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A Geographic Information System to Identify Areas forAlternative Crops in Northwestern Wyoming

J.A. Young, B.M. Christensen, M.S. Schaad, M.E. Herdendorf, G.F. Vance, and L.C. Munn*

Agriculture is the third largest industry in Wyoming after mining and tourism (R. Micheli, WyomingDepartment of Agriculture Director, pers. commun.). The Bighorn Basin, located in northwestern Wyoming,is one of the largest agricultural production areas of the state. This area accounts for 27% of the value ofcrops produced in Wyoming (Wyoming Agricultural Statistics Service 1998). The Bighorn Basin was devel-oped for agricultural use when irrigation was introduced into the area in 1905 with the completion of theBuffalo Bill Dam. Major crops currently grown in the Bighorn Basin include: spring wheat, barley, oats, drybeans, sugar beets, alfalfa hay, and corn.

One alternative for increasing profit margins of the Wyoming agricultural industry is through the intro-duction of new crops. Wallis et al. (1989) defines new or alternative crops as either crops new to a particularcounty, region or state, or as a crop that has been, or is being developed, from a plant that has never beencultivated for commercial production. Alternative crops such as cabbage, mint, pumpkins, squash, and grassseed have been cultivated in the Bighorn Basin, but are most often marketed for local consumption rather thanbeing commercially produced (J. Jenkins, Park County Cooperative Extension Agent, pers. commun.).

The study area is noted for producing 80% of Wyoming’s sugar beet and barley crops. Intense cultiva-tion, however, has resulted in reduced production and increased use of pesticides, tillage, and other manage-ment practices. The sugar beet nematode (Heterodera schachtii) has greatly reduced the yield of sugar beets,the highest value crop grown in the area. Crop rotation is one of the most effective cultivation practices usedto help control pests, including the sugar beet nematode (Gardner, 1994). Introduction of alternative crops tothe Bighorn Basin would aid in providing crop rotations, thus breaking disease cycles and pest infestation.

A tool that can be used to predict alternative crop growth is a Geographic Information System (GIS).GIS is “an organized collection of computer hardware, software, geographic data, and personnel designed toefficiently capture, store, update, manipulate, analyze, and display all forms of geographically referenced in-formation” (ESRI 1995). A GIS stores spatial data as data layers. These layers are defined as a set of fea-tures, each having both location and attributes. The advantage of GIS is attributed to its ability to spatiallyanalyze multiple data layers. This powerful tool allows decision-makers to simulate effects of managementand policy alternatives within a geographic area prior to implementation (Congalton and Green 1992).

OBJECTIVESThe Bighorn Basin of Wyoming is an agricultural community that relies heavily on the production of

staple crops. Production of alternative crops such as canola, buckwheat, and mint could provide new opportu-nities for agriculturalists to increase income possibilities and to break herbicide and pest cycles. This studyused a GIS to investigate the potential for cultivating new crops in the Bighorn Basin. Environmental traits ofthe basin (e.g., rainfall, temperature, and soil) influence where new or alternative crops could be produced.Maps developed in this project provide producers with possible alternatives to current practices in the Big-horn Basin. The objectives of this study were to: (1) develop a spatially-correlated database that includesenvironmental and climatic data; (2) develop a continuous soils layer for the Bighorn Basin study area; (3)determine crop growth parameters for 28 agricultural crops; and (4) combine growth parameters with environ-mental data to display and describe areas of potential alternative crop production.

*We express our appreciation to Dr. Renduo Zhang for his assistance in the geostatistical analysis and development of theclimactic data layers used in this study.

Reprinted from: Perspectives on new crops and new uses. 1999.J. Janick (ed.), ASHS Press, Alexandria, VA.

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METHODOLOGY

Site DescriptionThe Bighorn Basin is located in the northwestern corner of Wyoming (Fig. 1). The study area includes

parts of three different counties and is comprised of 760,000 ha. The area elevation ranges from 1220 to 1525m; this low elevation, relative to the rest of the state, results in the region having an average of 90–120 frost-free days (Western Regional Climate Center 1998).

The study area was delineated in the GRID module of ARC/INFO. The 1:24,000 USGS topographicquadrangle maps and the Wyoming State Land Cover Classification were overlayed onto the Park, Big Hornand Washakie counties. These coverages were clipped to the study area. Due to irrigation constraints, topo-graphic maps having a majority of slopes greater than 5% were eliminated. This resulted in the removal ofonly a portion of the topographic maps for the three counties. From these topographic maps, the quadrangleswith greater than 25% agricultural land were selected. A buffer of one quadrangle was placed around theentire study area to include smaller areas of agricultural land. This analysis resulted in the inclusion of 81quadrangles in our study area. Upon ground-truthing in May 1998, 22 of the quadrangles were excluded fromthe study area because they lacked either agricultural production potential due to topography or had insuffi-cient irrigation capabilities.

Soils DescriptionPublished soil survey data for the majority of the study area is unavailable; Washakie county soils have

been delineated, while Park and Big Horn counties have not been completed. In order to obtain soils informa-tion, a GIS simulation model was created to predict soil occurrence in the Bighorn Basin (Fig. 2). Bedrockand surficial geology covering the state of Wyoming was obtained from the Spatial Data and VisualizationCenter at the University of Wyoming (1998). These coverages were clipped to the study area. Soils series inthe Washakie County comprehensive soil survey were examined to determine bedrock and surficial geologycombinations upon which they occurred (Iiams 1983). These combinations, and combinations predicted fromother unpublished work in the region, were used to predict soils for the entire study area. The model wasapplied utilizing decision rules in Arc Macro Language (Munn and Arneson 1998). The predicted soils mapwas field checked and updated accordingly.

Weather RecordsEighteen weather stations exist both in and around

the study area (Fig. 3). These stations have collectedweather data for 30 years or longer (Western RegionalClimate Center, 1998). The weather station attributedata were used to create continuous weather patternsfor the basin; contour lines were extrapolated from thepoint data utilizing geostatistics. Environmental lay-ers developed from the weather station data includefrost-free days (80% probability), growing degree-days(base 5°C), annual precipitation, and August mean tem-perature. Geostatistics has proven to be advantageouswhen compared to other methods of extrapolation(Kravchenko et al. 1996). Semi-variograms of each en-vironmental attribute were plotted and cross-validationand kriging techniques were applied. Kriging resultedin a grid of each attribute with values placed at thenodes or intersections of the grid. This information wasimported into ARC/INFO and used to create continu-ous grid coverages of the four environmental layersshown in Fig. 3. Fig. 1. Study area location.

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Crop Growth ParametersThe crop growth parameters of 28 alternative crops were derived through documented sources; many

parameters were taken from Purdue University’s NewCrop Resource Online Program (Purdue University 1998).Other sources of information were obtained through the Cooperative Extension Publications from MontanaState University, University of Nebraska–Lincoln, and Colorado State University. These parameters werecompiled into one database for analysis. Table 1 illustrates crop growth parameters that were analyzed in theGIS database for buckwheat and canola potential production areas.

Fig. 2. Soils of the Bighorn Basin, WY.

Fig. 3. Environmental layers for the Bighorn Basin, WY.

WATER

Weather stations Study boundary

Frost-freeperiod (days)

71–7879–8687–9495–101102–109110–117

1283–14291430–15761577–17221723–18691870–20152016–2162

Growingdegree days(C)

13–1718–2122–2526–2930–3334–37

Annualprecipitation(cm)

15–161718192021

August meantemperature(C)

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Model FormationEnvironmental data were compiled into a GIS and analysis using map algebra was performed. The pa-

rameters queried included length of frost-free season, growing degree-days, annual precipitation, and averageAugust temperature. Areas with selected crop growth parameter combinations were displayed. A separatemap representing two alternative crops was created showing potential areas for its production. Each maputilized the specific requirements of the individual crop.

RESULTSSoils of the study area were a mosaic of 19 mapping units. Ground-truthing conducted in May 1998

confirmed that the soils map created in the simulation model was suitably accurate. Classification of only onesoil mapping unit required change. The creation of the soils data allows for the use of textural classes, pH, andwater-holding capacities in our alternative crop analysis. A large proportion of the study area consists of

Table 1. Crop growth parameters for buckwheat and canola.

Buckwheat Canola(Fagopyrum esculentum) (Brassica campestris)Warm season broadleaf Cool season broadleaf

Optimal temperature < 25°C 12–30°C, needs temp. below 25°C for flowering

Soil attributes Wide range of soils, no crusting, Non-crusting clay loam soils, medium prefers medium textured soils texture

Precipitation Sensitive to drought stress Dryland >30.5 cm annuallyFrost-free season Matures in 75–90 days, easily killed by frost > 90 daysMinimum temp. 0°C 5°CMaximum temp. Unavailable < 11 days >32°C in JulyGrowing degree-days 1200 days (base 5°C) 860–920 (base 5°C)

Fig. 4. Production potential for buckwheat and canola in the Bighorn Basin, WY.

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Torrifluvents, which is where a significant portion of the Bighorn Basin irrigated agriculture currently occurs.In an arid region, crop development commonly occurs in flood-plain soils.

Contour maps created from the kriging process are shown in Fig. 3. These contour maps are related tothe topography of the surrounding study area, i.e., with an increase in elevation there is a decrease in frost-freeperiod, a decrease in growing degree-days, an increase in precipitation, and a decrease in temperature. Thesemaps display frost-free period (80% probability), growing degree-days (base 5°C), annual precipitation, andAugust mean temperature.

Preliminary findings utilizing frost-free period and growing degree-days indicate that canola and buck-wheat can be grown in virtually all of the study area under irrigated conditions (Fig. 4). Canola productionrequires a frost-free period of 90 days or greater and a value of 920 or greater growing degree-days (base 5°C)or heat units. Buckwheat also requires a frost-free period exceeding 90 days, but needs 1200 growing degree-days. Figure 4 also displays the areas of potential dryland production of canola; the factors for frost-freeperiod and growing degree-days were used in addition to greater than 30.5 cm annual precipitation. There isless than 5% dryland agriculture production currently in the study area.

CONCLUSIONThe Bighorn Basin in Wyoming has potential for the introduction of many new or alternative crops,

though only two examples are described in this paper. As more of the environmental variables are createdthrough the use of geostatistical methods, a more accurate picture of potential alternative crops will emerge.A GIS provides an excellent means for exploring the possibilities of cultivating new crops. The process oflocating areas suitable for growth is rapid, once the necessary information is entered into the database.

The study area has a short growing season that lends itself to the cultivation of cool-season crops. Whilemany of the crops being investigated can be grown in the Bighorn Basin, the commercial yield of these cropsis uncertain. A crop yield model should be employed to predict if alternative crop production could competein the marketplace. An economic analysis of the feasibility of the growth of these new crops is also an areathat requires further analysis.

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and Wiley, New York.Gardner, J.C. 1994. Choosing among alternative crops. North Dakota Farm Research 50(2):3–5.Iiams, J.E. 1983. Soil survey of Washakie County, Wyoming. National Cooperative Soil Survey. U.S. Gov-

ernment Printing Office, Washington, DC.Kravechenko, A., R. Zhang, and Y.K. Tung. 1995. Estimation of mean annual precipitation in Wyoming

using geostatistical analysis. p. 271–282. In: H.J. Morel-Seytoux (ed.), Proc. 16th Annual AmericanGeophysical Union Hydrology Days. Hydrology Days Press: Atherton, CA.

Munn, L.C. and C.S. Arneson. 1998. Soils of Wyoming: A digital statewide map at 1:500,000-Scale. Agr.Expt. Sta. Rpt. B-1069. Univ. Wyoming, College of Agriculture, Laramie, Wyoming.

Purdue University—Center for New Crops and Plant Products. New Crop Resource Online Program. Online.Available: http://www.hort.purdue.edu/newcrop/. July 1998.

Spatial Data and Visualization Center. Wyoming Natural Resources Data Clearinghouse. Online. Available:http://www.sdvc.uwyo.edu/clearinghouse/. March 20, 1998.

Wallis, E.S., I.M. Wood, and D.E. Byth. 1989. New crops: A suggested framework for their selection, evalu-ation and commercial development. p. 36–52. In: G.E. Wickens, N. Haq, and P. Day (eds.), New cropsfor food and industry. Chapman and Hill, London and New York.

Western Regional Climate Center. Wyoming climate summaries. Online. Available: http://www.wrcc.dri.edu/summary/climsmwy.html. July 15, 1998.

Wyoming Agricultural Statistics Service. 1998. Wyoming Agricultural Statistics 1998. Wyoming Depart-ment of Agriculture, Univ. Wyoming, College of Agriculture.