0.8) 5.5 (-0.4) 8.3 (2.6)

264-266 5.8 6.1 (0.3) 2.4 (-3.6) 1.8 (-4.0) 3.7 (-2.1)

283-285 5.6 5.4 (-0.2) 5.6 (0.0) 3.8 (-1.8) 11.5 (5.9)

286-288 4.0 4.2 (0.2) 6.1 (2.1) 3.3 (-0.7) 12.4 (8.4)

Avg. 5.1 5.2 5.1 3.8 7.9

* BT, Bulk Transfer Model; pen, Penman Model; PT, Priestley-Taylor Model; DB, DeBruin Model

1.21

Table 5. Average daily (24-h) energy balances of Lagoon A.

Period Rn LE H G

(DOY) (W m-2)

258-260 146.6 -108.6 -9.2 28.8

261-263 168.1 -180.2 8.1 -4.0

264-266 61.3 -180.0 -55.1 173.7

283-285 126.4 -154.0 39.6 -12.0

286-288 109.3 -119.2 77.2 -67.3

1.22

Table 6. Water balances of a soil-lined Lagoons B and C. Shown are evaporation and the

calculated seepage rate when the floating evaporation pans and three different models were used

to calculate evaporation. The measurement periods for lagoons B and C where 6 and 11 days,

respectively.

Location ∆D Evaporation Method E S

(mm) (mm) (mm d-1) (mm) (mm d-1)

Lagoon B 24.5 Pan 1 20.5 3.42 4.0 0.67

(swine) Pan 2 19.0 3.16 5.5 0.92

Bulk Transfer 20.1 3.35 4.4 0.74

Penman 32.1 5.35 -7.6 -1.27

Priestley-Taylor 27.6 4.60 -3.1 -0.52

Lagoon C 22.8 Pan 1 21.0 1.91 1.8 0.16

(cattle) Pan 2 22.8 2.07 0.0 0.0

Bulk Transfer 20.5 1.86 2.3 0.21

Penman 28.6 2.58 -5.8 -0.52

Priestley-Taylor 16.1 1.46 6.7 0.61

1.23

List of Figures

Figure 1. Photograph showing one of the rafts used to measure pan evaporation and

meteorological conditions at the lagoons.

Figure 2. Cumulative depth change (i.e., evaporation) in the plastic-lined Lagoon A and two

floating evaporation pans between (a) DOY 258-267 and (b) DOY 278-289. Depth changes

recorded in the pans were multiplied by a pan coefficient, Kp, of 0.81 to approximate actual

evaporation from the lagoon (table 3).

Figure 3. Temperature regime at the plastic-lined Lagoon A between DOY 258-267. Shown are

(a) air temperatures at 1.0 m and waste temperatures at the surface and 0.1 m, and (b) the

difference in waste surface temperatures inside and outside the evaporation pans (Tlagoon-Tpan).

Figure 4. Comparison of cumulative evaporation at the plastic-lined Lagoon A to that calculated

using three different models (see equations 3, 4,and 6). Data are shown for two experimental

periods: (a) DOY 258-267; (b) DOY 283-289.

Figure 5. Cumulative change in depth and evaporation at soil-lined Lagoon B (swine waste)

between DOY 108 and 114, 1998. Evaporation was estimated with (a) two floating evaporation

pans and (b) meteorological models. The overall water balance is given in table 6.

Figure 6. Cumulative change in depth and evaporation at soil-lined Lagoon C (cattle feedlot)

between DOY 325 and 336, 1998. Evaporation was estimated with (a) two floating evaporation

pans and (b) meteorological models. The overall water balance is given in table 6.

1.24

Figure 1.

1.25

258 259 260 261 262 263 264 265 266 267 268

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1.26

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1.27

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1.29

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Figure 6.

Chapter 2

Field Evaluation of Animal-Waste Lagoons:Seepage Rates and Subsurface Nitrogen Transport

J.M. Ham and T.M. DeSutter

Department of Agronomy, Kansas State University, Manhattan, KS 66506

Abstract: Earthen lagoons are an integral part of the waste management plan at many concentrated

animal-feeding operations. Lagoon waste contains high concentrations of N, P, salts, and other

nutrients that, in many cases, are applied to farmland as liquid fertilizer. However, while the waste is

being stored and treated in the lagoon, subsurface seepage losses may affect soil and water quality near

the facility. Water balance methods were used to study seepage losses and nitrogen export from soil-

lined lagoons at nine different swine and cattle feedlots in Kansas. Lagoons ranged in size from 0.2 to

2.5 ha and had waste depths between 1.2 and 5.8 m. Compacted-soil liners were between 0.30 to 0.46

m thick and built with native soil or, in some cases, a soil-bentonite mixture. Whole lagoon seepage

was measured using the methods of Ham (1999) and Ham and DeSutter (1999). Seepage rates from the

lagoons ranged from 0.2 to 2.4 mm/d, with an overall average of rate of 1.2 mm/d . Analysis of lagoon

effluent showed that Ammonium-nitrogen (NH4+-N) accounted for over 99 % of the soluble nitrogen

and averaged 673 mg/L at swine waste lagoons and 98 mg/L at the cattle sites. The NH4+-N typically

ranged from 550 to 900 mg/L at swine sites and from 20 to 200 mg/L at cattle feedlots. Nitrate

(NO3--N) concentrations were less than 3 mg/L at all locations. Analysis of soil cores collected

beneath an 11-year-old cattle-waste lagoon showed that a large fraction of the NH4+-N in the leachate

remained in a shallow (e.g., 5 m) adsorption zone directly beneath the lagoon. When lagoons are

closed, emptied, and dried; NH4+-N could convert to NO3

--N and more readily move towards the

ground water. More information is needed regarding the fate of NH4+-N deposited in soil (vadose

zone) beneath lagoons. Data suggest that risk of ground water contamination will be location and

species dependent.

2.2

IntroductionAnaerobic lagoons are an integral part of the waste management system at many concentrated

animal operations (CAOs). Lagoon waste contains high concentrations of nitrogen, phosphorus, salts,and other nutrients that are usually applied to farmland as liquid fertilizer. However, while the waste isbeing stored and treated in the lagoon, subsurface seepage losses may affect soil and water quality nearthe facility. Of particular concern is the movement of nitrate-N into local drinking water supplies.Kansas State University is conducting research to determine the relationship between the lagoon useand ground water quality. This report provides an update on the field component of the research effort.Emphasis is placed on lagoon effluent chemistry, whole-lagoon seepage rates, and the fate andtransport of material in the subsoil (vadose zone) directly beneath the lagoons. Results representprogress to date and are not final conclusions. A more thorough synthesis of these concepts will bepresented in later reports.

Evaluating the potential impact of animal waste lagoons on ground water quality requires theconsideration of three focus areas: a) toxicity – what are the constituents in the lagoon waste that posea threat to water quality and public health? (b) input loading – at what rate does waste seep from alagoon under field conditions? and (c) aquifer vulnerability – how do soil properties, geology, andwater table depth affect the risk of waste movement from the lagoon to the ground water? Theseconcepts are outlined in Table 1 and provide a framework for the remainder of the report.

Lagoon Effluent Chemistry and ToxicityLagoon effluent was analyzed from five swine-waste lagoons and four cattle-feedlot runoff

lagoons in Kansas (DeSutter et al., 1999; Appendix A). Samples were sometimes collected severaltimes throughout the year to examine seasonal trends. Analysis included twenty-five chemical andphysical characteristics. Ammonium-nitrogen (NH4

+-N) accounted for over 99 % of the solublenitrogen and averaged 673 mg/L at swine-waste lagoons and 98 mg/L at the cattle sites. Totalphosphorous averaged 45 mg/L across all samples and was similar at the cattle and swine lagoons. Onaverage, sodium was 148 mg/L at the cattle feedlots and 270 mg/L at the swine sites. Chloride was275 and 569 mg/L at the swine and cattle sites, respectively. In most cases, strong seasonal patterns inwaste chemistry were not evident. At some swine sites, NH4

+-N in spring tended to be about 200 mg/Lhigher than that observed in late fall. Results show that waste chemistry was species dependent, withnitrogen concentrations at swine sites being about six times higher than those at cattle feedlots.Conversely, chloride tended to be higher in cattle-feedlot runoff lagoons.

The chemistry and toxicity of lagoon effluent are species dependent. The mechanisms behinddifferences in chemistry are primarily caused by how the waste is managed rather than by inherentdifferences in the biology of the animals. Because “pull-plug” swine lagoon systems must accept allthe waste produced in the barn, concentrations in the waste entering the lagoon are very high. Forexample, NH4

+-N in waste entering a swine lagoon is often greater than 3,500 mg/L (Ni et al., 1998).Ammonia-N volatilization from the lagoon surface and some dilution by precipitation reduceslong-term concentrations in the lagoon to the 500 to 900 mg/L range. Conversely, at a cattle feedlot,most wastewater entering a lagoon is runoff from precipitation that falls on the pens. In this case, mostof the NH4

+-N stays on the pen surface, trapped in manure and the soil surface. This process keepsnitrogen in a cattle feedlot lagoon more dilute. However, ions that easily leach through the soil, suchas chloride, will accumulate in the runoff as it flows downhill over a long swath of open pens.Therefore, chloride concentrations are often much higher in cattle lagoons than at swine sites (Table2).

There are also site-to-site differences in chemistry among lagoons used for the same species.DeSutter et al. (1999) found that NH4

+-N ranged from 550 to 900 mg/L at swine sites and from 20 to200 mg/L at cattle feedlots. The highest concentration, 2000 mg/L, was observed at swine site in thefirst stage basin of a two-stage lagoon system (concentration was much lower in the second stagelagoon). Conversely, the NH4

+-N concentrations at one of the cattle feedlots never exceeded 70 mg/L

2.3

and was often less than 30 mg/L. Data show that site-to-site differences in waste chemistry will affectthe toxicity and the potential for input loading (Table 1).

Whole-lagoon Seepage Rates and Subsurface Nitrogen ExportRegulations in Kansas stipulate that soil-lined lagoons used for animal waste should be

constructed so that seepage is less than 6.4 or 3.2 mm/d (1/4 or 1/8 inch per day), depending on whereand when the facility was built. Whole-lagoon seepage rates were measured from seven swine-wastelagoons and two cattle-feedlot runoff collection lagoons. Measurements were made using the methodsof Ham (1999) and Ham and DeSutter (1999). Descriptions of the lagoons and details of the waterbalance calculations are provided in Appendix 2A (Water Balance Worksheets). The earthen lagoonsranged in size from 0.2 to 2.5 ha and had waste depths between 1.2 and 5.8 m. Five of the lagoonshad waste depths in excess of 4.9 m. Most lagoons had compacted soil liners between 0.3 and 0.5 mthick. The average seepage rate from the lagoons was 1.2 mm/day (Table 3). Among lagoons tested,seepage ranged from 0.2 to about 2.4 mm/day. At some locations, seepage results were combined withdata on lagoon geometry and construction to estimate the in-situ permeability of the liner. In lagoonsbuilt with silt loam liners (no bentonite) having initial permeability’s greater than 3.5x10-7 cm/s,seepage rates on a whole-lagoon basis were about two to five times less than those predicted from soilcore data collected prior to the addition of waste (Table 4). Results imply that permeability of the linerwas reduced by organic sludge on the bottom of the lagoons. Field measurements showed that theorganic sludge layer was 0.38 m thick on the bottom in a four-year-old, swine-waste lagoon. Sludgedepth was approximately 0.15 m thick on the side embankments, which where constructed with a 4:1slope.

Measurements of whole-lagoon seepage where combined with waste chemistry data to estimatethe rate of nitrogen movement into the surrounding soil (Table 5). Ammonium-N losses ranged from0.2 to 0.5 kg/m2 ·yr (130 to 4453 lbs./acre·yr). Nitrogen export was much lower at the cattle feedlotscompared to swine sites because the NH4

+-N concentrations in the waste were more dilute. Althoughonly two cattle feedlots are represented in the current study, one would expect nitrogen export(nitrogen input loading, Table 1) to be five to ten times lower at cattle feedlots compared to swinesites.

Subsurface Nitrogen Losses Into Soil Under LagoonsThe movement of effluent-nitrogen into the soil surrounding the lagoon is not only dependent

on the seepage rate and the nitrogen concentration, but also is affected by the chemical and physicalproperties of the soil. Ammonium-N (NH4

+ ion) has a positive charge, while clay particles in soil arenegatively charged. Objects with opposite charge attract; thus, NH4

+ ions that leak from a lagoon areoften adsorbed onto the surface of clay particles in the soil profile. Conversely, negatively chargedions, such as chloride (Cl-), are not attracted to soil particles and tend to move through the soil profileunimpeded. The ability of a soil to adsorb positively charged ions is described by the Cation ExchangeCapacity (CEC). Soils with high clay contents have CECs near 30 cmol/kg and very sandy soils haveCECs near 5 cmol/kg. If two lagoons were seeping at the same rate, but one was built above a sandysoil and the other above a clayey soil, one might expect the NH4

+ to travel six times farther from thelagoon built at the sandy site. This is not exactly what happens in the field because other factors affectsolute transport, but it does demonstrate the importance of soil CEC.

To gain a better understanding of subsurface nitrogen dynamics, soil cores were collected fromthe bottom of an 11-year-old cattle-feedlot lagoon in southwestern Kansas. The lagoon had been driedand the organic sludge removed prior to sampling. A direct-push soil coring unit was used to samplefour locations to a depth of 5 m. Figure 1 shows the average NH4

+-N and chloride concentrationprofiles. Ammonium-N concentrations were near 400 ppm near the original bottom of the lagoon andthen decreased rapidly to about 30 ppm at 5 m. The shape of the concentration curve demonstrateshow NH4

+-N was adsorbed in the soil profile. There were essentially no nitrates in any of the soil

2.4

samples. Thus, almost all the nitrogen that had been lost from the lagoon was still in the NH4+-N form

and about 90% of that nitrogen was still within 3 m of the soil liner. However, in one area of thelagoon the subsoil was very sandy, and NH4

+ concentrations were 66 ppm at 5 m. This shows how alower CEC allowed nitrogen to move to lower depths. Chloride concentrations did not decrease withdepth (Fig. 1) because these ions have a negative charge and were not adsorbed by clay particles. Insummary, preliminary data suggest that nitrogen losses through a lagoon liner will, in many cases, bedeposited as NH4

+-N in a rather shallow soil zone near the periphery of the lagoon liner. Ammonium-Ncould potentially move directly into the ground water at sites built above shallow aquifers in sandysoils. The amount of nitrogen and size of the deposit will be dependent on the seepage rate,concentrations of nitrogen in the waste, CEC of the underlying soil, local geology, and lagoon age.

Aquifer VulnerabilityAquifer vulnerability is one of the most critical factors affecting the risk of ground water

contamination. In many cases, depth to ground water is the most important geologic feature correlatedwith vulnerability. Although data are limited, previous research shows that ground watercontamination from lagoons usually occurs at locations with high rainfall and water tables less than 7.6m deep (Table 6). Kansas is a state that has tremendous geographic variation in hydrology, soils, andagricultural practices. Thus, we would expect large regional variation in aquifer vulnerability. Todemonstrate this point, Table 7 compares conditions in Washington Co. (northeast) and Grant Co.(southwest) – regions with intense livestock production. Grant Co. has low precipitation, highevaporation, and a aquifer median aquifer depth over 70 m. Thus, there is a thick vadose zone betweenthe lagoons and the water table. Under these conditions, soil beneath lagoons becomes unsaturated justa few meters from the bottom of the basin. Unsaturated conditions are beneficial because they greatlyretard the movement of water, nutrients, and bacteria that may have seeped from the lagoon (Schafer etal., 1998). In contrast, Washington Co. has almost twice the rainfall of Grant Co. and median groundwater depths near 12 m. Clearly, the aquifer is more vulnerable in the northeastern portion of the state.This does not imply that lagoons in northeastern counties are polluting ground water. The comparisonwas made to simply show that large differences in vulnerability exist between regions and that anychanges in regulations, permitting, and prescribed management practices should consider thesedifferences.

Lagoon ClosureField measurements have shown that seepage losses from many lagoons occur very slowly.

However, over 20 to 40 years of operation, even a low seepage rate can deposit a large mass ofnitrogen beneath a lagoon. For example, Ham and Desutter (1999) showed that the total nitrogendeposited in soil beneath a 2.2-ha (5-acre) swine lagoon could potentially exceed 110,000 kg (250,000lbs.) over a 20 year period. When a lagoon is eventually emptied and closed, the nutrient-laden zoneof soil under the lagoon will tend to become dry and aerobic , especially in western Kansas wherepotential evaporation is much greater than precipitation. Under dry soil conditions the NH4

+-N mayconvert to NO3

--N, which is very mobile in the soil (Figure 2). Over time, seasonal precipitation andintermittent water movement (drainage) through the soil profile could transport this newly formedNO3

--N toward the ground water. However, a fraction of the nitrogen may be converted to harmlessN2 gas and released into the atmosphere (denitrification). It is difficult to predict the ultimate fate ofnitrogen in the NH4-laden soil surrounding lagoons. It may be feasible to phytoremediate the soilprofile with plants. Salt tolerant crops like barley or perhaps constructed wetlands might be capable ofabsorbing large portions of the nitrogen and also stimulate denitrification. Furthermore, it is not clearif the nutrient-laden soil under a lagoon poses a significant risk to the groundwater, especially whenthe depth to ground water is large (e.g., 100 ft). Much of the nitrogen may be lost to the atmosphereeven without a phytoremediation plan. In summary, older lagoons that are closed and abandoned willinitially have a deposit of NH4

+nitrogen in the soil under the facility. Additional research is needed to

2.5

determine if this nitrogen will affect ground water quality, and how the risk of contamination isaffected by soil and geologic conditions. Best management practices for lagoon closure should beexplored.

2.6

ReferencesCiravolo, T.G., D.C. Martens, D.L. Hallock, Jr. E.R. Collins, E.T. Kornegay, and H.R. Thomas. 1979.

Pollutant movement to shallow ground water tables from anaerobic swine waste lagoons. J.Environ. Qual. 8:126-130.

DeSutter T.M., J.M. Ham, and T. Trooien. 1999. Survey of waste chemistry in anaerobic lagoons atswine units and cattle feedlots. Technical Report. Department of Agronomy, Kansas StateUniversity, Manhattan, KS 66506. (Animal waste lagoon water quality study, Appendix A)

Ham, J.M. 1999. Measuring evaporation and seepage losses from lagoons used to contain animalwaste. Trans. of the ASAE (in press)

Ham, J.M. 1999. Seepage losses and nitrogen export from animal waste lagoons: A water balancestudy. J. Environ. Qual. (in press)

Ham, J.M., L. Reddi, C.W. Rice and J.P. Murphy. 1998. Evaluation of lagoons for the containment ofanimal waste. A report submitted to the Kansas Department of Health and the Environment.Kansas Center for Agric. Resources and the Environment. Kansas State University, Manhattan, KS66506.

Krapac, I.L., W.S. Dey, C.A. Smyth, and W.R. Roy. Impacts of bacteria, metals, and nutrients ongroundwater at two hog confinement facilities. Proceedings from Animal Feeding Operations andGround Water: Issues, Impacts, and Solutions – A Conference for the future, Presented by NationalGround Water Assoc., Nov. 4-5, 1998, St. Louis, Missouri. pp. 29-50.

Ni, J., Heber, A.J., Lim, T.T., Duggirala, R., Haymore, B.L., Diehl, C.A., and A.L. Sutton. 1998.Ammonia emissions from a large mechanically ventilated swine building during warm weather.ASAE paper 984051. ASAE International Meeting, Orlando, Florida. ASAE, St. Joseph, MI

Quade, D.J., R.D. Libra, and L.S. Seigley. 1996. Ground water monitoring at an earthen manurestorage structure. Iowa Geological Survey, Bureau Guidebook Series No. 18.

Schafer, A., Ustohal, P., Harms, H., Stauffer, F., Dracos, T., and A. Zehnder. 1998. Transport ofbacteria in unsaturated porous media. J. Contaminant Hydrology. 33:149-169.

Sewell, J.I. 1978. Dairy lagoon effects on groundwater quality. Trans. of the ASAE. 21:948-952.Westerman, P.W., R.L. Huffman, and J.S. Feng. 1995. Swine lagoon seepage in a sandy soil. Trans. of

the ASAE 38:1749-1760.Wise, C.F. 1998. Regulatory control of groundwater impacts at animal feeding operations. Proceedings

from Animal Feeding Operations and Ground Water: Issues, Impacts, and Solutions – AConference for the future, Presented by National Ground Water Assoc., Nov. 4-5, 1998, St. Louis,Missouri. pp. 14-23.

2.7

Table 1. Factors that must be considered when assessing the potential impact of animal waste lagoonson local ground water quality. The impact of each factor is often dependent on livestock species,characteristics and design of the waste handling system, and location.

Toxicity: Constituents in an anaerobic waste lagoon that could potentially affect human health by

contaminating ground water.

a. Inorganic Constituents (nitrate-N, ammonium-N, Chloride, Phosphorous, metals)b. Bacteria (Fecal Coliform, Fecal Strep.)c. Enteric viruses ?d. Pharmaceuticals ?

Input Loading:The rate at which waste and potential contaminates seep from the lagoon into the soil profile surrounding the earthen basin.

a. Seepage Rate (properties of soil liner, depth of waste, sludge accumulation)b. Concentration of constituents in the waste (species, management)

Aquifer Vulnerability:Properties of the zone between the lagoon and the water table that determine if seepage losses willreach the ground water.

a. Depth to Ground waterb. Soil Properties (rate of contaminant transport, biochemical transformations)c. Geology (geologic layers that inhibit or promote contaminant movement)

2.8

Table 2. Selected chemical characteristics of waste in anaerobic lagoons. Data are averages of fiveswine sites and four cattle feedlots in Kansas, U.S.A. (DeSutter et al., 1999)

Measured Lagoon Type

parameters Swine Cattle

mg L-1

Nitrate-Nitrogen 1 0.5

Ammonium-Nitrogen 673 98

Total N 792 184

Organic N 119 86

Total P 43 48

Sodium 270 148

Chloride 276 569

pH 8.1 7.7

BOD* 1726 370

* BOD, Biological Oxygen Demand

2.9

Table 3. Whole-lagoon seepage rates from nine animal waste lagoons in Kansas. Data used tocalculate the seepage rates are presented in Appendix 2A.

Waste Lagoon Seepage Max. SeepageLagoon Species Depth Area Rate Rate*

m (ft.) ha (acre) mm/d (in./d) mm/d (in./d)

1 swine 5.5 (18) 0.7 (1.7) 1.4 (0.06) 1.5 (0.06)

2 swine 5.8 (19) 2.3 (5.7) 2.0 (0.08) 2.2 (0.09)

3 swine 5.3 (17) 2.2 (5.5) 0.8 (0.03) 0.9 (0.03)

4 swine 5.4 (18) 2.2 (5.5) 0.9 (0.03) 1.0 (0.04)

5 swine 4.9 (16) 2.9 (7.2) 1.5 (0.06) 1.6 (0.06)

6 swine 2.1 (7) 0.5 (1.2) 1.3 (0.05) 3.0 (0.11)

7 swine 4.4 (14) 1.5 (3.7) 0.6 (0.02) 1.9 (0.07)

8 cattle 2.3 (8) 1.8 (4.5) 0.2 (0.01) 0.5 (0.02)

9 cattle† 1.2 (4) 2.8 (7.0) 2.4 (0.09) 4.3 (0.17)

Mean 4.1 (13) 1.9 (4.6) 1.2 (0.05) 1.9 (0.07)

* estimate of whole lagoon seepage at maximum capacity (i.e., maximum waste depth).

† measurements made using different techniques and equipment than employed at lagoons 1 through 9.

2.10

Table 4. Properties of the compacted soil liner at six of the lagoons in the study. Also shown is acomparison of the mesured seepage rate with that predicted from soil cores collected prior to theaddition of waste.

Predicted MeasuredSoil Texture CEC* Ks* Seepage Seepage