DELINEATING AGRICULTURE IN THE NEUSE RIVER BASIN

Transcription

1 DELINEATING AGRICULTURE IN THE NEUSE RIVER BASIN For Final Report for the Sampling Analysis: Delineating Agriculture in the Neuse River Basin Submitted October 5, 2011 to the NC Department of Environment and Natural Resources (NCDENR), Division of Water Quality Funding Period 10/01/ /30/2011 Principal Investigator: Deanna L. Osmond NC State University Department of Soil Science with Kathy Neas (Cooperator) U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS)

2 ACKNOWLEDGMENTS This project was funded under an EPA Section 319 Grant. Rich Gannon with the NC DENR - Division of Water Quality was a cooperator on this grant. A special thanks Steve Pratt (Understanding Systems, Inc) for determining map units and Sheri Cahill, Josh Edgell, and others for working on parts of the report. Last, but most importantly, this project could not have been completed without the field enumerators who collected the data and the producers and landowners, who were willing to participate in the survey. Without all these people, and the funding provided through USEPA 319 as a pass through to NCDENR, this project would not have been possible.

3 TABLE OF CONTENTS EXECUTIVE SUMMARY... 1 INTRODUCTION... 3 PURPOSE AND GOALS... 3 DELIVERABLES... 3 METHODOLOGY... 4 Area Frame Sampling... 5 Determining the Census Blocks to Map... 5 Determining the Sampling Segments... 7 Enumeration of the Sampling Segments... 7 Data Processing... 8 OUTPUTS AND RESULTS... 9 Agronomic and Conservation Practices... 9 Land Use... 9 Drainage Directions Cover Crops Conservation Tillage Water Control Structures Riparian Buffers Nitrogen, Phosphorus, and Potassium Rates Soil Test P and P Fertilization Slope, Soil Loss, and Receiving Slopes Agricultural Demographics Fertilizer Use Information Animal Agriculture Neuse River Basin Special Situations OUTCOMES AND CONCLUSIONS BUDGET REFERENCES APPENDIX.. 52

4 List of Figures and Tables Figure 1. Selected segments in the Neuse River Basin... 6 Table 1. Agricultural land use by county... 9 Table 2. Number of fields (first number) and number of acres (number in parenthesis) that were not enumerated as the land use was other than agriculture. Number in parenthesis is the number of acres Table 3. Drainage directions by county minimum, maximum and mean Table 4. Acres and percentage of cover crops by species and by county Table 5. Percentage and acreage of conservation tillage by county Table 6. Number of acres and percentage of this area buffered and not buffered by county Table 7. Number of fields by county with tree/shrub buffer, and minimum, maximum and mean buffer width Table 8. Number of fields with vegetative buffers and minimum, maximum and mean vegetative buffer widths Table 9. Total agricultural acres affected by tree/shrub buffers, vegetative buffers, and tree/shrub + vegetative buffers Table 10. Total agricultural acres affected by in-stream basins or ponds Table 11a. Commercial fertilizer nitrogen rates Table 11b. Commercial fertilizer phosphorus rates Table 11c. Commercial fertilizer potassium rates Table 12a. Applied organic nitrogen (2008) Table 12b. Applied organic phosphorus (2008) Table 13. Number of fields of a crop fertilized by a producer (first number) and the number of different fertilizer application regimes by crop (numbers following the colon and separated by a, Table 14. Mean and weighted mean soil test P-index by county Table 15. Phosphorus fertilization rates for soils needing phosphorus fertilizer (STP > 60) and soils testing low and medium STP (< 60) Table 16. Non-fertilized spring and summer crops by acres and fields Table 17. Minimum, maximum and weighted means for field slope and soil erosion by county Table 18. Number of field acres* with associated receiving slopes for up to three drainage directions per field and the mean receiving length (feet) by county Table 19. Percent field acres owned or rented by county Table 20. Organizations or individuals who make fertilizer recommendations when a nutrient management plan is not used Table 21. Organizations or individuals who write nutrient management plans Table 22. Organizations or individuals who apply nutrients Table 23. Average head, average number of days, and stocking rate of cattle and horses Table 23. Average head, average number of days, and stocking rate of goats and sheep Table 25. Other animal types and numbers by county

5 EXECUTIVE SUMMARY In 2000 we undertook an agricultural survey of the Neuse River Basin to obtain data that would help inform the Division of Water Quality and the Neuse Basin Oversight Committee (BOC), which was charged with determining a baseline for nitrogen (N) losses from At that time, the Nitrogen Loss Estimation Worksheet (NLEW), a tracking and reporting field-scale tool, was developed, to calculate the N losses and change in N losses due to best management practice (BMP) implementation (Osmond et al., 2001). We developed a statistically defensible sampling scheme to determine a field-scale baseline. Now that the Neuse Rules have been in effect for 15 years, the intent of this survey was to determine current agricultural conditions and compare data collected from the 2000 Neuse Agricultural Survey. Using a valid statistical sampling technique, random census blocks were selected. The number of maps selected per county in the Neuse basin was based on how much of the county was within the river basin boundaries, as well as the amount of agriculture. Counties sampled consisted of Craven, Durham, Edgecombe, Franklin, Granville, Green, Johnston, Jones, Lenoir, Nash, Orange, Pamlico, Person, Pitt, Wake, Wayne, and Wilson. Enumerators employed by the North Carolina Department of Agriculture and Consumer Service (NCDA&CS), Division of Statistics administered the survey. The data set consisted of 3,954 distinct fields selected and 3,814 fields enumerated, of which 3,355 fields were actively farmed. This was the same data set that was used in We collected information on a wide variety of agricultural characteristics, including number of acres in development, wildlife, and CREP/CRP. Other data collected consisted of county, field size (ac), current crop, fertilizer applications (amount and type), tillage type, cover crop use, presence of different types of buffers, buffer widths, acreage affected by the buffers, presence of water control structures, acres affected by the water control structure, field slope, receiving slope length, and presence of other BMPs (sediment basin or pond). In Durham, Franklin, Granville, Orange, Person, and Wake, slope length was also determined in order to calculate soil loss. In all other counties, soil loss was based on table values, determined by USDA-NRCS, using physiographic region and cropping system. Soil test P was collected based on prior soil tests or current soil tests taken by the enumerators with the permission of the landowners. Finally, we collected producer nutrient management planning information. The survey instrument is attached at the end of this report (Appendix 3). After the information was collected, the data were then transformed in order to report on them. Of the agricultural land enumerated, 1,525 acres had moved out of agriculture into developed lands and and almost equal amount of land (1,249 acres) was idle. The majority of the land was still in agricultural use. The predominant agricultural land use in the Neuse Basin is production of row and some vegetable crops (> 95%). Pasture and hay lands predominate in Durham and Orange counties. Most counties had low use of non-fertilized winter cover crops (wheat, rye, oats, or triticale) 0.3 to 13.5% of the agricultural lands, with an average of 1% cover crop usage. Conservation tillage was used in all counties, with an average use of 54% and a range from 17 to 88%. 1

6 Only 20 fields with water control structures were found and about half of the structures were clearly managed. All structures were located in Craven, Jones, or Pamlico counties. The percent of agricultural acres affected by buffers ranged from a high in Orange County (83%) to a low in Pamlico (36%). In general, 74% of the agricultural acres are now currently buffered by either a tree, vegetative, or tree and vegetative buffer. More agricultural acres are protected by tree buffers (16, 245 acres), relative to vegetative buffers (8,832 acres) or tree+vegetative buffers (5,438 acres). Although buffer width was measured as little as 0.5 ft, the average width of a tree buffer was 200 ft and 50 ft for a vegetative buffer. On average, therefore, buffer width meets the Neuse Nutrient Rule requirement. Ponds and in-stream wetlands are considered to have some benefit for reducing P. There are approximately 2,500 acres affected by ponds and 1,500 acres affected by in-stream wetlands. Obviously these two practices are fairly insignificant for reducing P runoff. Almost all nutrients were from commercial fertilizer. Animal waste was applied to 57 fields out of 3,248, which represented 1.8% of all the agricultural fields to which nutrients were applied; nutrient rates were not excessive. In many counties for many crops, N fertilizer rates were below the expected rates based on realistic yield expectations. Some crops such as pasture, soybeans, peanuts, and cover crops are rarely fertilized. The majority of farmers use the same fertilizer plan with a particular crop, regardless of soil test recommendations or differences in yield goal. Mostly, however, this did not translate into excess fertilization of crops. Average soil test phosphorus (P) levels were very high in 12 counties and high in five counties. Lenoir County had the highest soil test P with a P index of 190, whereas Durham County just barely registered high (53). Despite high soil test P in most counties, except for soybean and pasture acres, farmers are still using around 40 lb P 2 O 5 ac -1. Research indicates that starter P is not necessary for mineral soils when soil test is high or greater (Cahill et al., 2010). Soil erosion was modest, ranging from an average of about < 1 t ac -1 to approximately 7.5 t ac -1, with an average of 3.05 t ac -1. Coastal Plain had higher soil erosion rates because these values were precalculated based on cropping system, coastal plain physiographic region and soil type; these rates most certainly overstate the actual erosion. Calculated erosion rates were much lower. These data suggest that soil erosion is well controlled in the Neuse River Basin either due to the cropping system, tillage system, topography or a combination of factors. Slope ranges were 0 to about 5.5 percent, with slopes increasing in the piedmont physiographic region. Average receiving slopes were feet; these results suggest that there is limited capacity of receiving slopes to slow soil erosion, thus reducing P. However, with low erosion due to the often flat topography of the coastal plain soils, the importance of receiving slope width is not so important. Animal agriculture is not intensive in this river basin. Cattle are the predominant livestock and there are some horses, sheep, goats, and miscellaneous livestock (chickens, llams, donkeys, etc). 2

7 Demographic information indicates that agriculture is the primary livelihood of most of the farmers to whom we spoke (86%). This is very different than in the Jordan Lake Watershed where only 50% of the agricultural landowners derive their primary income from agriculture. Most (62%) of the farmers had no nutrient management plan; fertilizer recommendations were made mostly by the farmers themselves (60%) or fertilizer dealers (20%). When producers did have fertilizer plans, 46% of the plans were written by the farmers, 21% by fertilizer dealers, 14% by NRCS, and 14% by agricultural consultants. In summary, when all the data are combined, it appears that producers in the Neuse River Basin are minimizing environmental impact of nutrient and soil losses from agricultural fields. Best management practices are being used, including buffers, water control structures, cover crops, and conservation tillage. Erosion is low and nutrient inputs generally are below recommended levels. The only area where we believe producers could improve management is by following soil test reports and reducing P fertilization. INTRODUCTION Under the Neuse Rules, the Neuse Basin Oversight Committee (BOC) is charged with determining a baseline for N losses from To calculate the N losses and change in N losses due to best management practice (BMP) implementation, a tracking and reporting fieldscale tool was developed, Nitrogen Loss Estimation Worksheet (NLEW), to accommodate this task (Osmond et al., 2001). Under the Neuse Rules, N-reduction plans could be at the subwatershed level, county level, or any other arrangement that the stakeholders chose. Stakeholders chose to account for N losses at the county level. There are 21 counties in the Neuse Basin, but several of these counties, such as Duplin and Sampson, have inconsequential amounts of land within the basin. PURPOSE AND GOALS The goal of this project is to obtain reliable information on agricultural practices by selecting randomly valid fields to determine if improvements can be made in agricultural practices to protect water quality. It will also allow us to compare current practices with practices used eight years ago since we did a survey in 2000 (Osmond et al., 2000). Much of the information collected in this survey can be compared with similar information collected in the 2000 survey, although we have expanded and refined the survey since Comparing data will give an idea of what agricultural changes have occurred. DELIVERABLES 1) Remake maps Orthoquod maps were printed with the selected area outlined. Some maps required further segmentation of the area. Segmentation was conducted by hand. Accompanying soil maps were printed and all maps were laminated. 2) Train enumerators This was accomplished prior to the survey and many of the numerators had been involved in previous sampling efforts 3) Collect field data Field survey was administered to producers. Information includes cropping and fertilizer history. Fields were surveyed for slope length (Granville and Franklin 3

8 county only, slope, receiving slope length, BMPs, and soil samples will be taken when the operator gave permission. Soil test P results will be provided by NCDAC&S. Information was collected on 3,814 sampling units within the Neuse River Basin. 4) QA/QC field data Each field form was reviewed by the enumerator supervisor, Kathy Neas (NCDA&CS) and Deanna Osmond 5) Develop statistics 6) Survey data was entered into a SAS database and analyzed by county. Once the data were contained available, they were reviewed to ensure their accuracy and that there were no miscodes or outliers. There were over 20 pieces of information entered for each field. We determined crop acreage, fertilizer rates for crops, soil series, appropriate N rates, current level of BMP use, % of agricultural land buffered, soil test P status of the soils, etc. 7) Run statistics Survey data was analyzed by county and the distinct information piece (e.g. crop, nutrient application rates, conservation tillage, etc. The data analysis was interpreted within the final report 8) Quarterly reports All quarterly reports were submitted. 9) Final written report This is the final report. 10) Final oral report We will be presenting a final oral report for the Jordan Lake Watershed Oversight Committee. METHODOLOGY In order to obtain statistically defensible data to meet the two objectives, we have done the following: 1) Determine the sample units through area frame sampling, which is a proven and defensible sampling technique. It is well tested and is used by USDA-NASS and others who need data on agricultural fields. From judgments of field-to-field variation in N runoff and of the number of fields to put in each sampled area, a sample size of 594 areas was deemed adequate to give a sampling CV (coefficient of variation) of 4%. These sampling areas were randomly selected and and maps of these areas were printed with the census block outlined and road names printed on the map. Census blocks were then segmented by hand on the map and selected randomly. All fields within the selected segment were sampled and represented from one to over 30 fields. 2) Conducting the survey by first designing and pretested instrument and then collecting the data through the North Carolina Department of Agriculture and Consumer Services under the supervision of USDA National Agricultural Statistical Service (NASS) enumerators. The survey was used to collect relevant information on all agricultural fields within the selected sample segment. 3) The data were then analyzed by: County Crop 4

9 Crop acres % Crop acres N fertilization rates (by crop) P fertilization rates (by crop) K fertilization rates (by crop) BMPs (by conservation practice and acres) Cover crops Conservation tillage Number of receiving slopes Soil test P Soil loss Average slope Crops and number of fields with High and Very High Soil Test P Crops and number of fields with Low and Medium Soil Test P Livestock type Livestock stocking rates Nutrient management characteristics Producer demographics Area Frame Sampling Determining the Census Blocks to Map In an area frame sample, the collection of N sampling units is determined clerically and then selected randomly (Monroe and Finkner, 1959). Data acquisition for frame construction is the first step in the process. Tiger data were obtained from the U. S. Census Bureau for each county in the Neuse River Basin. The census blocks were then extracted from the Tiger files and merged into a single consistent data table. Census blocks were used to define the areas from which samples would be randomly accessed. Efforts were taken to ensure that data were not resorted in order to maintain the data in its serpentine order as created by the Census Bureau. Once that data was sorted, a rural filter was applied to the data. For a census block to remain on the list, it had to have an area of 10 acres or more and had to contain more acres than persons to be considered for sampling. Then the Neuse River Basin filter was applied. For census blocks to remain on the frame, only census blocks that were entirely or to some extent within the Neuse basin were used. Each of the listed census blocks had a specific acreage associated with it. Listed census blocks then had their areas (in acres) accumulated. For all valid census blocks, the accumulated area of the census block equaled the area of all proceeding blocks plus the area of that block. A convenient sample unit size was then selected. This is an iterative step where trial sample sizes can be experimented with to get reasonable sample unit sizes. For the purposes of this survey, the sample size was determined to be 300 acres. From this, a provisional total population size (N) was calculated (N= total area / sample size). The total population size (N) is then readjusted to a convenient integer that must be divisible by 5 to allow for the five replicate subsamples. 5

10 A census block could itself become a sampling unit if the area of the census block was around 300 acres. If the census block area was less than 300, it may be combined with the next or previous census block or blocks to make the count unit, which is the technical term to describe the census block, or blocks, that contains the sampling units. The area sampling calculations with cumulative areas and cumulative sampling units define all of these units (Finkner and Monroe). To randomly select the 600 sampling units, a set of random number seeds were determined for each of the five subsamples from a random number generator and then applied to the cumulative sampling units and those sampling units that were hit became the areas to be sampled. Sample selections for the Neuse area sample have been made in 5 replicate subsamples, each covering all counties in the watershed and each consisting of 120 sampling units for a total of 600 sampling units (Fig. 1). Each selected cumulative sampling unit that qualified was marked for the plotting of its containing count unit. Once these census blocks were determined, plots were batched for printing. The count units were outlined on 1993 land cover digital orthographic quarter quadrangles (DOQQ). The census locations o f the count unit was plotted as an aerial view outlined in blue with its associated assigned number of sampling units. The apparent number of fields in samples selected per county matched very closely the different number of soils found in the counties. For example, there are more soil series in Wake County than any other county in the Neuse and there was also a large number of sampling units selected for sampling in Wake County. Soil maps delineating soil type for the sampling unit were also printed. Figure 1. Selected segments in the Neuse River Basin 6

11 Determining the Sampling Segments The selected census blocks count unit was segmented into the number of assigned sampling units (ASUs). The ASU dictates the number of segments into which the count unit should be divided. The cumulative sampling units was calculated as the Cumulative_Acres/(Total_Acres/Adjusted_N ). The ASU was calculated as (cumulative sampling unit)x (cumulative sampling unit) x-1, where x - 1 = the preceding cumulative sample unit of x. The ASUs are numbers of potential sampling units and their boundaries must allocate all fields in the census block count unit to one and only one segment. Natural boundaries, such as roads, streams and property lines, are useful boundaries. Imaginary boundaries, such as lines through the middle of woods, are acceptable and sometimes necessary but less useful than natural boundaries. Imaginary boundaries may also be extensions of roads or point-to-point lines or similar ones, so long as the enumerator will have an objective basis for deciding whether a field is in or out of a segment. The ASU number was designated on the maps. When there were two to four ASU numbers, the boundaries were all delineated in one pass. During segmentation, we tried to ensure that the amount of cultivated land (land in fields) was about equal over the segments. However, since field distribution was generally irregular, especially in heavily forested areas, this was not always possible. With five or more ASUs, the count units were divided into two, three or four parts before drawing in all segment boundaries. Segments were numbered and then selected from a random number table. The selected segment was outlined in red. Using this method, 3355 distinct fields were selected. Enumeration of the Sampling Segments Enumerators were trained by NC State and NCDA&CS personnel before they collected any of the information. This one-day training involved both classroom discussion of the sampling strategy and survey instrument, as well as field exercises. Training books were developed for the enumerators and used during the training session (Appendix 1). These books could also be referred to during the actual survey. The booklet included a wide range of information ranging from the reason the survey was being performed to pictures of buffers and controlled drainage. The Neuse Rules, BMPs and sample surveys were explained to the enumerators. During the remainder of the training, the enumerators had hands-on field training to recognize the different types of BMPs and to determine the area affected by them. The data survey instrument allowed collection of the following information: county, field size (ac), previous crop, current crop, fertilizer applications for previous crop (amount and type), fertilizer applications for current crop (amount and type), tillage type, cover crop use, presence of different types of buffers, buffer widths, acreage affected by the buffers, presence of water control structures, acres affected by the water control structure, other conservation practices, soil erosion, soil slope (in applicable counties), soil test P, number of fields with different soil test P levels, number of drainage directions, livestock types, livestock numbers, livestock stocking rate, nutrient management demographic information, and some producer demographic information. The survey instrument is attached at the end of this report (Appendix 3). 7

12 Enumerators visited all segments to collect the necessary information. The agricultural community was extremely helpful with this survey, in that we only had two individuals decline to participate. All fields within the selected segment were enumerated if they were currently agricultural lands, including idle fields. If there were no fields within the segment, the enumerator made note of this, how the field was being used and continued with the survey. This was especially important since the land coverage data that we were using was from Each field survey was reviewed by three individuals: the enumerator s supervisor, an employee of NCDA&CS and the principle investigator of the project. Any potential irregularities discovered in the review were addressed with the enumerator to explain or revisit the sample site. The data set consisted of 3,355 records, each record representing a field and 37,212 acres. Soil maps were placed under the DOQQs in order to determine the predominant soil series of the field. Once the quality of each survey was assured, all data was entered into a SAS database (SAS, 1985). Data Processing It took considerable effort and time to transform the data into a useful format. We had to separate fertilizer applications into previous crop and current crop. To determine the N amount per application for each record, we had to first determine the amount of N applied at each application. We used fertilize rate, N analysis of the nutrient material, and material type (e.g. animal waste, liquid fertilizer, pounds fertilizer, or pounds elemental N) to calculate the amount of N fertilizer applied. For crops with multiple applications of N, we added each N addition to determine the total N applied to each crop. Sometimes nutrients were applied only once, but in some instances, there were five applications of nutrients over the course of a growing season. When a winter cereal crop was grown in 2008, and if it was fertilized, we considered the crop to be produced in the next year (in this case 2009), because most of the fertilizer is applied in the proceeding calendar year to when the crop is planted. In some fields two crops were produced for a calendar year, and so the record was split for each crop. The cover crop and tillage data collected were determined to be unreliable. For example, sometimes there was more strip-tillage and no-till acres in a county than there were acres surveyed. This information was discarded from the data set. Rather than determining cover crop information directly from the survey instrument, we assumed a cover crop was planted if the 2008 crop was wheat, oats, rye, or triticale and it had not been fertilized with N. Numerous transformations had to be made with the BMP data in order to characterize the different buffer types and the acreage that they affected. Vegetation characteristics and widths determined the buffer type (20 foot tree/shrub buffer, 30 foot vegetative buffer, 50 foot buffer 30 feet trees, 20 feet vegetation). Buffer type was defined to meet the buffer criteria for the Neuse Rules. To accommodate different slope directions, the survey instrument allowed for three separate water flow directions per field, and thus three different types of possible buffers and/or ditch systems. If slope and buffer type and width or controlled drainage systems of two or more directions were the same, then they were added into one BMP type for that field. 8

13 OUTPUTS AND RESULTS Agronomic and Conservation Practices Land Use All fields were visited to determine land use. Most land was still in agriculture (3,355 fields) as opposed to 459 fields that had other uses. Owners of 53 fields refused to participate in the survey. In all, 3,355 agricultural fields were enumerated representing 37,212 acres. The average field size ranged from less than 1acre to 150 acres with a mean of 11.4 acres per field and a standard deviation of 12.5 acres. The type of agriculture in the Neuse River Basin is more much intensive than that of the Jordan Lake Watershed (Osmond and Neas, 2008), where much of the agricultural lands are pasture or hay. Most counties except Durham, Franklin Granville, Orange, Person, and Wake had greater than 90% of agricultural lands as row crop production. However, soybeans represented a very high proportion of most cropland (75%-32%) when hay and pasture were not significant. Not surprisingly, hay and pasture production occurred in piedmont counties where rolling topography, climate and soils often make row crop production difficult. Counties that are part of the Falls Lake watershed (Durham, Orange, and Person) have relatively high pasture and hay land use. (Most of Wake County that was enumerated falls outside the boundary of the Falls Lake Watershed). The large amount of pasture/hay or soybeans has implications because these crops are either not fertilized or minimally fertilized. Table 1. Agricultural land use by county County % soybeans % pasture % other crops County % soybeans 9 % pasture or hay % other crops or hay Craven Nash Durham Orange Edgecombe Pamlico Franklin Person Granville Pitt Greene Wake Johnston Wayne Jones Wilson Lenoir The percent pasture of hay/pasture was stable in most counties over the past 8 years; increase more than 5% was noticed in Craven (0 to 6%), Durham (62 to 74%), and Wake (21-27%). Decreases of more than 5% pasture/hay were noticed in Granville (63 to 42%) and Lenoir (8 to 5%). We have listed the uses of fields that were not in use for agricultural production (Table 2). The first number is the number of fields and the second number is the acreage involved. For example, in Craven County 11 fields were found to currently be in trees or shrub (waste) and these 11 fields represented acres. The largest number of acres moved from agriculture to development (1,525.2 ac) followed by idle acres (1,249.6 ac). Many of the idle fields were

14 found in the upper part of the basin in the Piedmont region in the Neuse Basin. Other transformation of agricultural fields were in to miscellaneous uses, followed by wildlife plantings, CRP/CREP, hunting and wetland conversion, but the loss of acres to these uses was small (~ 200 ac). 10

15 Table 2. Number of fields (first number) and number of acres (number in parenthesis) that were not enumerated as the land use was other than agriculture. Number in parenthesis is the number of acres. Woods/ Game Ag to Wildlife CRP/ County Waste Management Development Idle Planting Hunting CREP Craven 11 (176.8) 2 (16.0) 10 (93.0) 4 (49.0) Wetland Idle to Agriculture Durham 7 (34.9) 9 (357.0) 9 (38.6) 9 (52.5) Edgecombe 1 (1.5) 1 (8.0) Franklin 12 (136.0) 9 (86.0) 3 Miscellaneous Granville 26 (71.0) 26 (97.0) 3 (52.0) 1 (7.0) 3 (10.0) 1 (1.0) 6 2 (12.0) Greene 3 (9.0) 1 (12.0) 1 (18.0) 1 (1.5) 2 Johnston 10 (56.1) 27 (232.5) 53 (305.1) 1 (26.0) 2 (29.4) 32 4 (25.0) Jones 2 (20.0) 4 (30.3) 1 (5.4) 2 Lenoir 2 (24.6) 5 (49.0) 16 (138.6) 3 (33.8) 1 5 (27.7) Nash 3 (7.0) 7 (29.0) 8 (48.0) 1 (10.0) 5 Orange 1 (3.0) 3 (12.0) 17 (89.0) 29 2 (17.0) Pamlico 2 (9.0) 1 (6.0) 2 Person 2 (8.0) 16 (72.0) 12 (42.5) 12 Pitt 2 (22.0) 9 (97.9) 4 (65.0) 2 (86.4) Wake 11 (83.0) 25 (157.8) 19 (87.8) 2 (7.0) 11 2 (10.2) Wayne 2 (32.0) 3 (47.0) 9 (67.7) 8 Wilson 1 (5.5) 7 (178.0) 8 (55.0) 8 11

16 Drainage Directions The number of drainage directions within each field is presented in Table 3. The maximum number of drainage directions was 3 and the minimum 1. Orange County had the most number of drainage directions (average of 2.0), whereas Craven, Greene, Nash, and Wilson had average drainage directions of 1.0. Drainage direction is important because edge-of-field BMPs (e.g. controlled drainage structures, riparian buffers) may change if there is more than one drainage direction. In addition, since slope may vary with each drainage direction, soil erosion may differ. Sampling fields with fewer drainage directions is easier. It was not unexpected that the number of drainage directions decreased closer to the coast where the landscape is flat. Table 3. Drainage directions by county minimum, maximum and mean. County Number of fields Minimum drainage directions Maximum drainage directions Mean Craven Durham Edgecombe Franklin Granville Greene Johnston Jones Lenoir Nash Orange Pamlico Person Pitt Wake Wayne Wilson Cover Crops Winter cereal cover crops are one of several BMPs that can reduce both N and P. Although producers answered a question about cover crop use, we did not use their answer, but rather selected cover crops based on N fertilizer rates. To qualify as a winter cereal cover crop, no N fertilizer can be applied to wheat, oats, rye or triticale. Table 4 lists the acres of the different cover crop types by county and the percentage of the county acreage that these practices comprised for the 2008 winter season. Nine 12

17 counties did not use a cover crop, thus the overall average for cover crop usage was quite low 1%. Wheat was the predominant winter cereal cover crop used by producers in the Neuse River Basin, followed by rye and oats. Not only did producers did not fertilize cover crops with N, they also did not use P or potassium. Table 4. Acres and percentage of cover crops by species and by county. Acres enumerated Wheat cover (acres) % Wheat total acres Rye cover (acres) % Rye total acres Oats cover (acres) % Oats total acres Triticale cover (acres) % Triticale total acres Craven Durham Edgecombe Franklin Granville Greene Johnston Jones Lenoir Nash Orange Pamlico Person Pitt Wake Wayne Wilson Cover crop use, particularly wheat has dropped dramatically in this basin since the 2000 survey, when one county had wheat cover crops on 43% of the acreage. Cover crop use ranged from over 50% to none. Conservation Tillage For a field to be under conservation tillage, a 30% residue cover must be maintained. If producers selected conservation tillage and they had a cropping system that would produce the 30% cover, we designated these fields as conservation tillage. If, however, producers said they were using conservation tillage but did not have a cropping system that would produce the minimum cover, such as cotton following cotton without a winter cover crop, that field was designated as conventional tillage. All acreage of conservation tillage was summed to determine the total percent of all agriculture lands under conservation tillage (conservation tillage acres/total acres*100 = % conservation tillage) for both fall and spring planted crops (Table 5). 13

18 Table 5. Percentage and acreage of conservation tillage by county. % Acres Conservation Tillage County Conservation Enumerated (acres) Tillage Craven Durham Edgecombe Franklin Granville Greene Johnston Jones Lenoir Nash Orange Pamlico Person Pitt Wake Wayne Wilson All The largest amount of conservation tillage was used in Wayne County (88 % of the acreage). The next highest use of conservation tillage was Craven (70%) followed by Johnston (63%), Person (59%), Wake and Lenoir (54%), Pitt (48%), Greene and Durham (41%), Granville (40%), Franklin (35%), Pamlico (34%), Edgecombe (24%), Orange (23%), Jones (21%), Nash (20%), and Wilson (17%). The average amount of conservation tillage used in the Neuse Basin overall was 54%. Although it may appear that conservation tillage was used less frequently in some of the piedmont counties, such 14

19 as Durham and Orange, the calculation for conservation tillage was based on all agricultural acreage. Much of the agriculture in these counties is pasture based; thus most of the agricultural land use in the piedmont has coverage. Unfortunately, conservation tillage information was not explicitly collected in the Neuse 2000 Agricultural survey so there is no comparison. Water Control Structures Water control structures are used to control shallow groundwater depths, generally when slopes are less than 1%. During the spring, boards placed in flashboard risers are removed to allow the groundwater table to drop, thus drying up soil for planting. After planting, the boards are reinstalled to increase the depth of the groundwater table. Generally, both N and P are reduced through the use of these structures. Enumerators found 20 water control structures (Craven, Pamlico, and Jones) representing acres. This was fewer acres than the 2000 survey (560 acres); however, we believe that this represents more reliable enumeration in the 2008 survey as the enumerators have greatly increased their abilities as they conducted additional surveys. The water control structures had an average ditch distance of 180 ft. and were, on average, 40 in. deep. Six of the structures were not being managed, while 7 were under management. It is possible that the remaining 7, although not being actively managed, had sufficient number of boards year-round to qualify for some N reduction. We did not collect management data for water control structures in the 2000 survey. This data has been instrumental in Soil and Water revising credit for these structures by conducting spot-checks to ensure adequate maintenance. Riparian Buffers Several buffer types were recognized under the Neuse Rules and given credit for reducing N. These buffer types are as follows: 1) 50-foot buffer or greater comprised of at least 30 feet of trees and 20 feet of vegetation, 2) 30-foot or greater vegetative buffers, 3) 20 to 29 foot vegetative buffer, or 4) 20- to 29-foot tree or shrub buffers. These buffer widths and types are no longer used to differentiate buffer effectiveness and credit is based on width alone: ft (20% reduction), ft (25% reduction), ft (30% reduction), and >35 ft (35% reduction). Riparian buffer data are shown in Tables 5-8. Information was collected for buffer vegetation type (tree, shrub, or vegetative), buffer width, and number of cropped acres that flow through the buffer. We are confident that the buffer data is very solid. Each BMP record was reviewed against the 1993 DOQQ maps by two professionals one from USDA-NASS and the other from NC State University. Table 6 shows the percentage of agricultural fields not buffered by either vegetative or tree buffers. Some counties, such as Johnston and Orange, had most of their agricultural fields buffered; only 17% of the acreage is not buffered. 15

20 Table 6. Number of acres and percentage of this area buffered and not buffered by county. County % % No buffers Acres agriculture agriculture - acres Enumerated fields NOT fields affected buffered buffered Craven Durham Edgecombe Franklin Granville Greene Johnston Jones Lenoir Nash Orange Pamlico Person Pitt Wake Wayne Wilson All Agricultural fields in counties close to the estuary are very flat and poorly drained; as such, drainage ditches are used to drain the soil in order to farm the land and producers typically do not vegetation to grow next to the drainage ditches as to ensure ease of ditch cleanout. Thus counties, such as Craven, Jones, Pamlico, and Pitt, have large percentages (> 55%) of non-buffered agricultural lands; however, these are the counties that have the greatest amount of controlled drainage, which can replace riparian buffers. Buffer data in 2000 were obtained in a slightly different manner due to the buffer regulation and N reduction credits that were given at the time. Thus we can only compare % affected acres. About half of all counties had very similar number of acres affected by buffers; half did not. Those counties where the affected acres varied between 2000 and 2008, it was assumed that some of the increases in acres affected by buffers was due to buffer implementation programs such as CREP and CRP, especially in Edgecombe County where there was an aggressive push to enroll farmers in these programs. Buffer widths were reported for each type of buffer: shrub/tree or vegetative. The minimum width of tree/shrub buffers ranged from a low of 1 ft to over 4000 ft, with a mean width of 201 ft (Table 7). Mean buffer width in all counties was always greater than the standard width of 50 ft, which is a regulatory width 16

21 Table 7. Number of fields by county with tree/shrub buffer, and minimum, maximum and mean buffer width. County Number of fields Width (ft) Minimum Maximum Mean Craven Durham Edgecombe Franklin Granville Greene Johnston Jones Lenoir Nash Orange Pamlico Person Pitt Wake Wayne Wilson All

22 Vegetative buffers were found in all counties and ranged in width from 0.5 to 800 ft with a mean of 40 ft (Table 8). Table 8. Number of fields with vegetative buffers and minimum, maximum and mean vegetative buffer widths. County Width (ft) Number of fields Minimum Maximum Mean widths widths (ft) widths (ft) (ft) Craven Durham Edgecombe Franklin Granville Greene Johnston Jones Lenoir Nash Orange Pamlico Person Pitt Wake Wayne Wilson All

23 The number of agricultural field acres affected by buffers is presented in Table 9 by buffer type. More acres are affected by tree/shrub vegetative structures than vegetation (usually grass). Table 9. Total agricultural acres affected by tree/shrub buffers, vegetative buffers, and tree/shrub + vegetative buffers. Agricultural acres affected by different buffer types County Tree/shrub only Vegetative only Both buffer types Craven Durham Edgecombe Franklin Granville Greene Johnston Jones Lenoir Nash Orange Pamlico Person Pitt Wake Wayne Wilson All In-stream basins or ponds can serve to reduce P through sedimentation. Table 10 shows the number of field acres affected by both of these structure types. Ponds affected 2,513 acres, while in-stream wetlands affected 1,665 acres. The total number of agricultural acres that these practices affected was very small relative to the 37,212 acres enumerated. 19

24 Table 10. Total agricultural acres affected by in-stream basins or ponds County Total agricultural acres affected by ponds or in-stream wetlands In-stream County In-stream wetlands Ponds wetlands Ponds Craven Nash Durham Orange Edgecombe.. Pamlico Franklin Person Granville Pitt Greene Wake Johnston Wayne Jones Wilson Lenoir Nitrogen, Phosphorus, and Potassium Rates The average N, P and potassium (K) rates were sorted by type of applied nutrient (commercial fertilizer or manure) and presented in separate tables by source. Each set of source table are divided by nutrient (N, P, and K). Nutrients are then listed for each crop as a range and mean (Table 11 a-c). Nitrogen is reported as elemental N, P as P205 and K as K20. Although fertilizer rates varied between different crops within a county and within the same crop, across counties, fertilization seems on target for most crops, with the exception of P (to be discussed later). The average amount of N for all crops based on a weighted average was relatively low due to the high percentage of soybeans (most of which were not fertilized) and/or pasture/hay, which again is not fertilized or minimally fertilized. It is difficult to compare N rates from the 2000 enumeration to the 2008 as crops grown in each county shift from year to year. Overall, though, it is clear that there has been a significant reduction in applied N to soybean since 77% of the 2008 crop did not receive fertilizer, including N. This was not the case in The majority of tobacco acreage is receiving lower N rates in 2008 than 2000, while cotton fertilization appears to be similar or slightly greater in 2008 than in Unfortunately, the N fertilization rates on corn in 2000 were unreliable so it cannot be determined whether rates have increased or decreased. The corn rates are under what we would expect, because in most counties there are a few fields that are not fertilized. When this data is removed (data not shown), the N rate for corn is still well within the appropriate rate range for corn. 20

25 Table 11a. Commercial fertilizer nitrogen rates (Within subtotals, total acres and number of fields represent all acres and number of fields within that county that were enumerated, while minimum, maximum and mean rates averaged over all crops and presented in lbs/ac.) 21 Minimum N rate (lbs/ac) Maximum N rate (lbs/ac) Mean N rate (lbs/ac) County Crop Total acres Number of fields Craven Corn Tobacco Nursery Soybeans Other hay Peanuts Cotton Pasture Wheat Subtotal Durham Rye Wheat Soybeans Other hay Pasture Subtotal Edgecombe Wheat Soybeans Tobacco Subtotal Franklin Oats Wheat Barley Corn Vegetables Tobacco Other Hay Pasture Subtotal Granville Wheat Corn Other hay Soybeans Vegetables Tobacco Cotton Pasture Subtotal

26 Greene Rye Corn Soybeans Peanuts Sweet potatoes Tobacco Cotton Wheat Pasture Subtotal Johnston Oats Wheat Rye Corn Other hay Sorghum Soybeans Sweet potatoes Vegetables Strawberries Tobacco Cotton Pasture Subtotal Jones Wheat Corn Other hay Soybeans Peanuts Tobacco Cotton Pasture Subtotal

27 Lenoir Oats Wheat Corn Other hay Soybeans Peanuts Sunflowers Sweet potatoes Tobacco Cotton Pasture Subtotal Nash Oats Rye Corn Other hay Soybeans Peanuts Sweet potatoes Watermelons Tobacco Cotton Pasture Vegetables Wheat Subtotal Orange Oats Wheat Corn Other hay Soybeans Tobacco Pasture Sod Subtotal

28 Pamlico Wheat Corn Sorghum Soybeans Tobacco Cotton Other Hay Subtotal Person Oats Wheat Corn Other hay Soybeans Watermelons Tobacco Pasture Subtotal Pitt Vegetables Wheat Corn Other hay Peanuts Soybeans Tobacco (burley) Tobacco (flue cured) Cotton Pasture Subtotal

29 Wake Oats Rye Wheat Corn Other hay Soybeans Sorghum silage Sweet potatoes Watermelons Vegetables Tobacco Pasture Subtotal Wayne Wheat Rye Corn Other hay Sorghum Soybeans Peanuts Sweet potatoes Watermelons Tobacco Cotton Pasture Subtotal Vegetables Wheat Rye Corn Other hay Peanuts Soybeans Sweet Potatoes Watermelons Tobacco Cotton Subtotal

30 Table 11b. Commercial fertilizer phosphorus rates (Within subtotals, total acres and number of fields represent all acres and number of fields within that county, while minimum, maximum and mean rates averaged over all crops and presented in lbs/ac.) Total acres in production Number Minimum P Maximum Mean County Crop of fields rate P rate P rate Craven Corn Tobacco Nursery Soybeans Other hay Cotton Pasture Wheat Peanuts Subtotal Durham Rye Wheat Other hay Pasture Soybeans Subtotal Edgecombe Wheat Soybeans Tobacco Subtotal Franklin Oats Wheat Barley Corn Soybeans Vegetables Tobacco Pasture Other Hay Subtotal

31 Granville Wheat Corn Other hay Vegetables Tobacco Cotton Soybeans Pasture Subtotal Greene Rye Corn Soybeans Peanuts Sweet potatoes Tobacco Cotton Wheat Vegetables Subtotal Johnston Oats Wheat Rye Corn Other hay Sorghum Soybeans Peanuts Sweet potatoes Vegetables Strawberries Tobacco Cotton Millet Pasture Wildflowers for Seed Subtotal

32 Jones Wheat Corn Other hay Soybeans Peanuts Tobacco Cotton Pasture Subtotal Lenoir Oats Wheat Triticale Corn Other hay Soybeans Peanuts Sunflowers Sweet potatoes Tobacco Cotton Pasture Subtotal Nash Oats Corn Other hay Soybeans Peanuts Sweet potatoes Watermelons Tobacco Cotton Pasture Rye Vegetables Wheat Subtotal

33 Orange Oats Wheat Corn Other hay Soybeans Tobacco Pasture Sod Subtotal Pamlico Wheat Corn Sorghum Soybeans Tobacco Cotton Other hay Pasture Subtotal Person Oats Wheat Corn Other hay Soybeans Watermelons Tobacco Pasture Subtotal Pitt Vegetables Wheat Corn Other hay Peanuts Soybeans Tobacco (burley) Tobacco (flue cured) Cotton Pasture Subtotal

34 Wake Oats Rye Wheat Corn Other hay Soybeans Sweet potatoes Watermelons Vegetables Tobacco Sorghum silage Pasture Subtotal Wayne Wheat Corn Rye Other hay Sorghum Soybeans Sweet potatoes Watermelons Tobacco Cotton Pasture Alfalfa Subtotal

35 Wilson Watermelons Vegetables Wheat Corn Other hay Peanuts Soybeans Sweet potatoes Tobacco Cotton Subtotal Table 11c. Commercial fertilizer potassium rates (Within subtotals, total acres and number of fields represent all acres and number of fields within that county that were enumerated, while minimum, maximum and mean rates averaged over all crops and presented in lbs/ac.) Total acres in production Number Minimum Maximum Mean K County Crop of fields K rate K rate rate Craven Corn Tobacco Peanuts Nursery Soybeans Other hay Cotton Pasture Wheat Subtotal Durham Rye Wheat Soybeans Other hay Pasture Subtotal Edgecombe Wheat Soybeans Tobacco Subtotal

36 Franklin Oats Wheat Barley Soybeans Corn Vegetables Tobacco Pasture Subtotal Granville Wheat Corn Other hay Vegetables Soybeans Tobacco Cotton Pasture Subtotal Greene Rye Corn Soybeans Sweet potatoes Tobacco Cotton Wheat Pasture Vegetables Subtotal

37 Johnston Oats Wheat Rye Corn Other hay Sorghum Soybeans Sweet potatoes Vegetables Strawberries Tobacco Cotton Millet Pasture Wildflowers for seed Peanuts Subtotal Jones Wheat Corn Peanuts Soybeans Tobacco Cotton Pasture Subtotal Lenoir Oats Wheat Triticale Corn Other hay Soybeans Sunflowers Sweet potatoes Tobacco Cotton Pasture Subtotal

38 Nash Oats Corn Other hay Soybeans Sweet potatoes Watermelons Tobacco Cotton Pasture Rye Vegetables Wheat Subtotal Orange Oats Wheat Corn Other hay Soybeans Tobacco Pasture Sod Subtotal Pamlico Wheat Corn Sorghum Soybeans Tobacco Cotton Pasture Subtotal Person Oats Wheat Corn Other hay Soybeans Watermelons Tobacco Pasture Subtotal

39 Pitt Vegetables Wheat Corn Other hay Peanuts Soybeans Tobacco (burley) Tobacco (flue cured) Cotton Pasture Subtotal Wake Oats Rye Wheat Corn Sorghum silage Soybeans Sweet potatoes Watermelons Vegetables Tobacco (flue cured) Pasture Subtotal Wayne Wheat Rye Corn Other hay Sorghum Soybeans Sweet potatoes Watermelons Tobacco (flue cured) Cotton Pasture Subtotal

40 Wilson Watermelons Vegetables Wheat Corn Other hay Peanuts Soybeans Sweet Potatoes Tobacco Cotton Subtotal Animal waste was applied to 57 fields out of 3,248, which represented 1.8% of all the agricultural fields to which nutrients were applied (Table 12 a-b). Nutrient rates were not excessive. During the 2000 survey, farmers were unwilling to give us any information so we have no comparison. Table 12a. Applied organic nitrogen (2008). County Crop Field acres applied Number of fields lb N per acre per year Minimum rate Maximum rate Average rate Wheat Corn Greene Soybeans Johnston Soybeans Corn Jones Cotton Oats Wheat Corn Lenoir Pasture Nash Sweet potatoes Soybeans Pitt Cotton Orange Wheat Wheat Corn Wayne Pasture

41 Table 12b. Applied organic phosphorus (2008). County Crop Field acres applied Number of fields 37 Minimum rate lb N per acre per year Maximum rate Average rate Wheat Corn Greene Soybeans Johnston Soybeans Corn Jones Cotton Oats Wheat Corn Lenoir Pasture Nash Sweet potatoes Other hay Soybeans Pitt Cotton Orange Wheat Wheat Corn Wayne Pasture Sorting the data by county, producer id number, and crop, we were able to determine if the same producer fertilized his or her fields of the same crop using the identical fertilizer application rate. (The numbers are not exact since this analysis was done completely by hand but they are reasonably accurate.) This allows us to determine nutrient management use. The number of the same crop fields being managed by the same farmer and fertilized identically was 214 for cotton, 258 for corn, 245 for flue-cured tobacco, 202 for pasture/hay, 155 for miscellaneous crops (vegetables, etc), 982 for soybeans, and 290 for wheat. In some cases, such as soybean,s fields that were fertilized identically received no fertilizer; that is the effective rate of fertilizer application was 0 on approximately 50% of the fields. The percentage of the same crop being fertilized identically in multiple fields by the same farmer was 92% for cotton, 73% for corn, 86% for flue-cured tobacco, 73% for pasture/hay, 81% for miscellaneous crops (vegetables, etc), 90% for soybeans, and 82% for wheat. We have provided a table for any crop that was grown on multiple fields by the same farmer and fertilized differentially (Table 13). By crop, we list the number of fields managed by the same farmer (first number). We then identify the number of different fertilizer strategies (the numbers after the colon separated by comma(s). For

42 instance, for the first cell under cotton, there are 7 fields managed by the same farmer who applies the same fertilizer regiment to 2 fields and another fertilizer regime to 5 fields. For both soybeans and pasture/hay, often of the different fertilizer regimes consisted of no fertilizer or a rate of zero. Together, these data clearly demonstrate that producers are generally not following nutrient management plans that would prescribe different fertilizer rates based on soil test and N realistic yield expectations. Although, in some cases it is possible that identical fertilizer regimes do represent nutrient management planning. However, for the most part, nutrient management plans are not used. An analysis of the N and P fertilizer rates suggests that fertilizer is being used judiciously. Table 13. Number of fields of a crop fertilized by a producer (first number) and the number of different fertilizer application regimes by crop (numbers following the colon and separated by a,. Crop Cotton Corn Miscellaneous Pasture/Hay Soybean Tobacco Wheat 7:2,5 4:2,2 10:2,8 6:1,2,1,2 7:4,3 5:3,1,1 3:1,1,1 3:1,2 7:2,5 10:6,4 6:2,3,1 6:5,1 2:1,1 7:6,1 3:2,1 3:2,1 3:2,1 8:4,4 5:2,2,1 3:2,1 2:1,1 3:1,1,1 5:1,3,1 2:1,1 5:4,1 5:2,2,1 4:2,2 2:1,1 7:1,6 3:2,1 12:6,6 8:2,6 3:2,1 4:3,1 2:1,1 2:1,1 4:2,2 3:2,1 4:2,2 2:1,1 2:1,1 2:1,1 3:2,1 9:7,2 2:1,1 7:3,4 3:2,1 4:2,1,1 3:2,1,1 6:5,1 2:1,1 4:3,1 3:2,1 8:4,2,2 3:1,1,1 5:2,2,1 4:3,1 20:16,4 3:2,1 2:1,1 5:2,2,1 3:2,1 2:1,1 4:1,3 13:6,2,5 3:2,1 9:3,6 9:2,3,4 2:1,1 2:1,1 4:1,2,1 3:2,1 4:1,3 13:2,1,5,2 4:2,2 2:1,1 3:2,1 4:2,2 4:3,1 The NC Agricultural Nutrient Assessment Tool was used to calculate P and N losses for fields enumerated in the Neuse River Basin. Phosphorus losses calculated via PLAT were predominantly Low (85%). Slightly over 3% of all fields had PLAT ratings High (3%), and Very High (< 1%). Seventy-one percent of the fields had N application rates lower than recommended. Of the fields that applied more N than recommended, overapplication averaged 8.7 lb N ac

43 Soil Test P and P Fertilization In the last 3 years, 97% of the acres surveyed were soil sampled, while 3% of the acreage did not have samples. Soil test P was not part of the 2000 survey. The mean and weighted mean for soil test P is presented in Table 14 and the values, on average, are very close. We had soil test P data for the majority of the fields sampled either from farmer records or from soil sampling during this enumeration. Weighted soil mean takes each soil test value, multiplies it by the number of acres for that soil test value and then sums all these values. This summed value is then divided by the total number of acres. Using the weighted soil test P mean gives us more information than just the mean value. Twelve counties have mean soil test P levels above 100, reflecting very high soil test ratings; these soils do not need additional P. Soil test P values for the other five counties were high, which again indicates that typically P does not need to be applied. Despite the lack of need for fertilizer P, the average applied P was typically around 30 to 40 lb P 2 O 5 ac- 1. Producers could save money and reduce P losses by following their soil test results. Table 14. Mean and weighted mean soil test P-index by county. County Number of fields Minimum Maximum Weighted mean Mean Craven Durham Edgecombe Franklin Granville Greene Johnston Jones Lenoir Nash Orange Pamlico Person Pitt Wake Wayne Wilson All When soil test levels are above 60, crops do not need additional P except for perhaps as starter fertilizer. We divided fields into those with soil test levels above 60 and those less than or equal to 60 to determine if P fertilization rates are different (Table 15). Applied 39

44 P was similar for fields regardless of P needs: 33 lb P 2 O 5 ac- 1 for soils that do not need P and 35 lb P 2 O 5 ac- 1 for fields that do need P fertilizer. Table 15. Phosphorus fertilization rates for soils needing phosphorus fertilizer (STP > 60) and soils testing low and medium STP (< 60). Condition STP* > 60 & P Applied STP < 60 & P Applied STP > 60 & P Applied > 20 (lb ac -1 ) Fall Spring Fall Spring Fall Spring Acres Applied P2O5 (lbs ac -1 ) *Soil Test Phosphorus (STP) is measured as the P-Index by North Carolina Department of Agriculture and Consumer Services. There were 58 fields representing 637 acres in the fall that received no fertilizer and 892 fields representing 8961 acres that received no fertilizer in the summer. Non-fertilized spring & summer crops are listed in Table 16; soybeans and pasture represented 86% of the field acres that did not receive fertilizer. Twenty percent (1,387 acres) of the soybean acres were fertilized with, on average, 24 lb of N fertilizer. Table 16. Non-fertilized spring and summer crops by acres and fields. Crop Acres Number of Fields Corn Cotton 67 2 Hay Pasture Peanuts Sod 80 2 Sorghum 10 2 Soybeans Sweet Potato 18 1 Tobacco 4 2 Vegetables Slope, Soil Loss, and Receiving Slopes Predictably, counties in the lower coastal plain had much lower slopes than counties in the piedmont (Table 17). Durham, Granville, Orange, and Wake had the greatest slope. Soil erosion rates for the coastal plain counties were calculated using tables developed from RUSLE by USDA-NRCS and was based on the physiographic region in the coastal plain, crop and cropping system. In the piedmont region, soil erosion was calculated 40

45 using RUSLE Interpretation of erosion rates must be viewed with care since we used two methodologies to determine soil loss and thus, the differences in soil loss should be viewed as relative loss rates. In general, most counties displayed low rates except for Craven, Jones and Pamlico counties, which were estimated rather than calculated. The order of soil loss was Durham (0.71 t ac -1 ) < Granville (1.11 t ac -1 ), Orange (1.22 t ac -1 ) < Wake (1.5 t ac -1 ) < Person (1.96 t ac -1 ) = Wayne (1.98 t ac -1 ) < Greene (2.14 t ac -1 ) < Johnston (2.23 t ac -1 ),Franklin (2.33 t ac -1 ) < Edgecombe (2.55 t ac -1 ) < Lenoir (2.80 t ac -1 ) < Wilson (2.87 t ac -1 ) < Nash (3.33 t ac -1 ) < Craven (5.56 t ac -1 ) < Pamlico (6.45 t ac -1 ) < Pitt (6.90 t ac -1 ) < Jones (7.48 t ac -1 ). Soil erosion was calculated for the piedmont Counties using RUSLE 1.04; all of these counties, except Franklin had soil loss below 2 t ac -1. It is doubtful that soil erosion is as high as the NRCS tables predict in Craven, Pamlico, Pitt and Jones as they are very flat counties where runoff, not erosion, is the predominant hydrologic pathway. These data suggest that soil erosion is well controlled in the Neuse River Basin either due to the cropping system, tillage system, topography or a combination of factors. Table 17. Minimum, maximum and weighted means for field slope and soil erosion by county. Number County of fields Field slope (%) Soil erosion (t ac -1 ) Minimum Maximum Weighted mean Minimum Maximum Weighted mean Craven Durham Edgecombe Franklin Granville Greene Johnston Jones Lenoir Nash Orange Pamlico Person Pitt Wake Wayne Wilson All Receiving slopes are the slopes within the field that allow deposition of eroded materials. Some fields had only one slope direction and thus only one receiving slope whereas other fields could have as many as three slope directions; thus Table 18 is presented by slope 41

46 direction. Mean receiving slope widths ranged from a low of 1 ft to high of19 ft long. (Receiving slope widths are calculated within classes, for instance 0-9 ft or ft.) Receiving slopes are particularly useful if soil loss is occurring from the adjacent agricultural field. However, since soil loss was, on average, so low, receiving slopes would have less effect due to the lack of sediment eroded from fields. Not surprisingly, coastal plain counties had narrow receiving slopes (1-9 ft). Table 18. Number of field acres* with associated receiving slopes for up to three drainage directions per field and the mean receiving length (feet) by county. County Direction A Direction B Direction C Mean receiving Mean receiving Acres Affected* slope length (ft) Acres Affected slope length (ft) Acres Affected Mean receiving slope length (ft) Craven Durham Edgecombe Franklin Granville Greene Johnston Jones Lenoir Nash Orange Pamlico Person Pitt Wake Wayne Wilson Agricultural Demographics We started adding agricultural demographic questions during the Jordan Lake survey so this information is new for the Neuse survey. Of the respondents to this question, 86% consider agriculture to be their primary source of income and 14% did not. For those producers for whom their agricultural activities were not a primary source of income, 36% indicated that it was a secondary source of income, 35% said it was a minor source, and 29% said they received no income from their farming activities. These data suggest that most agricultural activities are conducted by full-time producers. Rental rates of crop land varied significantly (Table 19) from 38% leased land (Orange County) to 88% percent leased land (Pamlico and Johnston). In only one county (Orange) did producers own more land than they rented. 42

47 Table 19. Percent field acres owned or rented by county County Land Rented County Land Rented No (%) Yes (%) No (%) Yes (%) Craven Nash Durham Orange Edgecombe Pamlico Franklin Person Granville Pitt Greene Wake Johnston Wayne Jones Wilson Lenoir Fertilizer Use Information Of the producers who answered this question, 62% did not follow a nutrient management plan, while 38% did have a nutrient management plan. For those not having a plan, nutrient recommendations were made by the following organizations or individuals (Table 20). Table 20. Organizations or individuals who make fertilizer recommendations when a nutrient management plan is not used. Number of Organization or individual people % Fertilizer Dealer Paid consultant NRCS Extension Friend/Other Farmer Self Other No Commercial Fertilizer applied

48 For those individuals who have nutrient management plans, 32% use both commercial fertilizer and animal waste, 2% use only animal waste, and 66% use only commercial fertilizer. From Table 21, it is apparent that the majority of nutrient management plans are written by the producers themselves. Table 21. Organizations or individuals who write nutrient management plans. Number of Organization or individual people % Fertilizer Dealer Paid consultant NRCS Extension Friend/Other Farmer Self Other Nutrients are applied mostly by the farmers themselves (50%) but also by others, mostly fertilizer deals (35.5%) (Table 22). Table 22. Organizations or individuals who apply nutrients. Number of Organization or individual people % Fertilizer Dealer Friend/Other Farmer Self Other

49 Animal Agriculture We collected information on different animal species cattle, horses, sheep, goats, and other animals. The number of fields containing any animal type is listed below, as are the average head on a given field and the average day on pasture. Considerably more cattle are found in this basin than horses, sheep or goats (Table 23 and 24). The largest number of cattle on any field was in Lenoir County and the longest cattle were grazed was in Person (189.8days). The second largest animal population was horses with 2.4 average head and 92.7 average days. Jones County had the most horses, followed by Lenoir and Franklin. Pastures were rarely grazed all year, with the average grazing duration of 102 days for cattle and 93 days for horses. Pastures with livestock were lightly stocked. Table 23. Average head, average number of days, and stocking rate of cattle and horses. County Cattle Horses Average head Average day Average head/ ac/ yr Average head Average day Average head/ ac/ yr Craven Durham Edgecombe Franklin * Granville Greene * Johnston Jones Lenoir Nash Orange Pamlico * Person Pitt Wake Wayne Wilson *Stocking density and the amount of time is so low that the calculated rate is 0 45

50 Sheep were only found in Durham and Johnston County and goats were enumerated in Durham, Franklin, Johnston, Nash, Orange, Pamlico, Pitt, Wake, and Wayne counties (Table 24). Pastures with livestock were lightly stocked. Table 23. Average head, average number of days, and stocking rate of goats and sheep. County Goats Sheep Average head Average day Average head/ ac/ yr Average head Average day Average head/ ac/ yr Craven Durham * Edgecombe Franklin Granville Greene Johnston Jones Lenoir Nash Orange Pamlico Person Pitt Wake Wayne Wilson *Stocking density and the amount of time is so low that the calculated rate is 0 46

51 Additional animals included a llama and a buffalo, chickens, donkeys, ponies and miniature horses, and alpaca (Table 25). These animal species represented a very small number of animal agriculture. Table 25. Other animal types and numbers by county. Number County Animal type of animals Average days grazed per year Durham Llama Franklin Chickens Greene Donkeys Johnston Miniature horse Johnston Buffalo Jones Donkeys Nash Ponies Orange Donkey Pitt Alpaca Pitt Burro Wake Chickens Wayne Donkeys Neuse River Basin Special Situations There were a number of special situations enumerated and as the fertility rates could not be computed, these situations are listed below. We were unable to obtain a soil test report on most of these fields. In only a few cases does it appear that there is significant overstocking or over application of nutrients ac pasture; plowed ground that they tried to replant; currently no vegetative cover; has 1 miniature horse ac pasture with 3 horses, 2 goats, and 1 miniature donkey (122 days) 3. 3 ac pasture with 3 horses, 2 goats, and 1 miniature donkey (122 days) 4. 2 ac pasture with 3 horses, 2 goats, and 1 miniature donkey (122 days) 5. 1 ac flue-cured tobacco with regular fertilization (75 lbs N, 60 lbs P, 145 lbs K) PLUS class A sludge from City of Raleigh in dry form; operator said that sludge was mainly lime; applied in January; did not know amount of % N ac flue-cured tobacco with regular fertilizer (75 lbs N, 60 lbs P, 145 lbs K) PLUS class A sludge from City of Raleigh in dry form; operator said that sludge was mainly lime; applied in January; did not know amount of % N ac field; operator applied turkey house litter with analysis of 32-30; put out 1 load of litter per 2 acres but did not know pounds; was shooting for total 150 lbs of N ac field; grows wildflowers for seed; applied at 250 lbs per ac. 47

52 9. 4 ac field; grows wildflowers for seed; applied at 250 lbs per ac. 10. Entire segment are fields for Contentnea Metro Sewage District; all fields were coastal Bermuda grass with treated water applied. They supplied N and phosphate amounts. 11. Field1 is hay and field2 is pasture. Both have Granville Farms waste applied acre field that was dirt with 14 horses year round. Did not complete and did not collect soil samples acres pasture with 50 cattle year round; refused soil sample ac pasture w/6 cattle, 8 horses, and 1 buffalo w/ 21 lbs of N commercial fertilizer and also spreads manure from stalls on field. 15. City of Raleigh bought but nothing currently being done with the land ac cleared field on a wildlife trail; lots of horses in the woods near this clearing. 17. Owner has permit for septic dumping and gates were locked; these fields were coded inaccessible. 18. Woodland pasture (mostly woods) and no way to sample; field was coded inaccessible. 19. Agriculture land to Progress Energy (wooded now). 20. Wildlife planting by the NC Wildlife Commission ac hog pen with 25 hogs (not really a pasture); was nonag in ac with 4 miniature horses (nonag in 2001) 23. Oats/soybeans grazed by cattle in late winter (10 cattle for 30 days) 6 ac field 24. Oats/ soybeans grazed by cattle in late winter (15 cattle for 40 days) 11 ac field 25. Oats / soybeans grazed by cattle in late winter (20 cattle for 30 days) 6 ac field 26. Oats/ soybeans grazed by cattle in late winter (30 cattle for 14 days) 3.5 ac field 27. Oats/ soybeans grazed by cattle in late winter (20 cattle for 30 days) 3 ac field 28. Rye/millet not harvested but grazed by cattle (30 cattle for 75 days) 5 ac field 29. Oats/ soybeans grazed by cattle in late winter (10 cattle for 30 days) 8 ac field 30. Rye/millet grazed by cattle in late winter (30 cattle for 100 days) 8 ac field ac field coded as SB sweet potato beds planted 3/15 then harvested sweet potatoes on 5/1 then planted SB on 6/ Deer corn field that was fertilized 33. Planted sorghum then grazed and hayed since animals were on fields, it is coded as pasture with soil loss of Soybeans not harvested (crop loss) 35. Soybeans not harvested (crop loss) horses in a dirt lot. 37. Soybeans not harvested (crop loss) ac paddock; very little grass with 2 horses (voluntary non-profit therapeutic riding facility) 48

53 OUTCOMES AND CONCLUSIONS Neuse Basin The area frame sampling technique did an excellent job of allowing proper selection of fields within the Neuse River Basin. Agricultural information that is not generally collected through USDA agricultural surveys was gathered. This information demonstrates much more detail about current agricultural practices than normally obtained. There were approximately 1,500 acres transferred from agricultural into developed land uses. Most agricultural uses, however, stayed in row crop production primarily of corn, soybeans, cotton, and tobacco. Eighty-six percent of the people we interviewed received their primary income from farming, although many rent land (> 50% rental lands). In general, this survey demonstrated that agricultural producers are minimizing soil erosion through conservation tillage (53%) and topographic location (coastal plain). Erosion, which is most probably overestimated, was on average only 3 t ac -1 yr -1. Nitrogen and P reducing BMPs are used throughout the basin, with an average of 64% of all field acres being buffered. Over half the buffers are trees that have an average width of 200 ft; vegetative buffers had an average width of 50 ft thus meeting the width requirements of the Neuse Rules. There were a limited number of water control structures. Soil test P is very high average P-I of 135) in 12 out of the 17 counties; five counties had high soil test P. For fields not needing P (high or very high soil test P), farmers applied 33lb P 2 O 5 ac -1 and 35 lb P 2 O 5 ac -1 to fields that needed P. Nitrogen fertilizer rates were not excessive and farmers have significantly reduced the amount of N applied to soybeans. Most producers are using the same fertilizer regime if they fertilize multiple fields of the same crop, but the fertilization does not seem to be excessive. More than 60% of the farmers do not follow nutrient management plans, which supports the data that most producers use the same fertilizer regime on multiple fields of the same crop. Again, however, except for starter applications of P, which could be discontinued in most fields, the data show that producers are not applying excess fertilizer rates. The data lead us to believe that the majority of agricultural production is controlling erosion, using conservation practices such as buffers frequently, and applying reasonable amounts of fertilizer and animal waste. Falls Lake Watershed Specific to those counties in the upper portion of the Neuse Basin which are part of Falls Lake, pasture represents more than half the agricultural land use in Durham (74%) and 49

54 Orange (69%). Durham lost the most amount of land of all counties in the entire Neuse Basin to development. Nitrogen application to all crops are well within the recommended N rates and sometimes below in both Orange and Durham counties. Erosion is low (below T) in Durham (0.71 t ac -1 yr -1 ) and Orange ( t ac -1 yr -1 ), which is due to large amounts of pasture and relatively large use of conservation tillage in Durham (41%) and Orange (23%). Percent conservation tillage is calculated from all agricultural lands, including pasture. In Durham, all cropland is under conservation tillage because when % pasture and % conservation tillage are added, the value is greater than 100%. This is because fields can be counted more than once in a crop year by accommodating a wheat crop in the fall and a second crop, generally soybeans, during the summer. Lastly, Orange County had the greatest amount of buffered land (83%), while Durham had approximately half of their fields buffered (48%). The only apparent conservation practices in these two counties are buffers in Orange and for producers to discontinue soybean fertilization in Orange County. Phosphorus fertilization could be discontinued, particularly in Orange County, where farmers should be following their soil test reports. Person County had more acreage cultivated (65%) than pastured/hayed (35%). Conservation tillage represents 59% for all agricultural lands (both pasture and cultivated); this means that conservation tillage is used on almost all cultivated fields for all crops. Erosion rates are under T at 1.96 t ac -1 yr -1 and soil test P is within the lower range of high (68). Nitrogen rates for all crops are within or below the expected N fertilization rate range. Fertilizer phosphorus rates most probably exceed soil test results, particularly for tobacco as the average application was 100 lbs of P ac -1 yr -1. Seventyfour percent of the agricultural lands in Person are buffered. The results suggest that only two conservation practices are available: additional riparian buffers and P fertilization based on soil tests. 50

55 BUDGET Description Budget ($) Spent ($) Salaries 20, , Fringe 3, , Total Personal Costs 23, , Supplies and materials 3, , Travel 4, , Current services 155, , Fixed charges Total direct costs 185, , Total indirect costs 18,575 18, Total costs 204, , REFERENCES Cahill, S.L., D.L. Osmond, R. Gehl, D. Hardy, and C. Crozier Soil Facts: Starter Phosphorus Fertilizers in North Carolina, AG W. Monroe, J. and A.L. Finkner, Handbook of Area Sampling. Chilton Co., Philadelphia, New York. Johnson, A.M. and D.L. Osmond Accounting Method for Tracking Relative Changes in Agricultural Phosphorus Loading into the Tar-Pamlico. With concurrence and consent of the Phosphorus Technical Advisory Committee. October 21, The N.C. PLAT Committee North Carolina Phosphorus Loss Assessment: I. Model Description and II. Scientific Basis and Supporting Literature. North Carolina Agricultural Research Service Technical Bulletin 323, North Carolina State University, Raleigh, NC. Osmond, D.L., L. Xu, N.N. Ranells, S.C. Hodges, R.Hansard, and S.H. Pratt Nitrogen Loss Estimation Worksheet (NLEW): An Agricultural Nitrogen Loading Reduction Tracking Tool. In Optimizing Nitrogen Management in Food and Energy Production and Environmental Protection: Proceedings of the 2nd International Nitrogen Conference on Science and Policy. Scientific World:1. SAS SAS/STAT guide for personal computers, Version 6 Edition. SAS Institute Inc., Cary, NC. 373 pp. 51

56 APPENDICES Appendix 1: Training Schedule 2008 NEUSE RIVER BASIN WORKSHOP Raleigh, NC Tuesday, October 14 Welcome and Overview Purpose of Project Kathy Deanna Osmond, NCSU Photos Using old and new How to use 2000 information Kathy What to do with new photos field numbers drawing Questionnaire Review Definitions Deanna -Land Use definitions -Drainage Directions -Buffers -Sediment Basin/Ponds -Water Control Structures Completing Form Grid Map and Drawing Field Kathy Kate ---- L U N C H ---- Soil Sampling - Inside Kathy How to collect 52

57 Packaging and Sending to Office Slope - Inside Kate How to Use Clinometer Slope Length (GPS) and Receiving Slope West only Fieldwork Outside Discussion Deanna Drainage Directions, Buffers, and More Slope and Soil Sampling - Outside Assignments Deanna/Kate/Kathy Kathy/Kate Appendix 2. Press Release Study to Confirm Nitrogen Reduction by the Agricultural Community in the Neuse River Basin The Neuse Best Management Practices Survey will be conducted by the North Carolina Agricultural Statistics Service for North Carolina State University. This survey will collect information about agricultural practices such as fertilizer use, controlled drainage, and riparian buffers from producers in the Neuse River Basin. The agricultural community exceeded the goal of 30% nitrogen reduction as of 2003 by joining Local Area Committees. These committees used a nitrogen accounting tool to track reductions in nitrogen from the use of best management practices. The objective of the Neuse Best Management Practices Survey is to reconfirm the results of this tracking tool. North Carolina farm operators in the study will be contacted by interviewers to collect the information from October 2008 through January Individual operator information will be confidential. Published results will be available winter of 2009 at 53

58 54

59 Project 450 Neuse River Basin Best Management Practices Survey 2008 East Version Latitude 114 Longitude 115 County Sample Field Name of Operator Address City, NC Zip Telephone Purpose of survey - This survey is designed to help farmers add more fl e xibility to the Best Management Practices (BMPs) required in the Neuse river basin. The program will develop a baseline of nitrogen and phosphorus use, track nitrogen and phosphorus reduction and demonstrate what type of BMPs farmers currently utilize. By law, your response will remain confidential. It will only be used in combination with other reports to summarize the results for the Neuse river basin. The results of this survey will be available at the end of Land Use of Field 1. agricultural 4. agricultural to developement 7. hunting 2. woods/waste 5. idle 8. CRP/CREP 3. game management 6. wildlife planting 9. wetland 10. Other (specify) How many acres are in the field?... 1a. Is this field leased, rented, or used rent free? 1 Yes 3 No Ac *Enumerator note: Draw the sample field on the inserted diagram. Mark the crest of the field and the drainage directions. Indicate the nearest ditch, stream, or river, water, control structures, along with the vegetative buffers on the diagram. If factors of the drainage directions are the same, do not separate. 2. Now I would like to ask some questions about the crops planted on this field in the fall of 2005 and spring and summer of Planting Crop Month Was this Was Date Date Cover Season and Planted a Cover Conservation of Harvest Crop Killed Crop Code (1=Jan,...12=Dec) Crop? 1 Tillage Used? 2 (mm/dd/yy) (mm/dd/yy) Fall of 2007 (Circle one.) Wheat, Oats, Rye, Barley, Triticale 211 Yes No Yes No Spring/ Summer 2008 Crop Yes No Cover Crop - Crop grown in the fall and winter to protect the soil from wind and water erosion. Cover crops are usually small grain crops that are either killed with herbicides or plowed down prior to spring planting. 2 Conservation Tillage - Tillage method that will leave a minimum of 30% of the soil surface covered by residue following planting. 2a. If hayland or pastureland in this FIELD,was it used anytime during the past year to graze animals?... Yes -1 (go to 2b) No -3 (go to 3) 226

60 2b. For this FIELD, record the type of livestock grazed, the average number of livestock grazed, and the average number of days grazed per year. Type of Livestock (Check all that were grazed in THIS field.) Cattle (cows, calves, bulls, and all other cattle) Horses Average Number Grazed (Head) Average Number Days Grazed Per Year Goats Sheep Other (specify: ) Other (specify: ) Has a soil test been completed on this field in the last 3 years?... Yes -1 (go to 3a) No -3 (go to 3c) 3a. Do you have a copy of the soil test available?... Yes -1 (go to 3b) No -3 (go to 3c) 3b. Copy the P-index from latest soil test (go to 4)... 3c. With your permission, I will collect soil samples from this field after harvest.your name will be given to the NCDA soil lab so that the results of the free soil test can be sent to you. Will that be all right?... Yes -1 No -3 Sample ID 850 Farm ID Lime (if applied in last 12 months). t/ac mo yr 200

61 4. Were COMMERCIAL FERTILIZERS applied to this field for the 2008 crop year? (Include custom applied fertilizer.) (Fall of 2007 through the Summer of 2008.)... Yes -1 (continue) No -3 (go to item 5) Crop Crop Code 310 Materials Used (Enter percentage analysis or actual pounds of plant nutrients applied per acre.) N Nitrogen 311 P 2 O 5 Phosphate K 2 O Potash Quantity Applied per Acre (leave blank if actual nutrients were reported) 314 Used Material Code 1 Pounds 12 Gallons 15 Tons 19 Pounds of actual nutrients 315 Month of Application [Enter Code.] 316 How was this applied? [Enter Code.] January 2 February 3 March 4 April 5 May Codes for Column 6 6 June 11 November 7 July 12 December 8 August 9 September 10 October Codes for Column 7 1 Injected 2 Incorporated within 48 hours 3 Incorporated between 48 hrs and 4 weeks 4 Incorporated between 4 weeks and 3 months 5 Surface Application

62 5. Was MANURE applied to this field for the 2008 crop year? (Fall of 2007 through the Summer of 2008)... Yes -1 (continue) No -3 (go to item 6) Crop Crop Code 410 Materials Used (Enter percentage analysis or actual pounds of plant nutrients applied per acre.) N 411 Nitrogen P 2 O 5 Phosphate 412 Quantity Applied per Acre (leave blank if actual nutrients were reported) 414 Used Material Code 1 Pounds 12 Gallons 15 Tons 19 Pounds of actual nutrients 415 Month of Application [Enter Code.] 416 How was this applied? [Enter Code.] Major Source of Manure [Enter Code.] Codes for Column 6 1 January 7 July 2 February 8 August 3 March 9 September 4 April 10 October 5 May 11 November 6 June 12 December Codes for Column 7 1 Injected 2 Incorporated within 48 hours 3 Incorporated between 48 hrs and 4 weeks 4 Incorporated between 4 weeks and 3 months 5 Surface Application (liquid or dry broadcast) Codes for Column 8 1 Broiler - house litter 7 Hogs - lagoon liquid 2 Broiler - stockpiled litter 8 Hogs - lagoon sludge 3 Dairy - lagoon liquid 9 Turkey - house litter 4 Dairy - lagoon sludge 10 Turkey - stockpiled litter 5 Dairy - scraped manure 11 Other 6 Poultry layer - lagoon liquid 5a. (If, hay was reported in item 5 table), was the harvested hay used for livestock feed? 1 Yes 3 No Does this field have a water control structure?... 1 Yes (continue) 3 No (go to item 7) 6a. How much of this field is affected by the water control structure?... 6b. Spacing (feet)... 6c. Depth (inches)... 6d. Month(s) boards placed (or put in )... (Circle all that are applicable.) Jan Feb Mar Apr May June Jul Aug Sep Oct Nov Dec 6e. Month(s) boards removed (or pulled out )... (Circle all that are applicable.) Jan Feb Mar Apr May June Jul Aug Sep Oct Nov Dec 7. Does this field have tile drainage?... 1 Yes (continue) 3 No (go to item 8) 7a. How much of this field is affected by the tile drainage?... 7b. Spacing (feet)... 7c. Depth (inches) % % OR OR Acres ft. in.. Acres ft. in.

63 8. How many drainage directions are in the field? 1 (Complete Table A) 2 (Complete Tables A+B) 3 (Complete Tables A+B+C) 810 TABLE A - First Drainage Direction in Field 9. What type(s) of buffer is between this field and the nearest ditch, stream or river? (Record the distance in feet using 5 foot increments.) none shrub/tree buffer... vegetative buffer (not shrub/tree)... a. How much of the field is affected by either the vegetative and/or shrub/tree buffer?... b. Receiving Slope width (in field)... (Check one.) 0-9 feet (1) feet (4) feet (7) feet (2) feet (5) feet (8) feet (3) feet (6) 300 or more feet (9) c. Is there a sediment basin in the drainage area?... Yes -1 No -3 d. Is there a pond in the drainage area?... Yes -1 No ft. ft. % OFFICE USE C = 511 LS = 512 K = R = P = 515

64 TABLE B - Second Drainage Direction in Field 10. What type(s) of buffer is between this field and the nearest ditch, stream or river? (Record the distance in feet using 5 foot increments.) none... shrub/tree buffer... vegetative buffer (not shrub/tree)... a. How much of the field is affected by either the vegetative and/or shrub/tree buffer? ft. ft. % b. Receiving Slope width (in field)... (Check one.) 0-9 feet (1) feet (4) feet (7) feet (2) feet (5) feet (8) feet (3) feet (6) 300 or more feet (9) c. Is there a sediment basin in the drainage area?... Yes -1 No -3 d. Is there a pond in the drainage area?... Yes -1 No OFFICE USE C = 611 LS = 612 K = R = P = 615

65 TABLE C - Third Drainage Direction in Field 11. What type(s) of buffer is between this field and the nearest ditch, stream or river? (Record the distance in feet using 5 foot increments.) none... shrub/tree buffer... vegetative buffer (not shrub/tree) ft. ft. a. How much of the field is affected by either the vegetative and/or shrub/tree buffer?... % b. Receiving Slope width (in field)... (Check one.) 0-9 feet (1) feet (4) feet (7) feet (2) feet (5) feet (8) feet (3) feet (6) 300 or more feet (9) c. Is there a sediment basin in the drainage area?... Yes -1 No -3 d. Is there a pond in the drainage area?... Yes -1 No OFFICE USE C = 711 LS = 712 K = R = P = 715

66 12. What is the hydrologic condition? (If the field is under conservation tillage or hay, do not answer.) 811 Conventional tillage good poor... Pasture good fair poor Do you consider farming your primary occupation?... Yes -1 (go to 14) No -3 (go to 13a) 13a. If no, which source do you consider your farm income to be?... (Check one.) 1 secondary source of income 2 minor source of income 3 none 14. Do you follow a nutrient management plan?... Yes -1 (complete 14b and 14c then go to 15) No -3 (complete 14a then go to 15) 14a. Who makes the commercial fertilizer recommendations?... (Check all that apply.) 1 Fertilizer Dealer 2 Paid Consultant 3 NRCS 4 Extension 5 Friend or another farmer 6 Self 7 Other (specify) 8 No Commercial Fertilizer Applied 14b. Which of the following are included in the nutrient management plan?... (Check one.) 1 animal waste only 2 commercial fertilizers only 3 both animal waste and commercial fertilizers 14c. Who writes the nutrient management plan?... 1 Fertilizer Dealer 2 Paid Consultant 3 NRCS 4 Extension 5 Friend or another farmer 6 Self 7 Other (specify) 15. Who applies your nutrients?... (Includes all applications of animal waste and commercial fertilizers.) (Check all that apply.) 1 Fertilizer Dealer 2 Friend or another farmer 3 Self 4 Other (specify) 16. Results of the survey will be available at Predominant soil mapping unit for this field...officeuse Respondent s name Phone Date Respondent Response Code Enum. Eval. 1-Op/Mgr/Ptr 2-Sp 3-Other S/E Tel Int 7-Ref

67 Project 450 Neuse River Basin Best Management Practices Survey 2008 West Version Latitude 114 Longitude 115 County Sample Field Name of Operator Address City, NC Zip Telephone Purpose of survey - This survey is designed to help farmers add more fl e xibility to the Best Management Practices (BMPs) required in the Neuse river basin. The program will develop a baseline of nitrogen and phosphorus use, track nitrogen and phosphorus reduction and demonstrate what type of BMPs farmers currently utilize. By law, your response will remain confidential. It will only be used in combination with other reports to summarize the results for the Neuse river basin. The results of this survey will be available at the end of Land Use of Field 1. agricultural 4. agricultural to developement 7. hunting 2. woods/waste 5. idle 8. CRP/CREP 3. game management 6. wildlife planting 9. wetland 10. Other (specify) How many acres are in the field?... 1a. Is this field leased, rented, or used rent free? 1 Yes 3 No Ac *Enumerator note: Draw the sample field on the inserted diagram. Mark the crest of the field and the drainage directions. Indicate the nearest ditch, stream, or river, water, control structures, along with the vegetative buffers on the diagram. If factors of the drainage directions are the same, do not separate. 2. Now I would like to ask some questions about the crops planted on this field in the fall of 2005 and spring and summer of Planting Crop Month Was this Was Date Date Cover Season and Planted a Cover Conservation of Harvest Crop Killed Crop Code (1=Jan,...12=Dec) Crop? 1 Tillage Used? 2 (mm/dd/yy) (mm/dd/yy) Fall of 2007 (Circle one.) Wheat, Oats, Rye, Barley, Triticale 211 Yes No Yes No Spring/ Summer 2008 Crop Yes No Cover Crop - Crop grown in the fall and winter to protect the soil from wind and water erosion. Cover crops are usually small grain crops that are either killed with herbicides or plowed down prior to spring planting. 2 Conservation Tillage - Tillage method that will leave a minimum of 30% of the soil surface covered by residue following planting. 2a. If hayland or pastureland in this FIELD,was it used anytime during the past year to graze animals?... Yes -1 (go to 2b) No -3 (go to 3) 226