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Young, J.A., B.M. Christensen, M.S. Schaad, M.E. Herdendorf, G.F. Vance, and L.C. Munn. 1999. A geographic information system to identify areas for alternative crops in northwestern Wyoming. p. 176–180. In: J. Janick (ed.), Perspectives on new crops and new uses. ASHS Press, Alexandria, VA.

A Geographic Information System to Identify Areas for Alternative Crops in Northwestern Wyoming

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

    1. Site Description
    2. Soils Description
    3. Weather Records
    4. Crop Growth Parameters
    5. Model Formation

Agriculture is the third largest industry in Wyoming after mining and tourism (R. Micheli, Wyoming Department 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 of crops produced in Wyoming (Wyoming Agricultural Statistics Service 1998). The Bighorn Basin was developed for agricultural use when irrigation was introduced into the area in 1905 with the completion of the Buffalo Bill Dam. Major crops currently grown in the Bighorn Basin include: spring wheat, barley, oats, dry beans, sugar beets, alfalfa hay, and corn.

One alternative for increasing profit margins of the Wyoming agricultural industry is through the introduction of new crops. Wallis et al. (1989) defines new or alternative crops as either crops new to a particular county, region or state, or as a crop that has been, or is being developed, from a plant that has never been cultivated for commercial production. Alternative crops such as cabbage, mint, pumpkins, squash, and grass seed have been cultivated in the Bighorn Basin, but are most often marketed for local consumption rather than being 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 cultivation, however, has resulted in reduced production and increased use of pesticides, tillage, and other management 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 used to help control pests, including the sugar beet nematode (Gardner, 1994). Introduction of alternative crops to the 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 to efficiently capture, store, update, manipulate, analyze, and display all forms of geographically referenced information" (ESRI 1995). A GIS stores spatial data as data layers. These layers are defined as a set of features, each having both location and attributes. The advantage of GIS is attributed to its ability to spatially analyze multiple data layers. This powerful tool allows decision-makers to simulate effects of management and policy alternatives within a geographic area prior to implementation (Congalton and Green 1992).


The 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 opportunities for agriculturalists to increase income possibilities and to break herbicide and pest cycles. This study used a GIS to investigate the potential for cultivating new crops in the Bighorn Basin. Environmental traits of the 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 Bighorn Basin. The objectives of this study were to: (1) develop a spatially-correlated database that includes environmental 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 environmental data to display and describe areas of potential alternative crop production.


Figure 1
Fig. 1. Study area location.

Site Description

The 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 1525 m; 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 topographic quadrangle maps and the Wyoming State Land Cover Classification were overlayed onto the Park, Big Horn and Washakie counties. These coverages were clipped to the study area. Due to irrigation constraints, topographic maps having a majority of slopes greater than 5% were eliminated. This resulted in the removal of only a portion of the topographic maps for the three counties. From these topographic maps, the quadrangles with greater than 25% agricultural land were selected. A buffer of one quadrangle was placed around the entire study area to include smaller areas of agricultural land. This analysis resulted in the inclusion of 81 quadrangles in our study area. Upon ground-truthing in May 1998, 22 of the quadrangles were excluded from the study area because they lacked either agricultural production potential due to topography or had insufficient irrigation capabilities.

Soils Description

Published 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 information, a GIS simulation model was created to predict soil occurrence in the Bighorn Basin (Fig. 2). Bedrock and surficial geology covering the state of Wyoming was obtained from the Spatial Data and Visualization Center at the University of Wyoming (1998). These coverages were clipped to the study area. Soils series in the Washakie County comprehensive soil survey were examined to determine bedrock and surficial geology combinations upon which they occurred (Iiams 1983). These combinations, and combinations predicted from other unpublished work in the region, were used to predict soils for the entire study area. The model was applied utilizing decision rules in Arc Macro Language (Munn and Arneson 1998). The predicted soils map was field checked and updated accordingly.

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

Weather Records

Eighteen weather stations exist both in and around the study area (Fig. 3). These stations have collected weather data for 30 years or longer (Western Regional Climate Center, 1998). The weather station attribute data were used to create continuous weather patterns for the basin; contour lines were extrapolated from the point data utilizing geostatistics. Environmental layers developed from the weather station data include frost-free days (80% probability), growing degree-days (base 5°C), annual precipitation, and August mean temperature. Geostatistics has proven to be advantageous when compared to other methods of extrapolation (Kravchenko et al. 1996). Semi-variograms of each environmental attribute were plotted and cross-validation and kriging techniques were applied. Kriging resulted in a grid of each attribute with values placed at the nodes or intersections of the grid. This information was imported into ARC/INFO and used to create continuous grid coverages of the four environmental layers shown in Fig. 3.

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

Crop Growth Parameters

The 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 Montana State University, University of Nebraska–Lincoln, and Colorado State University. These parameters were compiled into one database for analysis. Table 1 illustrates crop growth parameters that were analyzed in the GIS database for buckwheat and canola potential production areas.

Table 1. Crop growth parameters for buckwheat and canola.


(Fagopyrum esculentum)
Warm season broadleaf

(Brassica campestris)
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, prefers medium textured soils

Non-crusting clay loam soils, medium texture


Sensitive to drought stress

Dryland >30.5 cm annually

Frost-free season

Matures in 75–90 days, easily killed by frost

> 90 days

Minimum temp.



Maximum temp.


< 11 days >32°C in July

Growing degree-days

1200 days (base 5°C)

860–920 (base 5°C)

Model Formation

Environmental data were compiled into a GIS and analysis using map algebra was performed. The parameters queried included length of frost-free season, growing degree-days, annual precipitation, and average August temperature. Areas with selected crop growth parameter combinations were displayed. A separate map representing two alternative crops was created showing potential areas for its production. Each map utilized the specific requirements of the individual crop.


Soils 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 one soil mapping unit required change. The creation of the soils data allows for the use of textural classes, pH, and water-holding capacities in our alternative crop analysis. A large proportion of the study area consists of 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 to the topography of the surrounding study area, i.e., with an increase in elevation there is a decrease in frost-free period, a decrease in growing degree-days, an increase in precipitation, and a decrease in temperature. These maps display frost-free period (80% probability), growing degree-days (base 5°C), annual precipitation, and August mean temperature.

Preliminary findings utilizing frost-free period and growing degree-days indicate that canola and buckwheat can be grown in virtually all of the study area under irrigated conditions (Fig. 4). Canola production requires 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-free period and growing degree-days were used in addition to greater than 30.5 cm annual precipitation. There is less than 5% dryland agriculture production currently in the study area.

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


The 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 created through 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 of locating 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. While many of the crops being investigated can be grown in the Bighorn Basin, the commercial yield of these crops is uncertain. A crop yield model should be employed to predict if alternative crop production could compete in the marketplace. An economic analysis of the feasibility of the growth of these new crops is also an area that requires further analysis.


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