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11 Potential Uses of the NR} In State and Local Decision Making Chris ~ Johannsen Many people have been impressed by the beautiful landscapes of Missouri and they soon find that there are many interesting contrasts. Missouri is indeed a state where the north meets the south and east meets the west in terms of geology, soils, crops, climate, and people. Looking at these different landscapes, it is sometimes difficult to determine if anything is wrong. Yet, when something is very wrong, even the untrained eye can observe it. Missouri has a very serious soil erosion problem. Missouri ranks second in the country behind Tennessee in rates of erosion from cropland acres e Its erosion rate is over 10 tons of soil loss/cropland acre, which amounts to nearly 160 tons of soil loss each year (USDA, 1981). During 1982, with the heavy spring rains, the estimated soil loss was nearly 22 tons/acre (Johannsen, 1982). That phenomenon was repeated this last spring-- indeed, the estimate increased to over 25 tons/acre. The northern part of Missouri has experienced a loss of cattle production operations resulting in many pas- turelands being plowed and put to row crops. In Atchison County alone, satellite images recently documented that 70 percent of the county area is now in row crops. This is in contrast to 5 years ago, when less than half the county was in such crops. During the past 5 years, many counties in northern Missouri have lost from 35 to 50 percent of their pastured areas to row-crop production. The Deep Loess Hills in northwest Missouri have experienced erosion rates as high as 50 tons/acre/year. Many road ditches have been completely silted in. It is interesting to note that the county highway engineers were some of the first to complain about the ditches 296
297 being filled; they did not have enough money budgeted to remove the materials. In the west central part of the state, the productive soils are developed on acid shale materials with loess or windblown topsoil. This area, called the Cherokee Prairie, has many severe erosion problems, but it receives little publicity because its erosion rates are not as dramatically high as those of the northwest portion of the state. This nearly level to gently sloping area is intensively farmed and, with low water intake due to slightly heavy textured surface soil, erosion rates are normally high. The loss of topsoil and exposure of some acid subsoils will be a very serious problem to the agricultural economy of this area with continued erosion rates. Missouri's Ozark region has bottomland areas that are usually row-cropped. Many of the upland areas have very shallow soil with little topsoil. Over 2 million acres of forest and brushland have been aerial sprayed with herbicides or removed by bulldozer and then seeded to grass. Some of these areas have been intensively grazed, resulting in severe erosion. Any erosion is a major problem since the topsoils are thin and subsoil materials are usually very infertile. The Bootheel area of the state contains soils that are formed in alluvium, either on floodplain or terraced positions. The soils are deep and vary in texture from clay to loamy sands. The problem receiving increasingly more attention in this area is wind erosion. SEEKING A SOLUTION In 1981, the Soil Conservation Service (SCS) of the U.S. Department of Agriculture (USDA) held a meeting with state and federal resource agencies, farm organizations, and the University of Missouri to assess the resource information needs of these groups. As a result, Missouri expanded the data collection format of the proposed state- wide National Resources Inventory (NRI) to include more detailed wildlife habitat and timber resource data. Additionally, at the request of the participants, the data were put in a geographically referenced data base to display queries in graphic, map, and tabular formats. The Geographic Resources Center (GRC) at the University of Missouri-Columbia was contracted to develop the NRI geographic data base.
298 ls.s~h W4~.,~- ~' 74~ 1 ~,,~-,t It, 1 ~ ~ 7;g ant' ·tS4't** 4 AIDS ink. .-,,tJ~ t 4;~. `4 . · ~ · , .t ·;q,~, ·. ~ . ~. .~r - ,.;~1i ^,,tSj: i. _. ~_4.~ ·a~ ' ~ ~ * ; ~..;.1. .. .'...' 41 ...^ .1 N - / a: FIGURE 1 Primary sampling unit (PSU) locations in Missouri. The samples selected for the 1982 NRI in Missouri totaled over 13,000 primary sampling units (PSUs), shown in Figure 1. These represented a sample of about 4 percent and translated to 150 PSUs for an average Missouri county. Since three sample locations were selected statistically within each PSU, data were collected from over 39,000 locations by SCS soil scientists and district conservationists, providing the most detailed data ever collected on Missouri's soil and water resources (Johannsen, 1984). The development of the PSU data base was divided into four steps: data entry and verification, digitizing PSU locations, digitizing ancillary data, and implementation of a retrieval and display system (Johannsen et al., 1984). Data entry and verification will be a continuing process until about 15,000 PSU points are collected and
299 entered into the data base. To date, approximately 13,000 PSUs have been entered into the system. Additional samples are being obtained to provide county-reliable data for more than 25 of Missouri's 114 counties. The field data worksheets were entered with a specially designed data entry program through the use of form-drive interactive mechanisms. Every form displayed on the operator's terminal was constructed to look just like its corresponding section on the original worksheet. Twenty- one screen forms are required to cover an entire PSU worksheet. When a form has been entered, the next one is prompted automatically. Filled forms are easily recalled for editing or correction. The individual PSUs were located on Geological Survey 7.5-minute quadrangle sheets and digitized to describe accurately their locations in Universal Transverse Mercator (UTM) coordinates for use by the data retrieval and display system. In addition, seven statewide maps were digitized for inclusion in the data base; they serve as supplemental geocodes for improving the analytical and reporting functions of the systems. The digitized maps include general soils, county boundaries, forest cover, zoographic regions, fish-fauna regions, Major Land Resource Areas, and hydrologic units. The maps were digitized manually. After capturing the line segments, the segments were cycled to produce polygons that can be displayed with the locations of selected PSUs on a raster or vector graphics device. A relational data base management system integrates the PSU field data, PSU locations, supplemental attribute geocodes, and supplemental attribute boundary files (Johannsen et al., 1984). The PSU field data file and supplemental attribute file are used to create a retrieval file that is searched to answer all queries. The PSU location file and supplemental attribute boundary file are primarily used to put retrieval results into graphic format on a display monitor or plotter. All search results can be reported in tabular or graphic formats. USING THE PSU DATA BASE The Soil Conservation Service (SCS) and the Office of Soil and Water Conservation Programs of the Missouri Department of Natural Resources are currently requesting specific illustrations and results from the Missouri PSU data base. In August 1984, Missouri voters approved a
300 sales tax of 0.1 percent to provide state funds for a cost-sharing program as an incentive to landowners to use conservation practices. The funds will be administered through the Department of Natural Resources, with SCS providing technical assistance. Funds are to be used when USDA/Agricultural Stabilization and Conservation Service (ASCS) funds are not available for erosion control practices. Therefore, soil and water districts are cooperating with county ASCS committees in the program. The funds will be distributed on the basis of a formula that provides a portion to each district, with the remainder allocated according to the percentage erodible cropland acreage of the state total. Figure 2 shows the distribution of cropland PSUs and the location of cropland PSUs with losses greater than 10 tons/acre/ year. The latter was determined using the Universal Soil Loss Equation (USLE), which was calculated from the data collected in the field for each point location within a PSU. The data could be requested on the basis of soil loss tolerance limit (T value), twice the tolerance (2T), or any specific erosion level entered by the user. The flexibility of the retrieval of the statewide data is shown in Figure 3, where the user wanted to see row-crop and small-grain PSU locations. The locations of a specific crop can also be retrieved. For example, the location of soybeans was requested by the State Extension Agronomy Specialist with responsibility for that crop. Warm season grasses (see Figure 3-C) are of increasing interest to wildlife specialists, while the distribution of forests (see Figure 3-D) that are being grazed are of interest to the resource professionals working with the timber industry. Maps and illustrations are being provided to each SCS planning area such as those shown in Figure 4. Other agencies with different area boundaries, such as the Extension Service and ASCS, can request illustrations by providing an organizational map or listing of counties to the Geographic Resources Center. The data can also be presented in a table (such as the soil loss by land capability class in Table 1) or by pie chart (such as Figure 5, which shows the distribution of different crops in SCS Area 3). Additionally, bar charts like those shown in Figure 6 can be developed for comparing data between counties or any categories selected by the user. County-reliable data have been collected for about 15 percent of Missouri's counties. One example is Monroe \
301 I;., , <go% O_9OX 50-70% 0-5096 A. Cropland PSUs with county boundaries B. Cropland distribution C. Cropland with greater than 10 tons/acre/year soil loss FIGURE 2 Cropland PSUs in Missouri with information presented in different formats.
302 A. Row crop ~ _ ~ :~: _ C. Forage with warm season grasses 9_) B. Small grain D. Forest and grazed forest FIGURE 3 Sample statewide data retrieved by PSU location, specifying land cover or land use categories.
303 A. PSU locations B. Cropland PSUs :!. :;. :.. . ~ . C. Row crop PSUs D. Row crop with greater than 10 tons/acre/year soil loss FIGURE 4 Use of NRI data, SCS Area 3, northeast Missouri.
304 TABLE 1 Average Soil Loss and Land Use Categories by Soil Loss Tolerance (T) for Area 3 in Northeast Missouri Average Soil Loss Soil Lossa Acres Land Use Tolerance (Tons/Acre) (100) Cropland <T2. 426,317 T to 2T5.084,017 >2T18.7911,869 All11.9922,203 Grassland <T1.208,339 T to 2T5.391,648 >2T16.481,996 All3.9911~983 Forest IT0.635,204 T to 2T4.76583 >2T24.90680 All3.066,467 Grazed forest <T1.281,016 T to 2T5.13394 >2T25.93562 All7.951,972 Nongrazed <T0.464,188 forest T to 2T3.95189 >2T20.43118 All1.044,495 Urban All0.0045 Other All9.87783 aCalculated by Universal Soil Loss Equation using data collected from PSU locations. SOURCE: 1982 NRI.
305 - - / / Grasslands (28.88%) f: I\ Fo rest la nd ( 1 5.5 9% ) Cropland (5353%} Other (1.89%) Urban (0.11%) FIGURE S Distribution of cropland by a specific crop in Area 3. County (see Figure 7), located in northeast Missouri. The data can be retrieved by watershed boundaries or by cropland classes and specific conservation treatment. The query for information is additive so that the user can request multiple conditions from the data. Individual county displays will only be made for counties with county-reliable sample points so that information provided is not misused. Table 2 illustrates specific data for Monroe County, Missouri, showing the amount of row-crop acreage on different land capability classes. This county may want to target its funds to assist either the most productive lands or the areas that should be removed from cropland production. All the soil and water conservation districts are in the process of developing 5-year plans. Information from all available sources and the NRI data will be used to establish priorities for starting conservation. All districts have funds available to help implement their plans--a resource which increases emphasis on developing sound plans. The district conservationist and local extension specialist, a district supervisor by virtue of the position, are working together to write the plans with assistance from their elected supervisors. There are many possibilities for display and use of the NRI data in Missouri. Many uses will only be known
306 = _ i Tons/Acre AS 05 99 97 75 73 63 37 27 21 11 03 45 01 COU NTY FIGURE 6 Average soil loss for row crops for selected counties in northeast Missouri. Key: Average of all 13 counties, A3; Knox, 05; Shelby, 99; Scotland, 97; Schuyler, 75; Randolph, 73; Rails, 63; Monroe, 37; Marion, 27; Macon, 21; Lewis, 11; Clark, 03; Pike, 45; Adair, 01. as people become familiar with the data base. A recent request for the locations of irrigated lands by one of the state agencies, for example, brought an additional appreciated response when it was learned that information on the source of the water could also be provided. SUMMARY AND CONCLUSIONS The data base management system established for analyzing Missouri's NRI data serves as a model for query, display, and application of these data in other states. Further data collections of this magnitude will likely consider a geographic information system approach in planning data collection and use of results. Missouri is in the initial stages of using the results from this system. Many uses of the products have not yet been envisioned. The flexibility of retrieving the results in formats requested by the user will lead to
307 1 1 A. PSU locations 1: B. Cropland PSUs - C. Row crop PSUs D. Row crop with greater than 10 tons/acre/year soil loss FIGURE 7 Use of NRI data for Monroe County (northeast Missouri) with county-reliable samples.
308 TABLE 2 Average Soil Loss and Acreage by Land Capa- bility Class for Monroe County, Missouri Land Capability Class PSU Subclass Points Average Soil Loss Acres (Tons/Acre) (100) II e1249.56731 w865.71519 III e11712.61731 w115.3765 IV e2813.86172 VI e231.0516 Total 9.952,234 SOURCE: 1982 NRI. many additional cooperative efforts among resource agencies that are trying to stop the deterioration of Missouri's soil resource and its influence on vegetation, water, and wildlife resources. REFERENCES Johannsen, C. J. 1982. Soil erosion of Missouri: An inventory. Pp. 13-15 in Soil and Water Conservation: The Principle and the Practice. Special Report 290. Columbia: Agricultural Experiment Station, University of Missouri. Johannsen, C. J. 1984. Missouri's National Resources Inventory. University of Missouri-Columbia Agronomy Technical Report 2(11):5-7. Johannsen, C. J., J. M. Pan, T. W. Barney, and G. T. Koeln. 1984. A data base management system for Missouri's National Resource Inventory. Pecora IX Symposium, Sioux Falls, S. Dak., Oct. 12-15. USDA (U.S. Department of Agriculture). 1981. Soil and Water and Related Resources in the United States, 1980 RCA Appraisal, Part I. Washington, D.C.: U.S. Department of Agriculture.
309 Discussion Max Schnepf Some states now realize the wealth of information they possess from the 1982 National Resources Inventory (NRI) data. Missouri is a good example, as Johannsen's paper points out. Other states and local governments have yet to recognize how flush they are in terms of the value of the NRI data. OVERALL OBSERVATIONS The NRI is a national assessment tool, first and foremost, and while the 1982 NRI is accurate to the level of Major Land Resource Area (MLRA), there are real limitations to its use at the county level and, for some purposes, even at the state and national levels. The 1977 NRI raised questions about the value of the data to individuals and agencies at the state and local levels. Many bought into the 1977 NRI with their time and effort and apparently wanted more out of the assess- ment than they felt they received. As a result, data accurate to the county level became an objective of the 1982 NRI. When budget considerations forced abandonment of that objective, the compromise was data reliable to the MLRA level. A number of states--Missouri, Louisiana, and Kansas, for example--opted to spend additional funds to achieve county-level accuracy in all or selected counties, and about 200 counties now have reached this goal. Several hundred more are in the process of collecting data to achieve this level of accuracy. The fact that MLRA boundaries do not coincide with county boundaries poses problems for use of the data at the county level. In some cases, as Johannsen points out regarding Missouri, county-level information can be interpolated from MLRA data, but the accuracy of that interpolation is often questionable. It will be difficult to avoid some misuse of NRI data, particularly at local levels, where the view surely will be "any information is better than no information." Comparison of 1982 NRI data with 1977 NRI data is possible in many cases at the state and national levels because the same PSUs (primary sampling units) sampled in 1977 were sampled again in 1982. In other cases, the data are
310 not comparable because the methodology changed. An example is the case of urban and built-up uses of land. Because people want time-series data, the possibility exists in these latter cases of comparing apples to oranges. The fact that the NRI excludes federal lands is a real shortcoming for state and local users in areas where there are extensive federal land holdings. Another problem is that the accuracy of the NRI data varies. For example, data on riparian land and wildlife habitat diversity are so limited that they are not accurate at the state level and may not even be so at the national level. Lastly, NRI data are of little use in dealing with relatively site-specific situations--for example, water quality problems emanating from livestock or poultry operations. S TATE AND LOCAL USES OF THE NRI How has the NRI been used thus far by state and local decision makers? Beyond the experience in Missouri, information received from a number of directors of state soil and water conservation agencies and Soil Conservation Service (SCS) state conservationists paints a varied pic- ture, for several reasons. First, the preliminary nature of the NRI data in some states has generated a cautious attitude among some administrators toward releasing the information and encouraging its use. Second, some states have created more elaborate data bases of their own, which are being used in conjunction with or in lieu of the NRI. Missouri is unquestionably a leader in making use of the NRI. But there are other good examples of the data's use by state and local decision makers. Louisiana has perhaps been the most ambitious in developing and using NRI data. From the outset of the 1982 effort, the state pursued a much more elaborate sampling scheme that ensured data accurate to the county or parish level. A number of state and federal agencies in Louisiana are now using that data, as are some consultants and scientists at Louisiana State University (LSU). For example, the Louisiana Division of Water Pollution Control has used the information to identify the general location of soils with high erosion rates. The agency uses this data in its nonpoint source program to locate potential water quality problem areas resulting from soil erosion, and it recently expanded this effort to locate cropland and
311 forested areas where erosion is serious and has the potential to pollute surface waters. The agency also uses the NRI data to locate areas with different crops growing on lands with serious erosion. This will help officials identify what water pollution problems might result from the use of fertilizers and pesticides on these crops. The Louisiana Soil and Water Conservation Committee used the NRI data to help conservation districts develop workload analyses for staffing and budgetary needs. The NRI data are also used by the Department of Transportation and Development in its water quality management basin reports, by the Water Resources Studies Commission to identify potentially serious groundwater quantity and quality problems, by the Louisiana Department of Agriculture in selected public information programs, by the Corps of Engineers to identify land cover/use and soil erosion in watersheds of reservoirs, and by the Agricultural Stabilization and Conservation Service to estimate soil erosion on marginal lands by parish and MLRA. The Department of Civil Engineering at LSU is using the NRI information in a pilot project at its Remote Sensing Laboratory to verify Landsat data. The LSU Department of Geography and Anthropology is using NRI data to develop a proximal mapping technique to show general locations of selected land use/cover and conditions of soil resources in the state. And LSU's Department of Agricultural Economics uses the NRI data to identify and analyze cropping patterns and yields by soil type in project areas. In other states, use of the NRI data appears more limited: · Indiana is completing a description of soil erosion problems in the state by the Governor's Soil Resources Study Commission. · Alabama's Soil and Water Conservation Committee is developing a long-range soil and water conservation program for the state. The committee is seeking legislative support for an $8-million annual state appropriation for 20 years to fund this program. ~ Nebraska's Natural Resource Commission is using the NRI in much the same fashion as Indiana and Alabama--to determine the magnitude of soil and water conservation problems in the state. The agency is also attempting to reorganize the data on the basis of its natural resource
312 districts, which follow hydrologic boundaries. It intends to allocate cost-sharing monies to the districts using the NRI data. · Georgia is producing an information piece that uses NRI data to characterize the state's soil and water problems. · Wisconsin is evaluating progress in soil erosion control and identifying priority areas for erosion control implementation projects. · Illinois agencies are using the data as a basis for writing county and state "T by 2000" plans, which include treatment, personnel, financial, and extension needs. · Kentucky is working on long-range soil and water conservation plans at the state level and in about half of the state's 121 conservation districts. The data were also used to establish parameters for development of a statewide soil erosion assessment computer model. And state officials used NRI information when seeking the governor's support for agricultural land protection initiatives. · Kansas is developing a state water plan using NRI data. The NRI information is also being used to allocate state cost-sharing monies, and Kansas State University researchers now have tables of preliminary data available for research purposes. Among other users of NRI data at state and local levels are the Agricultural Stabilization and Conservation Service, the Tennessee Valley Authority, and a number of researchers, several of whom report on their work in this volume. Some private groups, including the Texas Goat Raisers Association, have also requested the data. POTENTIAL USES OF NRI DATA The number of uses of NRI data in land and water planning is nearly endless. It is surely safe to say that the potential far exceeds what has been done to date. For example, the fact that the NRI data tapes can be meshed with the Soils-5 data tapes creates a number of analytical possibilities. As Johannsen mentions in his paper, there are possibilities for digitizing the NRI data and incorporating that data into geographic infor- mation systems. ~ ~ ~ - has enormous possibilities for planning and decision making at state and local levels. Ana outt~na NRI data into, mic~roc,omn',t~r`:
313 Obviously, what is needed most if the NRI data are to be used effectively and efficiently by state and local interests is a good educational effort. Thought must be given to creative ways of spurring interest in the NRI data, and then potential uses need to be advertised widely among state and local officials. To date, there has been limited effort along these lines. All state offices of SCS have money in their 1984-1985 budgets to produce publications on the NRI. Many are assembling a technical document as well as a more popular brochure. The agency also has an on-line computer query system linking its Washington, D.C., office with its state offices. The considerable analytical work going on as a result of this link will benefit the states. In addition, SCS now has designated representatives in its four technical centers who are working with the states on the use of NRI data. Some attempts are also being made within states to make potential users aware of the NRI data and encourage use of the information. Minnesota SCS officials, for example, recently sponsored a day-long seminar for federal, state, and local agencies and groups to acquaint them with the NRI and its use. Twenty-one agencies and groups were invited; 17 participated. In Kansas, SCS officials have discussed potential uses of the NRI at two meetings of that state's Agricultural Council, a group of farm- and ranch-oriented agencies and interest groups that meets monthly. Kansas and other states have also orchestrated broader publicity efforts via newspapers and other public media. CONCLUSION Three points seem worth making with respect to the future use of NRI information by state and local decision makers. First, SCS could do much to extend the value of the NRI by establishing a formal or informal work group at the national level to do some creative thinking about the potential uses, to make a laundry list of those possibilities perhaps, and to set some guidelines on the appropriateness and accuracy of the data for various uses. Second, the question of the need for and value of a broader national natural resource data base must be dealt with. The NRI information is of limited value in states with extensive federal land holdings. As the governor of
314 one western state reportedly lamented, "the NRI tells me a lot about the privately held land in my state, but it doesn't tell me a darn thing about my state." If people at state and local levels are encouraged to use NRI information, some in the West in particular are going to want and need a more extensive data base than the NRI provides. Moreover, if they do indeed want and need that information, they are not going to be greatly concerned about the turf battles that occur in Washington, D.C., whenever the subject of a national data base is raised. Third, as mentioned, many people at state and local levels bought into the NRI assessments in 1977 and 1982. Some still feel they are not getting as much out of those assessments as they should. As a result, pressure is likely to continue for data accurate to the county level in future NRIs. If the conduct of those assessments is to continue to rely on people at the state and local levels, some consideration must be given to accommodating their interests. The alternative is to devise an assessment process based on remote sensing or other technology that precludes the need for this state and local assistance.