Feedlot Hydrology Modeling

 

Unal Kizil and James A. Lindley

Agricultural and Biosystems Engineering Department

North Dakota State University

 

I

ntroduction

Although the United States has made significant progress in cleaning up water resources, still nearly 40 percent not meet quality criteria for drinking or recreational use. Pollution from industrial areas has been reduced, but runoff from agricultural operations still continues to pollute water (Haberstroh and Wilbur, 1999).

 

In feedlots, high concentrations of animals produce concentrated areas of manure production. Annual N production may be as much as 10 Mg Nha-1. About 50 percent of the N, is lost by ammonia volatilization (Power et al., 1994). Significant amounts of P and N are contained in the runoff (Swanson et al., 1971) and can create serious environmental problems if runoff is not retained in runoff containment structures.

 

One of the most important problems that feedlot operations face is the disposal of wastes. Disposal can be achieved by constructing holding ponds to collect manure and runoff until the field application time (Pinkowski et al., 1985). Feedlot runoff contains numerous pollutants that can be a significant source of water pollution (Nye, 1982). Power et al. (1994) reported that volatilization loss of nitrogen (N) is more significant than the runoff loss from the feedlots; however, the primary source of phosphorus (P) loss is runoff.

 

Yang and Lorimor (2000) reported runoff characteristics for a 22,720 m2, 380-head beef cattle feedlot as 109 and 34 ppm for N and P, respectively. In another study, Sweeten (1994) reported that feedlot runoff contains 3202, 93, and 31 ppm of COD, N and P, respectively. Nitrogen may be converted to nitrate form by soil bacteria. If the nitrate-N reaches the groundwater and concentration exceeds 10 ppm, it may create serious health problem for babies, pregnant women, and livestock (Madison et al., 2002).

 

Phosphorus transported by runoff can cause nutrient enrichment in surface water resulting in increased biological productivity. This process is called eutrophication and has been identified as the main source of surface water pollution (EPA, 1996, and Sharpley et al., 1999). Increased growth of algae and oxygen shortage restricts water use for fisheries, recreation, industry, and drinking. Phosphorus concentration exceeding 0.02 ppm in lake water accelerates the eutrophication (Sharpley et al., 1999).

 

The overall goal of the research reported here is to develop a complete feedlot runoff and nutrient management model to predict runoff and its concentrations generated from feedlots. Specific objectives of the study are to define hydrological models for feedlots, and to validate the model results with field experiments.  

                                                                                                                                              

Study Area and Instrumentation                                    

Runoff from a bison feedlot at the Carrington Research Extension Center has been measured. Manure, runoff, and pond samples were sent to a commercial lab to be analyzed. An ultrasonic sensor-based flowmeter was installed to collect flow data. Two D-Tec, float operated, Environmental Liquid Samplers have been used to collect runoff samples for quality analysis. To monitor runoff storage pond water quality an ISCO Model 3700 water sampler was used. Samples were analyzed for moisture content, dry matter, N, NO3-N, NH4-N, Organic-N, P2O5, and K2O.

 

Hydrology and Nutrient Transport Model

Rainfall runoff generated from the feedlot areas was calculated using SCS Curve Number method (SCS, 1972).

 

Nutrient transport equations are taken from the EPIC model (Williams et al., 1984), and AGNPS (Young et al., 1987). In the prediction of Org-N, NO3-N, sediment phase of P, and soluble P, the EPIC model approach was employed.

 

Total-N, and COD content of runoff were predicted using the AGNPS model approach. In the prediction of NH4-N it is assumed that NH4-N content of runoff is the difference between total-N, and the addition of Org-N and NO3-N (MWPS-18).

 

Results and Discussion

Seven runoff events were observed during summer of 2001. Runoff hydrographs for the feedlots were developed and runoff volumes were calculated for a particular rainfall event. Runoff data collection will continue in 2002. Therefore, the following results are preliminary data.                                                       

Soil Conservation Service (SCS) Curve Number Method employs a number to calculate runoff volume. This number is dependent on soil characteristics, soil cover and use. On a feedlot surface, a non-permeable layer is formed because of the compaction of the manure. It is assumed that there is no seepage through the soil layer. Considering this, the only important factor affecting the runoff curve number for the feedlot is manure compaction. In the literature following, curve numbers were suggested for feedlots (Table 1).

 

Table 1. Feedlot runoff curve number values

 

Curve Number

Researcher

Paved

Unpaved

Hauser (1975)

Swenson (1975)

Vanderholm et al. (1979)

Young et al. (1982)

82

96

97

94

82

82

90

91

 

Wet antecedent

Average antecedent

Miner et al. (1979)

97

91

 

In the following Table 2., rainfall, and observed and predicted runoff values are given. Following data concludes that curve number of 93 provides best correlation coefficient (r=0.89) between predicted and observed runoffs.

 

Table 2. Predicted and observed runoff events

 

 

Runoff

Rainfall event no.

Rainfall (mm)

Predicted

Observed

1

2

3

4

5

6

7

21.8

18.3

35.6

22.6

20.3*

5.3*

11.2

16.1

11.5

36.6

17.2

14.1

0.20

3.80

10

8.6

20

12.3

16.0

2.0

8.3

* Same rainfall event occurred in consecutive different days.

 

Manure samples were collected to be used in the model. Table 3 shows some manure analysis results and average nutrient contents of bison manure.

 

Table 3. Manure analysis results in ppm

Sampling date

N

Org-N

NO3-N

NH4-N

P

K

6.11.01

6.11.01

6.18.01

6.18.01

6.25.01

6.25.01

8.27.01

8.27.01

8.27.01

8.27.01

4678

4283

5682

6629

6932

4755

6120

5585

4467

5581

4611

4157

5165

6212

6429

4310

5596

5218

4092

5526

7.47

5.91

6.36

6.21

21.4

6.10

31.5

10.7

23.4

16.8

67

126

517

417

504

445

524

367

374

355

3571

3907

5759

7318

9088

3629

5663

2866

5400

3144

1797

1971

2001

2123

2724

2369

1213

789

1483

678

Average

5459

5088

13.22

371

5245

1830

 

Four runoff samples were collected and analyzed. Results are provided in the following Table 4. Since the number of samples is not adequate model results were not compare to observed values. It is expected to be done after collecting enough amounts of runoff data in 2002.

 

Table 4. Runoff analysis results in ppm

Sample #

N

Org-N

NO3-N

NH4-N

P

1

2

3

4

141

112

147

200

117

85

98

29

0.63

0.75

0.52

0.50

24

26

48

170

54

15

2

2

Average

150

82

0.6

67

18

 

Conclusion

It is essential to estimate the pollution potential of feedlot operations. Mathematical models provide one means of estimating pollution potential. To evaluate these models, runoff was measured for quantity and quality. This study indicates that a runoff curve number of 93 can be used to predict runoff from the bison feedlot at the Carrington Research Extension Center. The study is still continuing, and the nutrient transport model evaluation results will be provided after collecting adequate data in 2002.

 

Literature Cited

Environmental Protection Agency. 1996. Environmental indicators of water quality in the United States. EPA 841-R-96-002

Haberstroh, G, and Wilbur, J. 1999. Animal Feeding Operations. The North Dakota Approach. North Dakota Department of Health.

Madison, F., K. Kelling, L. Massie, and L.W. Good. 2002. Guidelines for applying manure to cropland and pasture in Wisconsin. University of Wisconsin Cooperative Extension Publications. A 3392, R-8-95-2M-E

MWPS 18. 1993. Livestock waste facilities handbook. Midwest Plan Service, Iowa State University, Ames Iowa

Nye, J.C. 1982. Runoff control for livestock feedlots. Research Results in Manure Digestion, Runoff, Refeeding, Odors. MWPS, North Central Regional Research Publication No. 284, 10-17.

Pinkowski, R.H., G.L. Rolfe, and L.E. Arnold. 1985. Effect of feedlot runoff on a Southern Illinois Forested Watershed. J. Environ. Qual., 14(1): 47-54.

Power J.F., B. Eghball, and J.A. Lory. 1994. Utilization of nutrients in beef cattle feedlot manure in the Northern Great Plains. Great Plains Animal Waste Conference on Confined Animal Production and Water Quality. Denver, Colorado. p 161:167

Sharpley, A.N., T. Daniel, T. Sims, J. Lemunyon, R. Stevens, and R. Parry. 1999. Agricultural phosphorus and eutrophication. United States Department of Agriculture, Agricultural Research Service, ARS-149.

Soil Conservation Service (SCS). 1972. Hydrology. In National Engineering Handbook, Sec. 4. GPO, Washington, DC.

Swanson N.P., N.L. Mielke., J.C. Lorimor, T.M. McCalla, and J.R. Ellis. 1971. Transport of pollutants from sloping cattle feedlots as affected by rainfall intensity, duration and reoccurrence. p 51-55. In: Livestock Waste Management and Pollution Abatement. ASAE, St. Joseph, MI 49085.

Sweeten, J.M. 1994. Water quality associated with playa basins receiving feedlot runoff. Playa Lake 1994 Symposium Article 17. http://lib.ttu.edu/playa/text94/playa17.htm.

Williams, J.R., C.A. Jones, and P.T. Dyke. 1984. A modeling approach to determining the relationship between erosion and soil productivity. Trans. ASAE 27:129-144.

Yang, P, and J, Lorimor. 2000. Physical and chemical analysis of beef cattle feedlot runoff before and after soil infiltration and wetland treatment. Proceedings of the 8th International Symposium on Animal, Agricultural and Food Processing Wastes. Des Moines, Iowa. pp. 203-208.

Young, R.A., C.A. Onstand, D.D. Bosch, and W.P. Anderson. 1987. AGNPS, Agricultural Non-Point-Source Pollution model; a large watershed analysis tool. U.S. Dept. Agr., Agric. Res. Serv., Cons. Res. Rpt. 35, Washington D.C., 77 pp.


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