Measuring the Capacity of Kentucky Crop Land to Assimilate Animal Manure

 

J.D. Long and R.A. Fleming

James Long is a Research Associate and Ronald Fleming an Assistant Professor in the Department of Agricultural Economics, University of Kentucky.

 

 

Abstract

With increased industrialization of the confined livestock feeding industry comes even larger stocks of manure. Yet the likelihood of soil nutrient toxicity and ground and surface water contaminate is minimal if sufficient crop acreage is available to assimilate manure nutrients. The inverse of the proportion of crop acreage times the proportion of acreage suitable for manure applications is used as an index of suitability. Using USGS Land Use Land Coding maps and digital elevation maps, levels of suitability are determined for western Kentucky. This information when used in a GIS framework helps guide the siting of livestock feeding facilities.

 


Introduction

With increased industrialization of the livestock industry comes ever-larger confined animal feeding operations (CAFOs) and associated manure stocks. These manure stocks are a growing concern of both the farming and non-farming public who fear eventual contamination of surface and groundwater supplies, nutrient and mineral toxicity of soil, and excessive odors. Yet, if properly managed, manure can augment soil organic material and serve as a natural source of crop nutrients.

In August 1997, Kentucky Governor Paul Patton imposed a 90-day moratorium on the issuance of permits for the construction of new swine production facilities. The Governor imposed this moratorium largely in response to public concern surrounding proposed investment in western Kentucky by two large, integrated swine production companies. Specifically, it was feared that current state environmental regulations were not adequate to protect surface and groundwater resources from contaminants arising from large swine production facilities.

During the 90-day moratorium, the Division of Water (DOW) in the Natural Resources and Environmental Protection Cabinet (NREPC) was instructed to develop new (emergency) regulations for the state. One of the issues debated during this period was the slope of crop acreage to which manure could be applied without fear of surface runoff of nutrients and other environmental contaminants. Regulators and environmental interests favored a 12 percent slope limit while agricultural interests favored a slope limit set at 18 percent. In March of 1998 a compromise version of the emergency regulations developed by the DOW that maintained a 12 percent slope restriction became law. However, these regulations are valid only until the next meeting of the state’s General Assembly in January 2000. At this time the General Assembly will take up the issue of swine (and other confined animal feeding operation) regulations and institute permanent regulations. Hence, the controversy surrounding the implementation of a 12 or 18 percent slope restriction is not yet settled.

Agricultural interests view an 18 percent restriction as sufficient to avoid manure runoff into surface waters. More importantly, they believe that a 12 percent restriction will eliminate a significant amount of crop and pasture acreage otherwise suitable for manure management. Without this acreage, manure management costs (particularly transportation) will rise resulting in higher production costs. In turn, these higher production costs imply that Kentucky’s pork industry will be less competitive in the US market.

Agricultural interests and others also conjecture that a 12 percent restriction could have a significant impact on the siting of swine production facilities. Specifically, to reduce their manure management costs, new swine facilities will want to locate in Aflatter@ regions of the state. This has the effect of concentrating the industry in a smaller area potentially leading to greater environmental impacts.

The purpose of this research is twofold: 1) to assess the impact on manure management cost of restricting the slope of crop acreage to which swine manure can be applied from 18 to 12 percent; and 2) to identify regions in the state where growth of the swine industry is more likely to occur as a consequence of differences in production cost. Achieving these goals required the integration of complex spatial data using a Geographical Information System (GIS) computer software package. Because this process proved to be very challenging and plagued with difficulties, it is described in detail. Although the current study is limited in scope (the state of Kentucky), it is anticipated that the methodology outlined here can be applied to larger regions.

Conceptual Model

The key to manure management is having enough crop acreage to which manure is applied at sufficient agronomic rates. If the capacity of a crop to absorb nutrients is equal to or greater than nutrients supplied by manure, the likelihood of soil nutrient toxicity (or buildup) and the potential to contaminate surface and ground waters is reduced. Most states, including Kentucky, require that manure management plans be filed with state regulators that specify the crops to which manure is applied. It is implicitly assumed in this investigation that manure is applied to meet crop growth needs (i.e., is not being over applied to minimize required acreage). The types of crops that can be grown in an area and crop rotation largely determine the amount of manure that can be applied to a field if following agronomic rates. Hence, information about crop acreage can be used to create a measure of assimilative capacity, the capacity of the environment to absorb or convert livestock manure such that the environment is not harmed.

Following Fleming et al. (1998) and Fleming (2000), assimilative capacity is measured as an index value. Specifically, this index called a suitability index (SI), is the inverse of the product of 1) the percent of cropland that comprises all land in an area (); 2) the percentage of cropland agronomically (or legally) suited for receiving manure (); and 3) the percentage of suitable cropland actually available for receiving manure (; see Equation 1). As it happens, Fleming ignored an important component of assimilative capacity, the percentage of suitable cropland already receiving manure and no longer available (d). Hence, in Equation 1 the parameters and represent the natural absorptive capacity of an area for a given crop rotation and and the remaining absorptive capacity that is under human control.

1.

At this time readily available spatial data sources do not exist for the percentage of suitable cropland already receiving manure and the percentage of suitable cropland actually available for receiving manure. As a consequence and are restricted to values of 1 (Equation 2). These restrictions act to understate SI because only the natural absorptive capacity of an area for a given crop rotation is measured. In reality, as manure is applied to crops, less acreage remains to which additional manure can be applied (available and suitable acreage is fixed within a given region). This fact is reflected in a decreased value of which implies an increased SI. Also, as Fleming et. al. note, many farmers do not want manure on their land, hence will be less than one. Reasons cited for this reluctance include the following: 1) manure is often available for land application at a time when farmers are conducting other field operation; 2) some farmers believe that manure applicators compact their soils and; 3) some do not believe that the nitrogen content of manure is consistent enough for them to reduce their commercial fertilizer applications.

2.

Next the suitability index is linked to swine production cost via the cost of transporting manure to application fields. Fleming et. al. (1998) developed the SI to inflate the distance a producer would have to travel in order to apply swine manure to crops. Specifically, in areas where there is little crop ground or where that crop ground is unsuitable for manure application, the further a producer must travel to deliver manure to crops. In such a case SI is large. The greater is SI, the farther one must travel to deliver manure stocks (increased transportation costs). Alternatively, a smaller SI indicates a greater capacity for the area to absorb animal manure nutrients, hence lower transportation costs.

To illustrate, consider the following example. Fleming et. al. defined required acreage (RA) as the acreage actually needed to manage manure stocks. Unfortunately, RA rarely translates into acreage immediately available at the site where hogs are produced. If the area of interest is 100% suitable crop land, then SI is 1 meaning that RA is immediately available (transportation costs are nearly zero). However, if cropland comprises only 25% of an area and half of the available cropland is not suitable for manure applications, then SI is 1/(0.25*0.5) or 8. This means that the swine producer has to search over 8 acres to find 1 acre needed for manure management. If 1,000 acres are required for manure management in this area (RA), then the swine producer will have to haul manure over an 8,000-acre area at a considerable cost.

Following Fleming (2000) total manure management cost (TMC) is the product of total land cost (for acquiring manure application acreage; TLC), a base charge for transporting manure (BC), and an additional mileage charge (AMC; Equation 3). To simplify the analysis, it is assumed that the crop acreage needed (or required) for manure management is known (this is required acreage or RA). In turn, this fixes the quantity of manure (in gallons) that is being transported to application fields as well as the number of hogs that are being produced. Within the context of this study, these restrictions imply that TLC and BC in Equation 3 are fixed. Specifically, with respect to the parameter TLC, it is assumed that the cost of acquiring RA does not change, only the area over which we must search to find fields to meet RA change (see Fleming et. al., 1998). However, a close examination of Fleming's (2000) work indicates that land acquisition costs (TLC) may also increase as SI increases. These changes in cost are not considered here.

3.

Given the restriction outlined above, changes in land suitability (SI) will impact the total cost of manure management (TMC) only through changes in the additional mileage charge (AMC). Again, larger values of SI imply that swine producers must travel farther to deliver manure stocks. Equation 4 is Fleming et. al.'s (1998) expression for AMC that includes later modifications made by Fleming (2000). In Equation 4 the parameter rA is the unit mileage charge ($/gallon-miles), QH is the amount of liquid manure (in gallons) transported to fields, and is the slope of the unit mileage charge schedule. The parameter Z adjusts cost depending upon whether a return trip is necessary to deliver manure. Specifically, Z is assigned the value of 2 if manure is hauled to crop acreage because a return trip is necessary. If manure is pumped to application fields, then Z is assigned the value of 1 (there is no return trip). In most cases the unit mileage charge (rA) increases with the one-way distance to a field. The parameter is the rate of increase in rA as mileage to application fields increase.

4.

Given this expression for AMC (or TMC), it is now possible to calculate the impact on manure management costs of policies that alter the suitability of manure application areas. Again, in Kentucky, current policy restricts manure applications to crop acreage with slopes up to 12 percent even though agricultural interests argue that liquid swine manure can be safely applied to acreage with slopes up to 18 percent. By making illegal manure applications to crop acreage in excess of 12 percent, this policy essentially defines suitability. Hence, the economic impact of a 12 versus 18 percent slope policy can be measure by measuring changes in the parameter in Equation 4. Again, measures the percentage of cropland agronomically (or legally) suited for receiving manure. Using Equation 5, the change in manure management cost, measured in dollars per gallon of manure applied, for changes in policy that impact the suitability of manure application areas can be determined.

5.

Geographical Analysis

Calculating total manure cost and the change in this cost as a result of a more restrictive manure application policy requires knowledge of and . However, and are spatial parameters in that their value varies based upon their location. These parameters also depend upon the size of the area for which they are defined. Specifically, as the area for which and are calculated increases, and tend to decrease resulting in higher values of SI. Note, however, that this is not always the case. It is possible to construct numerous examples where SI would decrease as the area of focus is increased.

Because and are spatial parameters, it was determined that a computerized Geographic Information System (GIS) was best suited to measure these parameters. The parameter , for example, is measured by calculating the percent of agricultural land within a defined area. Similarly, 12 (Equation 5) is measured by calculating the percent of agricultural land within a defined area that is also less than 12 percent slope. Although GIS is best suited to measure these values, the process of assembling the data to measure and proved to be challenging. Assembling the data required knowledge of basic cartography principles and programming skills using the computer program Arc/Info Version 7.1.1 developed and distributed by Environmental Systems Research Institute (Esri), Inc.

The remainder of this section provides some of the more technical information needed to replicate this work as well as justification, where necessary, for what was done. Initial construction of the necessary spatial data sets was attempted using a vector format. Eventually, the vector format was abandoned in favor of a raster format. Vector data is stored and processed as a collection of arc segments. Raster data, on the other hand, is stored as pixels with individual x-y coordinates. While vectors are excellent at representing houses and roads, they are very processor and storage intensive when representing continuously varying features.

For this analysis, cell size was set to 200 by 200 meters. A cell represents an area to which values representing geographic, agronomic, or other information are assigned. This particular cell size represents a compromise between high resolution and reasonable computer processing time. Specifically, as resolution increases, computational time increases exponentially.

Calculating and required construction of two major databases. Calculating required slope information for the state while land use information was needed to calculate . Note, however, that each data set is unique in terms of its construction. The slope grid for Kentucky was created using United States Geological Survey (USGS) 2-Arc-Second Digital Elevation Models (DEMs) downloaded from the Kentucky Geological Society web site (http://www.uky.edu/KGS/gis/kgs_gis.html). Elevation data for the state is broken into 34 1:100,000 scale quads representing 8 DEMs. Each DEM is approximately 2000 square miles each (see http://rmmcweb.cr.usgs.gov/elevation/2arcinfo.html). Unfortunately, DEMs for the three eastern Kentucky quads were not available. Each DEM requires 1.2 megabits (MB) of storage memory (9.6 MB per quad) so 326.4 MB of memory is needed to store all available DEMs for the state. Once converted to the same geographic datum, the individual quads were joined to form a single grid (or elevation coverage). This grid was then resampled to the desired 200-meter resolution using Arc/Info.

Next the grid feature and slope command in Arc/Info were used to calculate the slope of each cell in the elevation grid. Here, percent slope is defined as the rise of a section of land divided by its run multiplied by 100. Note that Arc/Info is able to calculate both degree slope and percent slope. These are very different concepts that are sometimes confused. The difference between these two measures of slope is clarified in the help files that accompany Arc/Info. Finally, the slope grid created above was used to form two new grids representing area with 0 to 12 percent slope and area with 0 to 18 percent slope. Specifically, for the 12 percent grid, cells where the corresponding slope values is 12 percent or less are assigned the value of 1 and are 0 otherwise. The 18 percent grid is constructed similarly.

Anecdotal evidence suggests that most Kentucky producers are reluctant to transport manure more than 15 miles. For this reason cell values for and (and, eventually, SI and manure management cost) are calculated assuming an area based on a 15-mile radius originating from every cell. Along the state’s boundaries, special procedures were employed to adjust cell values when the surrounding area was less than 707 square miles (452,389 acres). Specifically, a "count grid" was created that the "focalsum" command in Arc/Info uses to count the number of cells within a 15-mile radius of a particular cell that are also within the state of Kentucky. This count grid insures that Arc/Info properly calculates and for cells within 15 miles of the border. Along the northern border of Kentucky, which is defined by the Ohio River, this correction procedure is expected to return reliable results because farmers are unlikely to transport manure across the river (transportation costs are too high). In the southern half of the state, however, lack of a natural barrier suggests that farmers could ship manure to fields in Tennessee. In these areas the correction procedure may not return reliable results. Combined, these processes result in surface maps that are smooth and continuous.

The next step was to create a grid (or coverage) representing land uses suitable for spreading swine manure. USGS Land Use and Land Coverage (LULC) digital data derived from 1:250,000 and 1:100,000 scale maps were selected to bring the land use component into the analysis. This data is scaled similarly as the DEM data. Land in the LULC data set is segregated into one of nine main classes (including agricultural uses) and into one of 37 sub-classes. With respect to agriculture, 4 sub-classes of land use are identified: Croplands and Pastures (LULC code 21); Orchards, Groves, Vineyards, Nurseries, and Ornamental Horticulture Areas (LULC code 22); Confined Feeding Operations (LULC code 23); and Other Agricultural Land (LULC code 24). Because this project is concerned with land that is suitable for manure management, LULC code 21 (Cropland and Pastures) is the focus of this investigation.

Little modification of the LULC data was necessary in order to use this data. Essentially, a 200-meter grid (of cells) was laid over the LULC coverage and each cell was assigned the dominant LULC code. Once completed, the LULC grid is used to calculate , the percentage of total acreage devoted to crops and pasture. Specifically, the focalsum command in Arc/Info is used to iterate across every cell in the grid and, at each cell, to count the number of surrounding cells within a 15-mile radius that hold the value of 21. The total number of cells within the 15-mile radius then divides this sum. The result of this calculation is assigned to the corresponding cell in a new grid (called the alpha grid) that holds the value of for an area with a 15-mile radius. In Figure 1, actual data grid images are used to illustrate creation of the alpha grid from the LULC coverage.

The final step is to calculate , the percent of crop or pasture acreage that is suitable for manure applications, and then the suitability index (SI). Again, 2 values of are calculated: 12, the percent of suitable acreage when manure applications are restricted to acreage with a slope less than 12 percent and 18, the percent of suitable acreage when manure applications are restricted to acreage with a slope less than 18 percent. While the discussion that follows concerns 12, note that 18 is calculated similarly.

The task of calculating 12 starts by laying the 12 percent slope grid over the LULC grid and physically linking the two data sets. Once linked, the focalsum command is used to iterate across every cell in the grid and, at each cell, to count the number of surrounding cells within a 15 mile radius that hold joint values of 1 for slope and 21 for crop type. The total number of cells within the 15-mile radius then divides this sum. The result of this calculation is assigned to the corresponding cell in a new grid (the beta12 grid) that captures the spatial distribution of 12, the percent of land within 15 miles that is pasture or cropland and legally suitable for manure applications. Given the alpha and beta12 grids, a grid for SI12 (suitability indexes given a 12 percent restriction) is calculated by inverting the product of the corresponding cell values for the alpha and beta12 grids (Equation 2).

Results

Using land use and digital elevation data, the computer package ArcInfo is used to calculate spatial suitability indices (SI) for the state of Kentucky. Two maps are pictured in Figure 2. The top map reports spatial indices for the case where liquid swine manure applications are restricted to crop acreage with a slope of 12 percent or less. The bottom map is similar except that applications are restricted to crop acreage with a slope of 18 percent or less. Casual observation indicates that there is little spatial difference in the distribution of SI between the 12 and 18 percent slope maps. Specifically, higher values of SI tend to be located in the same regions of the state regardless our assumption of slope. Note, however, that while the distribution of SI is similar between the two maps, there are differences in magnitude. This issue is addressed later.

With respect to spatial distribution, 25% of the crop-growing regions of the state (the light areas to the west of the dark band in the maps in Figure 2) have suitability indexes of 2 or less (Table 2). Likewise, 53% of the state has a SI less than 3, 69% is less than 4, and 80% of the state has a SI less than 5. Again, a SI of 2 implies that 2 acres are needed to find an acre of cropland on which to spread swine manure. Regions with higher SI values (SI values > 4) are found in Northern Kentucky (the Louisville, Cincinnati, Lexington metropolitan areas), in south central Kentucky (the southern Lincoln Trail area comprised of Casey, Adair, Russell, Pulaski, Cumberland, Clinton, and Wayne counties), and in the Ohio Valley area of west central Kentucky (Hancock, Ohio, Mclean, and Hopkins counties as well as Muhlenberg, Butler, Grayson, and Breckinridge counties). The dark shaded area in southwestern Kentucky identifies a recreational area known as the Land-Between-the-Lakes that is not important to agriculture. These areas with higher SI values are consistent with expectations. Specifically, the northern Kentucky region is the fastest growing area in the state in terms of commerce and industry. As agricultural land is converted for urban uses, there is simply less land available for manure management or other agricultural uses. The south-central region is topographically more diverse (hilly) which limits the availability of suitable acreage (slopes tend to exceed 18 percent slope). The higher SI values in western Kentucky are more difficult to explain. This area does correspond with the western Kentucky coalfield. As a consequence, much of this area has been strip-mined and is currently not available for agricultural purposes (at the least this area is not currently classified as crop or pasture acreage). With continued reclamation of this area, especially areas designated as prime farmland, it is anticipated that more crop acreage will become available, hence reducing SI. However, the extent to which SI is reduced will depend on regulatory changes that currently restrict manure applications on all reclaimed land except prime farmland.

According to Kentucky Agricultural Statistics (1999) for the 1997-1998 crop year, the western Kentucky region discussed above contains 5 of the state’s top ten swine producing counties (Hopkins, Mclean, Breckinridge, Grayson, and Butler). For these counties a higher SI value can have a significant impact in terms of their manure management cost. Table 1 and Figure 3 use Equation 4 to translate SI into monetary terms. The values reported in Table 1 ($ per gallon of liquid manure delivered) and Figure 3 ($ per head finished) do depend upon the crop acreage needed to manage manure stocks at agronomic rates (RA or required acreage) and are based on the following assumptions. Specifically, manure is surface applied by tank wagon to corn, soybeans, wheat, and bermuda grass in rotation at a rate of 30,078.5714 gallons per acre or 1.11 acre-inches annually (Fleming, 2000, Table 2; Thom et. al., 1997). Furthermore, this application rate is based on the nutrients derived from finished hogs (168 pound average weight) who excrete 8,422 gallons of manure per 1,000 pounds of pork produced (Thom et. al., 1997).

For comparison sake, a large producer (32,000 head finished annually) would require 1,500 acres of suitable cropland on which to manage manure stocks. Kentucky Farm Business Management records for 1996 indicate that the average "large" Kentucky pork producer is likely to produce 5,000 to 6,000 head of finished swine annually. These producers will only require 250 acres to manage manure stocks. Table 1 and Figure 3 indicate that the example Kentucky producer in a area with a SI of 4 will pay $0.0015 per gallon of delivered manure or $2.12 a head more than a similar producer in a region where SI is 1. For the example large producer, this difference is $12.59. Other cost differences can be calculated similarly.

Based on this analysis, Kentucky’s larger family-owned swine producers in areas with a higher suitability index value are operating at a cost disadvantage. These higher cost areas represent only 30 % of the state (Table 2), but include parts of 5 top ten swine producing counties in west central Kentucky. However, it is not possible to determine if other cost advantages such as lower feed costs or better access to the market may be offsetting higher manure management costs. If this is not the case then it is reasonable to expect that, over time, this type of swine operation will shift from these west central counties (and other areas with higher index values) to other western Kentucky counties that are not part of the "coalfield."

With respect to large commercial operations the story is much clearer. Better market access and (or) lower cost inputs are unlikely to overcome manure management costs that are as much as $13 per head more than similar operations in areas with a lower suitability index. This significantly higher cost is due to the large quantity of material that must be delivered in an area where crop acreage is relatively more scarce. Currently, large commercial operations such as the one assumed here do not exist in Kentucky. The results of this analysis imply that such companies could potentially reduce their manure management costs by locating in areas with lower SI values. As a consequence, growth of a commercial swine industry, should it occur, would likely occur in western Kentucky counties outside of the coalfield.

The final portion of this analysis concerns the impact on manure management cost of restricting from 18 to 12 percent the slope of crop acreage to which swine manure can be applied. Again, a casual analysis of Figure 2 might lead to the conclusion that there is little spatial difference in the distribution of SI between the 12 and 18 percent slope maps, hence no policy impact. While it is true that the spatial distribution of SI may be similar, at any particular point the SI values do differ and, in some cases, this difference is quite large.

Figure 4 reports differences in Suitability Index (SI) when liquid manure applications are restricted to crop acreage with less than 12 rather than 18 percent slope. For much of the state (67%; Table 2), a more restrictive manure application policy would increase SI by 0.25 or less. However, there are areas where the impact is more significant. Results indicate that a more restrictive application policy will have the greatest impact in the northern, the west central, and south central regions of the state. Specifically, in the northern and west central regions, SI was increased by at most 1 unit while SI was increased by at least 2 units in the south central region. The large change in SI measured in the south central region is due to this region being more mountainous. Here, switching from 12 to 18 percent slope significantly increases the amount of crop acreage available for manure management.

Using Table 3 and Figure 5, where changes in SI are expressed in monetary terms, the economic impact of a more restrictive manure application policy is assessed. Given the assumptions discussed previously, these results show that manure management costs in 85% of the studied area are increased by as much as 28 cents per head as a result of the policy. Yet there are regions of greater impact including west central Kentucky where most of the states’ hogs are produced. Here a 1-unit increase in SI is expected to increase the manure management cost of a large family owned swine producer by $0.0005 per gallon of delivered material or $0.71 per finished head. Similarly, a large commercial operation would see manure management costs increase by $0.003 per gallon or $2.24 per finished head. In the south central region of Kentucky where a more restrictive application policy would increase SI by at least 2 units, the large family operation is expected to pay an additional $1.41 per head.

To calculate the total economic impact on Kentucky swine producers of a more restrictive manure management policy requires knowledge of the size and general location of each producer in the state. Unfortunately, this information is not currently available. However, the results of this investigation do suggest possible regional impacts. Specifically, as a result of the policy, Kentucky’s swine industry would be expected to minimize cost and "migrate" into western counties outside of the coalfield. It is also note worthy that the regions where manure management is relatively more expensive as a result of higher SI values (compare Figures 3 and 5). In either case, there is incentive for the industry to relocate (or locate) in western Kentucky. The combined effect is for this migration to occur more rapidly.

Conclusions

To capture scale economies, swine facilities continue to expand in size and larger concentrations of animals give rise to larger concentrations of manure. If sufficient crop acreage is available in the vicinity of the production facility and manure nutrients are applied to crops at agronomic rates, then minimum environmental damage is expected to result from swine production. In short, the environmental impact of swine production, in terms of changes in surface and ground water quality, depends upon the assimilative capacity of the region.

Assimilative capacity is largely defined by regulations that restrict swine manure applications to narrowly defined areas. For example, Kentucky producers are required to apply swine manure to (crop or pasture) land following a certified nutrient management plan filed with the state. The nutrient plan, based on the amount of nitrogen in manure and crop nitrogen requirement, is to detail the location and types of "crops" to which manure is to be applied. Furthermore, swine producers are restricted from applying swine manure to land with a slope greater than 12 percent or land that has less than 18 inches of soil to bedrock. The first part of this regulation restricts total availability of manure applicable acreage. The second part defines what portion of total available acreage is actually suitable for manure applications.

It is these concepts of availability and suitability that give rise to the definition of the suitability index (SI) used in this investigation. The question addressed here concerns the state’s restriction on manure applications to land with a slope greater than 12 percent. Agricultural interests view an 18 percent restriction as sufficient to avoid manure runoff into surface waters. More importantly, they believe that a 12 percent restriction will eliminate a significant amount of acreage otherwise suitable for manure management resulting in higher manure management costs and increased concentration of the industry in flatter regions of the state.

The results of this study may support these claims. Restricting applications to slopes less than 12 rather than 18 percent increased manure management cost by as much as 28 cents per head across 85% of the state’s agricultural area. This result applies to the "typical" Kentucky producers who markets 5,000-finished head annually. For very large firms (30,000 head finished annually), manure management costs were increased by as much as $2.25 per head. In periods of low swine prices, this 28 cent increase in production cost could have a significant negative impact on enterprise profitability. If this is the case, than a significant portion of Kentucky’s swine producers could exit the industry as a result of this policy. Furthermore, this cost may be sufficiently large as to act as an economic disincentive to larger firms looking to locate in Kentucky. This finding is especially true of very large "integrated" firms.

Perhaps more importantly, the results of this study indicate that a more restrictive slope policy is likely to impact a region of significant pork production in Kentucky. Specifically, results indicate that producers in 5 top ten Kentucky swine producing counties pay higher manure management costs because of factors that restrict the availability and suitability of agricultural acreage in their area. This alone is sufficient incentive for swine producers located in these counties to migrate to nearby, but less costly areas. Yet, these are also the counties more severely impacted by the 12 percent slope policy. Adding the cost of the 12 percent slope policy to manure management costs that are already relatively high is expected to accelerate movement of firms out of these counties. Essentially, this "migration" will occur as firms in higher cost counties cease business and new firms locate in less expensive areas. Hence, the results of this study support the claim by industry that swine production could become more concentrated in counties outside of the coalfield and especially in extreme western Kentucky (the Jackson Purchase region).

The conclusions drawn in this investigation apply to Kentucky. However, the methodology presented here is easily applied to other regions of the United States. The scale of this methodology is limited only by the availability of slope and LULC data and the processing speed of one’s computer. This model can also be improved upon in a number of ways. Future research will attempt to measure the parameters d, the percentage of suitable cropland already receiving manure, and ?, the percentage of suitable cropland actually available for receiving manure. These parameters were set to 1 in this investigation resulting in understated SI values. Specifically, it is hoped that improvements in remote sensing technology will allow for the identification of agricultural acreage receiving manure. Currently, obtaining this data on a large scale is cost prohibitive.

Finally, the conclusions drawn here are based on cost minimization. In fact, the 12 percent slope restriction can be ruled inefficient only if the costs of the policy exceed the benefits. Currently, this investigation only addresses half of the equation. Yet, because of the cost of obtaining reliable benefit information, this is not an unreasonable approach. Future work includes measuring the environmental and other economic benefits associated with a 12 percent slope restriction.

 

References:

Fleming, R.A., "The Economic Impact of Setback Requirements on Land Application of Manure." Land Economics. Forthcoming February 2000.

Fleming, R.A., B.A. Babcock, and E. Wang, "Resource or Waste? The Economics of Swine Manure Storage and Management." Review of Agricultural Economics, 20(Spring/Summer 1998):96-113.

Kentucky Agricultural Statistics Service (KASS), "Kentucky Agricultural Statistics: 1997-1998," Kentucky Department of Agriculture, Frankfort, Kentucky. 1999.

Kentucky Farm Business Management Program (KFBM), "The Kentucky Farm Business Management Program 1997 Annual Summary," Agricultural Economics-Extension Series, no. 98-03, University of Kentucky Cooperative Extension Service and Agricultural Experiment Station, Lexington, KY. 1998.

Thom, W.O., and Associates. "Several Issues Related to Swine Waste Application to Land, Cropping and Utilization." Department of Agronomy, Report to the Cabinet for Natural Resources and Environmental Protection, University of Kentucky, Lexington, KY. 1997.

Table 1. The theoretic additional mileage charges ($/gallon) for liquid manure management by zone in Kentucky derived from Equation 4.
 

Zonal Value of SI from Figure 2

RA

1

4

8

12

16

10

0.0000

0.0001

0.0002

0.0002

0.0003

100

0.0002

0.0008

0.0016

0.0024

0.0032

250

0.0005

0.0020

0.0040

0.0060

0.0080

500

0.0010

0.0040

0.0080

0.0119

0.0159

1,000

0.0020

0.0080

0.0159

0.0239

0.0318

1,500

0.0030

0.0119

0.0239

0.0358

0.0477

2,000

0.0040

0.0159

0.0318

0.0477

0.0637

Note: Z is 2 and is 0.002 (Fleming, 2000; Lorimor, 1996).

To convert RA to Head, multiply RA by 21.2585.

To calculate impact in $/Ac, multiply table value by 30,078.5714.

To calculate impact in $/Head of finished hogs, multiply table value by 1,414.896.

To calculate total cost of the policy ($) multiply table value by 30,078.5714*RA.

These values assume that manure is surface applied by tank wagon to corn, soybeans, wheat, and bermuda grass in rotation at a rate of 30,078.5714 gallons per acre or 1.11 acre-inch annually (Fleming, 2000, Table 2; Thom et. al., 1997). This application rate is also based on the nutrients derived from finished hogs (168 pound average weight) who excrete 8,422 gallons of manure per 1,000 pounds of pork produced (Thom et. al., 1997).

 

 

Table 2. Percent of the non-mountainous, agricultural portion of Kentucky classified by legend category in Figures 1 and 3.
Derived Suitability Index for Liquid manure application to Kentucky crop acreage with slopes of 12 and 18 percent (Maps 1 and 2 in Figure 3). Difference in Suitability Index when liquid manure applications are restricted to crop acreage with less than 12 rather than 18 percent slope (Figure 1).

Index Value

Percent of State

Index Value

Percent of State

 

12 % Slope

18 % Slope

   

1 - 2

25.2

28.4

0.00 – 0.25

66.9

2 - 3

28.2

28.8

0.25 – 0.50

18.4

3 - 4

15.6

14.9

0.50 – 0.75

8.6

4 - 5

10.4

9.6

0.75 – 1.00

2.2

5 - 6

7.3

6.4

1.00 – 1.25

1.6

6 - 7

4.2

3.3

1.25 – 1.50

1.1

7 - 8

2.6

2.3

1.50 – 1.75

0.7

8 - 9

1.5

1.4

1.75 – 2.00

0.5

9 - 10

1.1

1.2

   

10 - 11

1.1

0.9

   

11 - 12

0.9

0.8

   

12 - 13

0.6

0.7

   

13 - 14

0.6

0.6

   

14 - 15

0.6

0.6

   
         

 

 

Table 3. The added cost of manure management ($/gallon) when liquid manure applications are restricted to crop acreage with less than 12 rather than 18 percent slope derived using Equation 5.
 

Difference in Suitability Index

RA

0.25

0.50

0.75

1.0

1.25

1.5

1.75

2.0

10

0.0000

0.0000

0.0000

0.0000

0.0000

0.0000

0.0000

0.0000

100

0.0000

0.0001

0.0001

0.0002

0.0002

0.0003

0.0003

0.0004

250

0.0001

0.0002

0.0004

0.0005

0.0006

0.0007

0.0009

0.0010

500

0.0002

0.0005

0.0007

0.0010

0.0012

0.0015

0.0017

0.0020

1,000

0.0005

0.0010

0.0015

0.0020

0.0025

0.0030

0.0035

0.0040

1,500

0.0007

0.0015

0.0022

0.0030

0.0037

0.0045

0.0052

0.0060

2,000

0.0010

0.0020

0.0030

0.0040

0.0050

0.0060

0.0070

0.0080

Note: Z is 2 and is 0.002 (Fleming, 2000; Lorimor, 1996).

To convert RA to Head, multiply RA by 21.2585.

To calculate impact in $/Ac, multiply table value by 30,078.5714.

To calculate impact in $/Head of finished hogs, multiply table value by 1,414.896.

To calculate total cost of the policy ($) multiply table value by 30,078.5714*RA.

These values assume that manure is surface applied by tank wagon to corn, soybeans, wheat, and bermuda grass in rotation at a rate of 30,078.5714 gallons per acre or 1.11 acre-inch annually (Fleming, 2000, Table 2; Thom et. al., 1997). This application rate is also based on the nutrients derived from finished hogs (168 pound average weight) who excrete 8,422 gallons of manure per 1,000 pounds of pork produced (Thom et. al., 1997).

Figure 1. Graphical presentation of procedures used to create the alpha grid.

 

The analysis for this study was conducted using the software package Arc/Info version 7.1.1 by Esri, Inc. After some attempts at doing this analysis in vector format it was decided that raster analysis was a more appropriate approach. (Raster data is stored as individual cells or pixels, while vector data is stored as a series of arc segments or lines.)

The cell size for the raster analysis was set at 200 meters, which was a compromise between high resolution and reasonable computer processing time. Analysis areas are defined using a 15-mile radius from any given cell because most producers are reluctant to transport manure more than 15 miles. Doing this analysis for each cell in the grid will result in a map that shows suitably for any given point in the state.

Figure 2. Derived Suitability Indices for liquid manure applications to Kentucky crop acreage with slopes of 12 (top map) and 18 percent (bottom map).

 

Figure 3. Manure management cost ($/head finished) paid by 5,000 and 32,000 head finishing operations assuming a 12 percent slope restriction on manure applications.

Figure 4. Difference in Suitability Index when liquid manure applications are restricted to crop acreage with less than 12 rather than 18 percent slope.

Figure 5. Increase in manure management costs ($/head finished) paid by 5,000 and 32,000 head finishing operations when liquid manure applications are restricted to crop acreage with less than 12 rather than 18 percent slope.