2006 Annual Report Waste Management | Dickinson
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Development of a
Software for Feedlot Hydrology/Nutrient Management
Unal Kizil1, James A. Lindley2
2Professor Emeritus, North Dakota State University, Agricultural and Biosystems
Engineering Department
Abstract. A software program was
developed to estimate runoff quality/quantity, make manure nutrient management
plans, and design waste storage and treatment facilities. Visual Basic
programming language was used to develop the software. The Soil Conservation Service’s curve number
method and EPIC and AGNPS models were used in the hydrological calculations. A
mass balance approach was employed to estimate nutrient fate of manure and
runoff throughout a year. Nutrient budget calculations were provided to the
user with default values that are either obtained from field studies or from
literature. Based on the results obtained from hydrology and manure management
calculations, a module was provided to design manure and runoff storage and treatment
structures. In the paper, models and their use in the program were explained.
Integration of the models with each other was explained with flowcharts. Basic
information was provided about the use of the program.
Manure management
software is generally available for nutrient management calculations. These
softwares cannot be used to estimate the pollution potential of feedlot
operations. Other software such as Animal Waste Management Software (AWM) is a
useful tool to design storage and treatment structures. However, it can be used
for neither manure management nor water quality estimation.
Even though computer
programs are available for water quality management, manure nutrient budgeting,
and control and treatment structures design, there is no software available
containing all these calculations. Water quality models and software are
generally considering watershed-based applications and paying less attention to
feedlot hydrology.
Therefore, objectives of
this paper are (1) to define the models that will be used in the program and
(2) to develop a user-friendly software that can be used in feedlot
hydrology/nutrient management and runoff/manure storage and treatment
structures design.
Methods
Visual basic programming language has been used to develop the software program. Feedlot Hydrology and Manure Management Software consists of three modules, including hydrology, manure management, and storage/treatment structure(s) design. Some default data such as animal manure characteristics, daily manure production rates, monthly evaporation, and rainfall data for all the counties in
The following modules
describe the models and their relation with each other.
The runoff and nutrient
transport model employs the Soil Conservation Service (SCS) curve number method
for runoff prediction (Eq 1, 2, and 3).
Since this software was
developed to estimate runoff quantity and quality to make nutrient management
plans, monthly rainfall values and evaporation rates were considered. In the
program, runoff depth is the runoff generated from the net rainfall for the
production year. Default monthly rainfall and evaporation values were provided
for each weather station in
After
calculating the runoff quantity, the nutrient transported with the runoff was
calculated. The EPIC model approach was adapted to calculate the runoff carried
by organic-N, nitrate-N, sediment phase of P, and soluble phosphorus
concentrations. The EPIC model uses the soil nutrient concentrations as an
input to runoff and predicts runoff concentrations. However, a feedlot surface
is generally covered by manure and is compacted by the animals. Feedlot surface
is the source of nutrients. Therefore, in the developed model, when the runoff
concentrations are calculated, feedlot surface nutrient contents were
considered. In order to provide default data, samples were collected and sent
to a commercial laboratory.
Runoff organic-N
concentration was calculated using the following equation adapted from EPIC
model (Eq. 4). Based on the literature, runoff sediment concentration was
assumed to be 1.5 % of runoff volume. Similar to organic-N, runoff nitrate-N
concentration was calculated using Eq. 5:
The EPIC model does not
provide a method to predict total runoff N concentration. Therefore, an AGNPS
model approach was used. The AGNPS model, unlike the EPIC model, considers a
default runoff N concentration value, and then based on the animal density on
the feedlot, it predicts runoff N concentration. The percentage of manure pack was
calculated based on animal unit density on the feedlot; runoff N concentration
was calculated proportional to the percentage of manure pack. If the percentage
of manure is 100, it is assumed that runoff N concentration is equal to that of
the default runoff concentration. However, if the percentage of manure pack is
75, the runoff N concentration is considered to be 75 % of default value (Eq.
6). After total N concentration, ammonium-N was predicted. Total N is the sum
of organic-N, nitrate-N and ammonium-N. Therefore, once the other components
are calculated, ammonium-N concentration can be predicted using Eq. (7):
The EPIC model equations
were used to predict phosphorus concentrations. Sediment and soluble phases of
phosphorus were predicted using Eqs. 8 and 9:
Manure Management Module
The mass balance
approach is used to predict nutrient fate of manure. This approach combines
nutrient loss information related to feedlot operations into a descriptive
model. The model tracks N and P through each of the system components including
collection, storage, treatment, and application and assumes that the operation
is a steady-state system (Eigenberg et al., 1998). The model utilizes the NRCS
Agriculture Waste Management Field Handbook procedures (Krider et al., 1992).
A schematic representation of the manure management module of the program is given in Figure 2. The dashed line represents the management options.
Runoff quality and
quantity calculations are based on the hydrology module of the program.
Management options allow users to store runoff with manure, or in a separate
structure, and apply runoff to the same field with manure or to another field.
The nutrient budgeting
procedure given by Craig and Beegle (1999) was employed with the mass balance
approach and feedlot hydrology model. The mass balance approach helps the model
predict nutrient fate, and the runoff module estimates the nutrient transport
from the feedlot. Finally, the budgeting procedure combines these two approaches
to calculate application rate, additional fertilizer requirements, and
commercial value of manure/runoff generated from the feedlot.
In the nutrient
budgeting calculations, animal unit (AU) was used. One AU was considered to be
500-kg live weight. Total manure production for the production season was
calculated using the daily manure production per AU, total AUs, and number of
days manure is produced (Eq.11):
Nutrient losses during
collection, storage, treatment, and application were calculated. Application
losses were calculated for four different application methods including
broadcasting, incorporation, sprinkling, and injection. The mass balance
approach and nutrient loss factors for feedlot manure were adapted from
Eigenberg et al. (1998).
Before calculating N and P balanced manure application rates, available N and P for each disposal land were calculated. A field may receive only runoff, only manure, or both. Therefore, the user is asked to enter the percentage of runoff and manure that each disposal field receives. Available N and P were then calculated using Equation 12:
Application rates were calculated based on N and P requirements (Eqs. 13 and 14). Then the actual application rate was determined. If the manure is to supply all the nutrient requirements for the crop, the higher of the two application rates was chosen. If the purpose is to maximize the use of manure nutrients, the smaller rate was chosen (Eq. 15):
Possible management
options for runoff and manure are shown in the following flowchart (Figure 3).
If there is no runoff containment structure, the hydrology/nutrient model
provides the information about the pollution risk of that particular feedlot
operation.
The final step was to
estimate the commercial value of nutrients applied. The user was asked to
estimate unit prices of commercial fertilizer. The application rate and the N,
P, and K values were used to predict the economic benefit of the manure
nutrients.
Containment and Treatment Structure Design Module
Manure and runoff storage and treatment pond design criteria are taken from AWMFH (1992) (Eq. 16). It is initially assumed that side slope ratio and liquid depth are known. The manure management module provides data for the runoff and/or manure storage volume requirement. After assigning a length-width ratio, Eq. 16 can be solved. The root of the quadratic equation gives the bottom width of the pond.
Required data are asked from the user through seven different data windows. These data windows are General, Animal, Feedlot, Crop/Land, Weather, Management, and Design.
The general data window
asks the user information such as hours per day when animals are not in the
feedlot, days per year when the manure is not produced, and estimated prices of
commercial fertilizers. The
animal data window provides the general information about the animals housed in
the operation. The number of animals and average animal weights were asked.
Daily default manure, total solids, volatile solids, BOD production rates, and
nutrient concentrations are provided to the user.
In the feedlot data
window, the runoff curve number and surface area for feedlot and contributing
area are asked. Also, default feedlot soil characteristics are provided to the
user. Since it might have been conservative, a default curve number for the
contributing area was provided.
In the crop/land data
window, the proposed crop to be planted, typical manure and fertilizer
application rates, and information about manure history for up to five lands
are asked. Phosphorus requirement for the selected plant were calculated
considering Bray-1 and Olsen recommendations. In the calculation of P and K
recommendation, soil test results and yield goal were asked from the user.
Nitrogen recommendation requires soil test results, yield goal, sampling day
adjustment and previous crop credit. Sampling day adjustment and previous crop
N credit were explained and the tabular data was provided in Franzen and
Cihacek (1996).
The weather database
covers the data such as monthly rainfall and evaporation, 25-year and 24-hour
rainfall data, 10-year and 1-hour rainfall intensity, lagoon volatile solids
loading rate, and lagoon BOD loading rate. Volatile solids loading rate and BOD
loading rate data were obtained from AWMFH (1992). The default database
includes all this information for all the stations in
In the management data
window, manure application techniques and options for manure/runoff storage and
treatment are provided. Broadcasting, incorporation, sprinkling, and injection
are the possible techniques provided to the user for manure/runoff application.
Based on the season, default nutrient loss factors are provided.
Finally, in the design
data window, some preferred structural/management information are asked to
design runoff and manure storage ponds, runoff settling basin, runoff settling
tank, circular and rectangular manure tanks, manure stacking structure, and
anaerobic and aerobic treatment ponds.
Since each module
requires data from the previous module, after entering the data, one should run
the models for hydrology, manure management, and design modules, respectively.
Reports are generated for each module. Estimated runoff characteristics, runoff
volume, manure and runoff nutrient fates, and dimensions of the
storage/treatment structures are provided in printable forms.
A complete example for a
beef feedlot was run for the following conditions using default data.
The hydrology/nutrient
transport, nutrient budget, and design reports are given in Figure 4, 5, and 6,
respectively.
Figure 6 shows that
collection, storage, and treatment has a significant impact on manure N content
while the P content remains almost same. The chart demonstrates the importance
of a runoff containment/treatment system. Stored and treated runoff N decreased
dramatically during these periods. In the absence or failure of a runoff
control system significant pollutant discharge may happen. The commercial
values and pollution potential of manure and runoff will help user to observe
the importance of manure/runoff management.
In the design module of
the program structural specifications for different storage/treatment
facilities are reported. Based on the available land one can see the different
alternatives and make the best decision for his/her operation.
Hydrology output,
including annual and event-based calculations, lets the user see the long- and
short-term pollution potential from his/her feedlot. The nutrient budgeting
module gives a good estimation of manure and runoff nutrient fate. For
different management options, the program can be run, and change in nutrient
fate could be observed for different options.
Since the program
designs all possible manure and runoff treatment/storage structures, one can
observe and decide the appropriate treatment/storage structure for his/her
operations. The program can also be used to see effects of these structures on
the pollution potential of the feedlot. For example, nutrient concentrations of
manure or runoff at the time of application could be observed if there was a
treatment facility.
It has been aimed to
provide as much default data as possible to the user to make the use of the
program easy. Also, the program provides a flexibility to change the default
data when the observed or real data available. The use of manure, runoff, and
soil test results will increase the precision of the results and avoid over and
under application of nutrients.
As the new models and
programming languages are released, this study should be updated. One challenge
might be the distribution of this software and database. With the collection of
more default data such as manure characteristics for each animal species and
feedlot soil characteristics for
Future work may involve
collection of the mentioned data. Also, nutrient loss factors that are given as
default values are not determined for
References
AWMFH. 1992. Agricultural Waste Management Field Handbook.
CFFM. 2000. Manure Application Rate Planner. Center for
Farm Financial Management. Department of Applied Economics,
Craig, P.H., and D.B.
Beegle. 1999.
Nutrient Management Plan Writing Workbook.
Eigenberg, R.A., R.L. Korthals, J.A. Nienaber, and G.L.
Hahn. 1998.
Implementation of a mass balance approach to predicting nutrient fate of manure
from beef cattle feedlots. Applied Engineering in Agriculture 14(5):475-484.
EPA. 2000. National pollutant discharge elimination system
permit regulation and effluent limitations guidelines and standards for
concentrated animal feeding operations, Proposed Revisions, December 15, 2000.
http://www.epa.gov/owm/afos/proposedrule.htm. 2002.
Fraisse, C.W., K.L. Campbell, J. W.
Franzen, D. W., and L. J. Cihacek. 1996.
Kessel, J.S., R.B. Thompson, and J.B. Reeves III. 1999. Rapid on-farm analysis
of manure nutrients using quick tests. Journal of Production Agriculture
12(2):215-224.
Krider, A.N., D.A.
MWPS 18. 1993. Livestock waste facilities handbook. Midwest
Plan Service,
NRCS. 1995. Animal waste management software. Natural
Resources Conservation Service.
Powers, W.J., and H.H. Van Horn. 2001. Nutritional
implications for manure nutrient management planning. Journal of Applied
Engineering in Agriculture 17(1): 27-39.
Van Horn, H.H., G.L.
Nordstedt, A.V. Bottcher, E.A. Hanlon, D.A. Graetz, and C.F. Chambliss.
1991.
Dairy manure management: strategies for recycling nutrients to recover
fertilizer value and avoid environmental Pollution. Circular No.1016
Van Horn, H.H., G.L. Newton, and W.E. Kunkle. 1996. Ruminant Nutrition from
an Environmental Perspective: Factors Affecting Whole-farm Nutrient Balance.
Journal of Animal Science 74(12): 3082 – 3102.
Van Horn, H.H., G.L. Newton, G. Kidder, E.C. French, and
G.L. Nordstedt. 1998.
Managing Dairy Manure Accountably: Worksheets for Nutrient Budgeting. Circular
No.1196
Nomenclature
Acont = Contributing area, (m2)
Afeedlot = Feedlot surface area, (m2)
ActualAppRate = Actual manure application rate,
(t/ha)
AU= Animal unit
AvailableN = Available N, (kg/t)
AvailableP = Available P, (kg/t)
AvNut = Available N or P,
(kg/t)
BL = Bottom length, (m)
BW = Bottom width, (m)
CNavr = Average runoff curve
number
DMP = Daily manure
production rate, (kg/day/AU)
ER = Enrichment ratio
kd = P concentration in the
sediment divided by that of the water, (175 ppm)
LD = Liquid depth, (m)
MappNut = Manure nutrient
contents at the time of application, (kg)
N = Runoff total-N
concentration, (ppm)
Ndefault = Default runoff
total-N concentration, (ppm)
NetNReq = Net N requirement,
(kg/ha)
NetPReq = Net P requirement,
(kg/ha)
NH4 – N = Runoff ammonium-N
concentration, (ppm)
NO3 – N = Runoff nitrate-N
concentration, (ppm)
NO3sur = Feedlot surface
nitrate-N concentration, (ppm)
NRate = N balanced manure
application rate, (t/ha)
ONsur = Feedlot surface
organic-N concentration, (ppm)
OrgN= Runoff organic-N
concentration, (ppm)
Psed = Sediment phase of
runoff P concentration, (ppm)
Psol = Soluble phase of
runoff P concentration, (ppm)
Psur = Feedlot surface P
concentration, (ppm)
Ptotal = Total P
concentration, (ppm)
PMP = Percentage of manure
pack
PMR = Percent manure
received
PRate = P balanced manure
application rate, (t/ha)
PRR = Percent runoff
received
Q = Runoff depth, (mm)
R= Net rainfall depth,
(mm)
RappNut = Runoff nutrient
contents at the time of application, (kg)
s = Retention parameter,
(mm)
Sy = Sediment yield,
(t/ha)
SS = Side slope, (1/n)
TDMP = Total days manure is
produced
TMP = Total manure
production, (t)
TMTM =Total manure to be managed, (t)
V = Runoff volume, (m3)
Vol = Pond volume, (m3)
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