United States
Environmental Protection
Agency
Robert S. Kerr Environmental Research
Laboratory
Ada, OK 74820
v-xEPA
Research and Development
EPA-600/S2-80-192 Jan. 1981
Project Summary
Predicting Cattle Feedlot
Runoff and Retention Basin
Quality
J. Ronald Miner, James K. Koelliker, and Marshall J. English
As a result of potential water and
land pollution from cattle feedlots, a
technology for control of feedlot
runoff has evolved. This study de-
scribes a procedure for controlling
runoff while recovering manure-laden
water for use as fertilizer. When rain or
melting snow reduces the surface
holding capacity of a feedlot's runoff
retention basin, manure-laden water,
valuable as a cropland fertilizer, may
be lost to soil surface and/or receiving
streams near the basin. Accurate pre-
diction of the quantity of runoff enter-
ing a retention basin or pond would
permit design of a basin with a holding
capacity sufficient to contain the
runoff.
A procedure was devised which can
predict, on a daily basis, the quality
and quantity of feedlot runoff entering
a retention basin. The predictions are
based on climate, feedlot size, type of
liquid-removal equipment, frequency
of pumping and the needed level for
land or water pollution control.
A cattle feedlot in Illinois was
sampled to adjust the predictive
model which measures the following
parameters on a daily basis: chemical
oxygen demand, total Kjeldahl
nitrogen, ammonia nitrogen, total
phosphorous, total solids, fixed dis-
solved solids, total coliforms, fecal
coliforms, and fecaf streptococcus. In
order to determine quality changes
between a runoff retention basin or
other manure-laden water storage and
the receiving soil surface, a separate
study was conducted. Ammonia
nitrogen is the major constituent lost.
A technique was devised and tested
for prediction of ammonia nitrogen
loss as a function of wastewater
quality, sprinkler equipment charac-
teristics, and current weather data.
Losses ranged from zero to 40
percent.
This project summary was devel-
oped by EPA's Robert S. Kerr Envi-
ronmental Research Laboratory in
Ada, OK, to announce key findings of
the research project that is fully
documented in a separate report of the
same title (see Project Report ordering
information at back).
Introduction
Runoff from cattle feedlots was
recognized as a potential water pollu-
tant in 1962, following a series of-fish
kills in Kansas; since that time, a tech-
nology for control of feedlot runoff has
evolved, accompanied by a variety of
regulatory schemes. The strategy
proven most feasible is the collection of
stormwater runoff in a retention basin
or pond. Following a storm, the manure-
laden water is applied to cropland in a
manner to avoid runoff. This approach
recaptures plant nutrients, thereby
reducing the cost of chemical fertilizer,
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Table 1. Cattle Feedlot Runoff Retention Basin Quality Parameters to be
Predicted in the Developed Model.
Parameter
Chemical oxygen demand
Total Kjeldahl nitrogen
Ammonia nitrogen (NHs+NH4+)-N
Total phosphorus
Total volatile solids
Fixed dissolved solids
Total solids
Total coliforms
Fecal coliforms
Fecal streptococcus
Abbreviation
COD
TKN
NH3-N
Total-P
TVS
FDS
TS
TC
FC
FS
Unit
mg/l
mg/l
mg/l
mg/l
mg/l
mg/l
mg/l
No. /TOO ml
No./ 100 ml
No. /WO ml
some of which is replaced by the runoff
water. The capacity of a runoff retention
basin for a given location is a function of
climate, feedlot size, availability of
liquid-removal equipment, frequency of
pumping and the required level of pollu-
tion control. Construction of a basin
which could retain all runoff, even
during the most extreme weather condi-
tions, is unreasonably expensive and
provides only minimal additional pollu-
tion control than a less expensive
system for which well-defined
limitations exist. Feedlot pollution
control guidelines define the conditions
under which a discharge will occur in a
well-designed feedlot runoff control
system during extreme weather condi-
tions; typically, these are the 10-year,
24-hour storm and the 25-year, 24-
hour storm.
Cattfe feedlot runoff is a high-
strength organic wastewater
containing large numbers of enteric
microorganisms. Qualityof runoff water
is highly variable, depending upon such
parameters as rate of rainfall, tempera-
ture, and feedlot surface conditions.
Quality is further modified by storage in
the runoff control system; organic
matter is stabilized, solids settle,
ammonia volatilizes, and enteric bac-
teria die off. All of these changes influ-
ence the quality of basin contents;
conversely, the rate of change is
influenced by the quality of runoff water
in the basin.
The quality and quantity of the dis-
charged material must be known, if its
impact on retention basin water is to be
accurately predicted. When basin
contents are to be applied to cropland,
optimal application rates are a function
of nitrogen concentration. Accurate
quality predictions are critical if optimal
nutritive values are to be fully realized.
Previous modeling efforts have
provided techniques for predicting the
size of runoff retention facilities to
achieve various levels of runoff control
or to predict the runoff retention
achieved by various combinations of
retention basin sizes and management
strategies. No previous efforts have
attempted to predict the quality of reten-
tion basin contents.
The initial plan for this effort was in
two phases. The first phase was to
develop a predictive model to estimate
the pond volume, liquid temperature,
and liquid constituent concentrations
listed in Table 1.
Originally, a cattle feedlot runoff
retention basin was to be sampled
simultaneously to generate data for
calibrating the model. In Phase II of the
project, the model was to be verified by
the collection of data in an intensive
field study. Due to changing research
priorities within the EPA, only Phase I of
the project was funded: the develop-
ment of a continuous water quality
model which will predict, on a daily
basis, the quality of feedlot runoff
entering a runoff retention basin and
contained in the basin. That runoff
would be discharged in case of an
uncontrolled event, or removed from the
basin for subsequent treatment, or
disposal on land. The predicted quality
for basin contents will be compared
with analytical data based upon samp-
ling a cattle feedlot runoff retention
basin in eastern Illinois during the
summer of 1978
In a separate but related effort, quality
changes occurring during the sprinkler
application of anaerobically stored
liquid manure to cropland was
investigated. Those data are also
included in this report.
Conclusions
Originally, this project was to include
two additional years of feedlot runoff
and runoff retention basin sampling at
several locations, to confirm the validity
of the model and to better define varia-
tions in the derived coefficients as a
function of site-specific variables. Due
to changes in priorities within EPA,
funding was not provided beyond the
initial phase; therefore, a degree of
uncertainty remains concerning the
accuracy of the reported coefficients
when applied to sites in different
climatic and geographic regions.
A technique was developed to predict
the quality of cattle feedlot runoff based
upon the various parameters. Using this
technique, it is possible to obtain a
better estimate of this quality than by
any other known procedure. Previous
work by the authors of this report and
others has provided a satisfactory
method of estimating runoff quantity in
response to climatic data and feedlot
characteristics. The water quality model
of a runoff retention basin developed in
this project is based upon an analysis of
previously published data and intensive
sampling of a cattle feedlot in Illinois.
The model represents the best available
technique for predicting the quality of
runoff water used for land application
under specific climatic conditions,
should runoff exceed the storage
capacity of the retention basin. Daily
calculation of liquid volume in a
retention basin is possible with this
technique. Also, the following water
quality parameters can be predicted:
COD, TS, FDS, TC. FC, and FS.
Water quality changes between a
storage reservoir and the land surface
during the process of sprinkler irrigation
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were analyzed to document that the
only significant change was NH3-N
volatilization. Depending primarily on
pH of the wastewater, volatilization of
NHs-N can range from nearly zero to
over 40 percent. Other variables which
influence NHa-N loss are air tempera-
ture, wind velocity, relative humidity,
droplet size and travel distance of the
droplet. The predictive technique
devised allows precise definition of this
nutrient loss.
Hydro logic Model
The hydrologic model developed in
this study can predictquality of runoff in
the following stages: (1) entering the
retention basin after running off a
feedlot surface and passing through a
solids trapping phase in a settling basin,
a porous dam, or a grassed waterway,
(2) contained in the retention basin, (3)
discharged from the retention basin by
uncontrolled events, (4) removed for
subsequent application to land, and
(5) deposited on the interception surface
of the land treatment area. The
hydrologic model and management
scheme provided the input quantities to
•determine how long material has been
in the basin and the extent of its degra-
dation.
This water quality model comple-
ments the water quantity models
developed previously under EPA grants
to Oregon State University and Kansas
State University. When completed, this
water quality model will provide a com-
plete quality and quantity model, to
provide a tool for evaluating the impact
of a cattle feedlot upon the waterquality
in a basin.
The continuous watershed model for
the hydrologic portion of the feedlot
runoff control system has previously
been described by Zovne and Koelliker1.
The reader isdirectedtothatpuolication
for a complete description of the model.
Included herein is an abridged descrip-
tion. Figure 1 shows a process sche-
matic of the feedlot runoff model. The
three components of the model are the
feedlot runoff generating surface, a
runoff retention basin and a soil
moisture budget model for the runoff
disposal area.
Zovne, J. J. and J. K. Koelliker. 1979. Application of
Continuous Watershed Modeling to Feedlot
IWm>« Managementand Control. EPA-600/2-79-
065, U.S. Environmental Protection Agency.
Washington, DC, 156 pp.
Feedlot
Surface
Settleable
Solids
Removal
Feedlot
Runoff
Figure 1.
Feedlot runoff generating
system.
For the purposes of the hydrologic
model, the surface area of the feedlot
must be defined so that the depth of
runoff produced times the area of the
feedlot will yield the runoff volume.
Likewise, the total surface area of the
retention pond at maximum depth must
be defined since the amount of precipi-
tation falling upon this surface is all
added to the volume of the basin. The
volume of precipitation added to the
basin is then the daily depth of precipi-
tation times the maximum surface area.
To determine evaporation from the
pond, the side slope, length, and width
of a pond must be defined. Evaporation,
considered to occur only from the actual
surface area of the liquid within the
pond, is equal to the actual surface area
times the predicted daily depth on pond
evaporation. The volume removed for
disposal is a function of the area of the
disposal field to which liquid can be
applied by the disposal system times the
depth of liquid that will be appliled in
one day. Therefore, the physical capa-
bilities of the disposal system must be
defined in order to set the daily disposal
volume. Discharge occurs when the
retention pond volume is exceeded.
Therefore, a maximum pond depth is
also required.
The deterministic water budget model
for the hydrology of the system is driven
by daily values of minimum and
maximum air temperature and daily
precipitation from a continuous
weather record for a particular station.
Other meteorological inputs required
are monthly mean values of air temper-
ature, solar radiation, relative humidity,
wind travel, percent sunshine, and A
and B coefficients for the Brunt
equation. Other input data needed for
the feedlot include a soil type in the
disposal area of only 12 classifications;
crop to be grown on the disposal area;
the management system for operation
of disposal, if any; and the limitations of
Table 2. Inputs to the Hydrologic
Model.
Physical characteristics of the system
Feedlot surface area
Surface area of retention basin at
capacity
Retention basin dimensions and
interior slopes
Disposal Held
Area
Soil type (one of 12)
Crop to be grown
Management system
Maximum application rale
Climatic data
Monthly mean data
Air temperature
Solar radiation
Relative humidity
Wind travel
Percent sunshine
Brunt equation coefficients
A and B
Daily values
Maximum temperature
Minimum temperature
Precipitation
the amount of runoff applied in any one
period, if any. These inputs are sum-
marized in Table 2.
This model was developed as a
technique to evaluate a particular feed-
lot in a particular location within the
continental United States; it is consid-
ered to be the most rigorous hydrologic
model that has yet been developed for a
feedlot runoff control system. All
masses of constituents will be reported
in kg/ha and all concentrations in mg/l
Adaptation to Hydrologic
Model for Water Quality
Con sidera tions
For purposes of the water quality
model, a unit feedlot area is considered.
To accommodate this approach with the
hydrologic model, a runoff control
system provides realistic runoff control
at a particular location. Next, all
volumes generated in the hydrologic
model are divided by the feedlot area to
provide values in terms of a depth per
jnit area of feedlot. Further, all depths
are converted to SI units of cubic meters
per hectare (mVha). This approach
allows fora simpler look at the quality of
runoff without complicating the issue
with the physical size of the feedlot
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runoff control system; i.e., the size of the
feedlot has no influence upon the
quality of the runoff water. However,
such factors as the shape and depth of
the pond may have some influence on
water quality within the system at any
given time. The model's prediction of
feedlot runoff control quality is unlikely
to be precise enough to separate such
variables.
For the water quality model, the daily
changes in liquid volume in the
retention basin in m3/ha, then is
described by:
AV = RUNOFF + PRECIP - SEVAP
-DISVOL - DSCHRG (1)
where,
AV = change in liquid volume,
RUNOFF = feedlot runoff into the
basin,
PRECIP = precipitation onto the basin
surface,
SEVAP = evaporation from basin
surface,
DISVOL = amount of liquid removed
by disposal operation, and
DSCHRG = amount of liquid dis-
charged by uncontrolled
events.
Infiltration through the bottom of the
pond is assumed to be zero. Sludge is
the volume of solids that accumulates
within the retention pond as estimated
in the COD portion of the model. The
volume of liquid within the pond at any
time per ha of feedlot is equal to the
pond volume (PONVOL) yesterday, plus
AV minus the increased volume
occupied by the sludge.
Modeling Cattle Feedlot
Runoff Quality
The cattle feedlot runoff process is a
complex phenomenon controlled by a
variety of physical, climatological, and
environmental factors. An effective
modeling effort requires that these
factors are selectively handled to assure
that the end product is useful as a plan-
ning tool even where in-depth local data
are not available.
Although a fully satisfactory relation-
ship between the factors influencing
the cattle feedlot runoff process and
runoff quality has not been achieved,
nor is it likely to be achieved in the
future, there are sufficient data
available to use runoff quality as an
input in calculating the quality of runoff
retention basin contents. The structure
of this process utilizes commonly avail-
able climatic and physical data to make
the needed estimates. The following
basic structure is inherent in the
process being proposed:
1. Cattle feedlot runoff is. an area-
based phenomenon; hence, the
constituent concentrations are
independent of feedlot size.
2. Being an area-based process, the
number of cattle on the lot is not an
input to the process. This assumes
the cattle are present in sufficient
intensity to preclude the growth of
vegetation, but not at such an
intensity to inhibit efficient animal
growth nor to result in unsuitable
lot conditions. Typically, this trans-
lates into an animal density of
between 350 and 850 head per ha
(1 50 and 350 head/ac).
3. Some technique to remove easily
settleable solids from runoff, prior
tointroduction of the runoff into a
retention basin, is a function of
sound design; such a function is
assumed to be part of this model.
The technique might involve use of
a debris basin, grassed waterway,
sedimentation basin, porous dam,
or any other device to provide short-
term sedimentations.
4. This is a calendar-based model
devised to estimate the average
concentration of runoff produced by
the precipitation occurring on a
specific day. For a storm which
occurs on two or more successive
days, each day is treated
separately.
The physical, chemical, and microbio-
logical quality of cattle feedlot runoff is
highly variable, not only among sites
and separate storms but during the
progress of a runoff event as well.
Field Sampling Program for
Data Collection
The basis for selection of an ideal
feedlot site from which to collect field
data was that the site be representative
of typical conditions in the major
feeding areas of the United States; also,
a site was needed which would insure
several runoff events and disposal, from
the retention pond during the testing
period. As much variation as possible in
pond volume and water quality as
desired to assure that the model would
be responsive to such changes. Since
our sampling program was operated
during the spring and summer, we
chose a more humid region of the
country where rainfall was likely to be
more consistent. Previously, sampling
programs had been run at several feed-
lot locations in Illinois. Also, previous
data were available in a form which
could be applied to evaluate the model's
performance.
Incorporation of Field Data
into Predictive Model
Occasionally, large discrepancies
occurred between measured pond
volumes and volumes predicted by the
hydrologic model. The nature of these
discrepancies indicated that substantial
subsurface seepage was entering the
pond, possibly originating in cultivated
fields adjacent to the feedlot. These
spurious flows rendered much of the
data useless. As a consequence, only
data collected during a single 45-day
perod was considered reliable enough
to be used for calibration of the model.
The accepted procedure for a modeling
effort of this sort calls for calibrating the
model with one set of data, and then
testing with a second set of data. How-
ever, because of the subsurface flow
problem, the data collected were not
sufficient for an independent test of the
model. Because of the resultant data
limitations, simple calibration of the
model did not confirm the model, nor did
it adequately represent the ideal situa-
tion upon which the model building
effort was posited.
Demonstration of the Model
To demonstrate the model's ability to
predict runoff and retention basin
quality, a simplified weather pattern
was adopted in which constant monthly
temperatures were assumed and
discrete rainfall events were specified.
Those simplifying assumptions allow
the influence of particular variables to
be noted so that the function of the
model can be viewed. A runoff retention
basin having a surface area equal to 35
percent of the feedlot surface area was
assumed.
Variations in cattle feedlot runoff
quality were expected to occur with
temperature,, rainfall intensity and pre-
vious rainfall for various dates on which
runoff was assumed to occur. The effect
of precipitation occurring as
accumulated snowfall is shown by the
runoff which occurred on specific dates
when no rainfall occurred. Januarv
temperatures were assumed to be stiff i-
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ciently low to maintain a snowpack;
hence, a high concentrated runoff was
noted as soon as the temperature
increased. Subsequent storms of one.
two and three days duration are shown
for comparison purposes to note the
effect of those variables on both runoff
quality and quantity.
The impact that various runoff events
have on the pond liquid concentrations
were shown by measuring runoff reten-
tion basin quantity and quality. In all
cases, the pond is assumed to have a
completely mixed liquid layer overlying
a sludge layer. Thus, a runoff event has
an immediate effect upon the liquid con-
centration. The periods during which
various constituents increased when no
runoff was occurring reflects the degra-
dation of the sludge layer releasing
soluble materials into the liquid portion.
Again, the model allows one to view the
impact of temperature and precipitation
on the rate of change of various consti-
tuents with time.
J. Ronald Miner and Marshall J. English are with the Department of Agricultural
Engineering, Oregon State University, Corvallis. OR 97331, and James E.
Koelliker is with the Agricultural Engineering Department, Kansas State
University, Lawrence, KS 66044.
R. Douglas Kreis is the EPA Project Officer (see below).
The complete report, entitled "Predicting Cattle Feedlot Runoff and Retention
Basin Quality." (Order No. PB 81-113045; Cost: $17.00, subject to change)
will be available only from:
Nationat Technical Information Service
5285 Port Royal Road
Springfield VA 22161
Telephone: 703-487-4650
The EPA Project Officer can be contacted at:
Robert S. Kerr Environmental Research Laboratory
U.S. Environmental Protection Agency
P.O. Box 1198
Ada, OK 74820
- US GOVERNMENT PRINTING OFFICE: 1961 - 75.7-064/Oa 18
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Environmental Protection
Agency
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