Site Analysis


Theoretical Pig Feedlot Locations

By Maggie Mabrey



Feedlots are areas in which livestock (cattle & hogs) are fed and raised for slaughter. For this reason they are beneficial to society because they provide food for people. If these areas are not given proper thought and consideration on their placement, they can have detrimental effects on humans, aquatic life, wild life, and the environment. More specifically when feedlots are located directly adjacent to surface water, such as streams or steeply sloping land where runoff would be most prevalent.

When feces are washed off the land by a precipitation event nitrate and ammonium can be found in the water. Gangbazo et al states health effects can be associated with heightened levels of nitrate as nitrogen. Children are mainly effected with methemoglobinemia. Bacteria from the waste is also a problem. Howell et al notes that agricultural runoff influenced by non-point pollution, such as feedlots, frequently exceed the United States Environmental Protection Agency's standards for bacterial contamination of primacy contact water (200 fecal coliforms/100 ml.). People should be aware of the diseases that can be passed from animal feces in surface waters to people and other animals by ingestion. These problems can range from minor gastrointestinal to severe illnesses.

Taylor et al looked at how cattle affected streams by increasing ammonia and nitrate levels through runoff. This caused fish populations to decline. They found that once the cattle were removed from the area ammonia and nitrate levels went down allowing the fish population to increase. They go on to say the source of the ammonia and nitrate was the cattle's urine and feces. The pollutants caused an increase of oxygen being used by nitrifying bacteria, which caused a decrease of available oxygen for fish to use.

Before 1960, agriculture's role was thought to be insignificant when dealing with contamination. It was thought pollutants were from discharge of municipal and urban areas. After the 1960's attitudes started to change when large amounts of fish were found dead in streams neighboring animal feedlots. (Martin, 1997)

Abbozzo et al, 1996, acknowledge there is a problem with swine production and the environment, especially when dealing with water pollution from manure. They say that water is a resource. For this reason, everybody needs to use water whether it be for drinking, cooking, bathing, or irrigation. Maintaining that resource for previously mentioned uses is necessary for continued development and growth of feedlots. Furthermore, it is not the single area where the source is at that is affected, but neighboring communities as well due to the movement of surface water over vast areas.

For these reasons it is important to try and locate feedlots in areas that are beneficial to the farmer and have the least amount of negative impact on surface water, people and animals. GIS can be used to make the site selection process easier. Multiple layers can be incorporated (soil, slope, vegetation cover, current land uses, and runoff probability) so the user is able to see them at once. Maps can be made showing areas that would have the greatest potential pollution and areas that would be the most stable for feedlots. Sites may be selected using this map. (Tee and White, 1992)


To create a theoretical model to determine the amount of runoff that will occur from feedlots to a stream. A soil layer with a runoff index will be created as well as an elevation layer to determine the path of least effort for the greatest amount of runoff. Since this is a theoretical model being created, a contour map containing a river will be randomly selected. Six theoretical feedlot and earthen storage facilities will be arbitrarily placed along the river using siting guidelines from the Manitoba Practice Guidelines for Hog Producers in Manitoba, 1994. The model will be used to determine were the greatest amount of runoff will occur by taking into consideration slope and soil type. The end result will be to find the feedlot that will have the greatest amount of possible pollution. The information can be used to select the site that would benefit both farmer, neighbors, the environment, and aquatic and wild life.

Study Area:

The study area consisted of six sections in Cheyenne County in south west Nebraska. The terrain was relatively flat consisting of three main soil types: Kuma-Keith-Duroc, Alliance-Duroc-Kuma, and Jayem-Duroc-Keith. Kuma-Keith-Duroc is a combination of silty clay loam, silt loam, and loam so I classified it as more silt and clay particles for my purposes. Alliance-Duroc-Kuma consisted of silty clay loam, calcarious silt loam, loam, and silt loam it was classified as more loam and clay particles. Finally, Jayem-Duroc-Keith contained fine sandy loam, loam, silty clay loam, and silt loam. It was classified as more sandy particles. Since the project was theoretical, current land uses were ignored for siting purposes. The greatest amount of rain occurs in late spring early summer.



A base map needed to be established so the layers (DEM, soil, and site locations) would match up when overlayed. The map was scanned in to the computer using Adobe Illustrator then brought into Map Factory to be cleaned up. The base map contained the river of interest. All other information was removed from the base by grouping the pixel values and assigning them a "void" value. Section boundaries, section numbers, river, and one cemetery was kept so they could be used as reference points.

figure 1: Base Map



In order for the DEM to be created in SURFACE III it needed to match up with the base, I needed to find out the number of rows and columns in the base. This was done by using the TRACKER option in Map Factory. The number of cells for rows and columns would be used to determine the matrix size in SURFACE III. Points of elevation were traced on to a piece of paper from the six section test area. The points were chosen by how well they described the lines using the fewest points possible. The (x,y) values were determined by the distance (in centimeters) they were from the (0,0) point which was in the bottom left corner of the bottom section. Elevation was recorded as the z value.

A table of (x, y, z) data was created without headers in Simple Text. Simple Text was used because Surface III can read that format with out translation problems. Once Surface III was open, I brought the (x, y, z) data in so values could be interpolated between points to create the DEM.

The commands used were:

File...import...x, y, z text data

Next, I created a grid of the table using the commands:


It then asked for the number of rows and columns. The data was used from earlier on the size (number of rows and columns) of the base map. Next, I exported the created grid into Map Factory to view the DEM.

Commands used were:

File...Export...z-value matrix to not included header in output

Once in Map Factory the matrix was opened using these commands: delimited...floating point

It was important to choose floating point because the z-matrix of elevation consisted of decimal numbers. If fixed point was chosen the decimals would not have been able to be read in causing the program to not recognize the data. Higher elevations have a brighter signature and lower elevations a darker signature.

figure 2: DEM


When I was trying to bring the interpolated grid in from SURFACE III, it would not read it because the table was too big. To fix the problem, the grid size for the z-matrix and base map was reduced by half. The base map was taken care of in Map Factory using the script:

Respace "map name" By .5 Average


figure 3: Resized Base Map


Average was used because the numbers in the base map were fixed point. The grid size was then recalculated. Those values were taken back into SURFACE III so the z-matrix of interpolated values could be recreated. This time when it asked for the number of rows and columns, I put in the size of the resized base map.


The soil coverage was made off of the base map using Map Factory. To determine the soil type I looked in the Cheyenne County Soil Survey book of the six sections. Again, the three main generalized types of soil were: Kuma-Keith-Duroc (most runoff), Alliance-Duroc-Kuma (medium runoff), and Jayem-Duroc-Keith (least runoff). Sections were colored using the pencil, line, and polygon tools. Once the tool was activated, then a value and color were assigned so pixels values could be changed. Values and color were assigned according to runoff capability: Kuma-Keith-Duroc (2000, light signature), Alliance-Duroc-Kuma (1000, medium dark signature), and Jayem-Duroc-Keith (500, dark signature). The values and colors created needed to be separated from the base map so when the layers were added only the soils and elevations would be used in the calculations. To do this I used the following script:

Recode "map" Assigning "new values" to "old values"


figure 4: Soils


STEP 4: Overlaying DEM and Soils

This was done so an area could be found with the greatest amount of runoff and steepest slope. This would be the least desirable location for a feedlot. The two layers were added together using the following script:

"soil layer" + "DEM layer"


figure 5: Soils + DEM


STEP 5: Creating Theoretical Feedlot Locations

This was done in Map Factory and using the base map as a reference. Siting criteria were taken from "Farm Practices Guidelines for Hog Producers in Manitoba". They state that if more than ten livestocks are in a feedlot it should be a minimum of 50 meters from any surface water. The earthen storage should be at least 100 meters from any surface water. Before I could place the lots, I needed to figure out how much one cell represented. I found the number of cells (135) that represented one side of a section, which equals one mile. This gave the ratio 135 cells = 1 mile. The mile was converted to feet, so 5280 ft = 135 cells. The two were divided to give 39.11ft/cell. Feet were then turned into meters, 3.28m = 1 foot, giving the new ratio 12m/cell. 50 meters = 4 cells and 100 meters = 8 cells. To locate the units, I counted back from the river for the appropriate number of cells. The pencil tool was used once again to assign values and color. A feedlot was given a value of 12 and a orange color; earthen storage was green with a value of 13. These values were assigned to their own coverage so they when they are overlayed the locations could be seen clearly. The following script was used:

Recode "map layer" Assigning "new value" To "old value" Assigning "new value" To "old value"


figure 6: Feedlot and Earthen Storage Locations


STEP 6: Covering All Layers to Create the Final Map for Analysis

This operation simply lays each layer on top of each other so they can be compared to how they relate to each other spatially. The script to do this was:

Cover "base map" with "soil and dem" with "locations"


figure 7: All Layers



figure 8: Final Map for Site Analysis


Areas with the closer contours indicate steeper slope, and areas with over all brighter signature indicate the soil with the greatest runoff. With this in mind, site 2 is a bad location because there is a steep slope and a high runoff soil. Site 4 is also a bad location due to steep slope and a moderate runoff soil. These two sites would have the most runoff to the river, which may pose a threat to humans, wildlife, and water systems for recreational and agricultural purposes. Sites 1 & 3 are ok locations, but not the best choice because they have a high runoff soil type and moderate slope. Sites 5 & 6 would be the best choices. Site 5 has a gentle slope and moderate runoff while site 6 has low runoff and gentle slopes.


To achieve the model a base map was established, the digital elevation model created, soil and location layers created, then all were overlayed to create the final product. A theoretical approach was taken to see if this method would be affective for actual use. Indeed, this model for runoff works as an effective tool for site analysis. It can be used to help reduce contamination of streams from runoff consisting of fecal material, reduce the amount of waste carried down stream to neighbors, prevent spreading of diseases associated with waste to both humans and animals, and help maintain and preserve water as a resource for domestic uses, recreational uses, and aquatic life. However, incorporating other variables such as vegetation cover, current land uses, other surface water, more detailed soil classification, and a more precise measurement of the amount of runoff that would occur would give a more accurate assessment of the area in question. Also, buffering could be done around the river for the distance of feedlots and earthen storage as well as for incorporating other siting criteria (distance from roads, houses, desired size of land by farmer). This would allow for analysis of the entire area and not just selected sites.

References Sited:

1. Abbozzo, P.; Boggia, A.; and Brunetti, M. 1996. Environmental Quality and Hog Production.

Environmental Monitoring and Assessment. 41:171-182.


2. Agriculture Guidelines Development Committee in Cooperation with Manitoba Park Est. May

1994. Farm Practices Guide Lines for Hog Producers in Manitoba-Manitoba Agriculture.


3. Gangbazo, G.; Pesant, A.R.; Barnett, G.M; Charuest, J.P.; and Cluis, D. 1995. Water

Contamination by Ammonium Nitrogen Following the Spreading of Hog Manure and Mineral

Fertilizers. Journal of Environmental Quality. 24:420-425.


4. Howell, J.M.; Coyne, M.S.; Cornelius, P. 1995. Fecal Bacteria in Agricultural Waters of the

Bluegrass Region of Kentucky. Journal of Environmental Quality. 24:411-419.


5. Lee, Ming T. and White, David C. December 1992. Applications of GIS Databases and Water

Quality Modeling for Agricultural Nonpoint Source Pollution Control.


6. Martin Jr., John H. 1997. The Clean Water Act and Animal Agriculture. Journal of

Environmental Quality. 26:1198-1203.


7. Taylor, Frances; Gillman, Leah A.; Pedretti, John W. October 1989. Impact of Cattle on Two

Isolated Fish Populations in Pahranagat Valley, Nevada. Great Basin Naturalist. 49(4):491-495.


8. Borchers, Glenn A. November 1997. Soil Survey of Cheyenne County, Nebraska. United States

Department of Agriculture. Natural Resource Conservation Service.