IMPROVING ALFALFA AND OTHER FORAGE CROPS FOR BIOENERGY, LIVESTOCK PRODUCTION, AND ENVIRONMENTAL PROTECTION
Location: Plant Science Research
Title: Spatial ramifications of crop selection: water quality and biomass energy
Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: March 23, 2010
Publication Date: February 16, 2011
Citation: Russelle, M.P., Kelley, D.W., Birr, A.S., Tiffany, D.G. 2011. Spatial ramifications of crop selection: water quality and biomass energy. In: Clay, D.E., Shanahan, J.F., editors. GIS Applications in Agriculture. Volume 2. Nutrient Management for Energy Efficiency. Boca Raton, FL: CRC Press. p. 395-424.
Interpretive Summary: In agriculture, as in other human endeavors, problems often arise by unintentional mismanagement of resources. For example, adding the amount of fertilizer that is acceptable in most situations could result in ground water contamination in other situations. Making good decisions about which crop to grow and how to manage it requires knowledge of the soils – how they affect crop growth, water storage, and water movement. We used soils information, computer models of crop growth, and a Geographic Information System (GIS) to produce maps for two kinds of problems. The first was a case of increasing nitrate concentrations in the ground water used for public drinking water in a rural area. We developed maps that showed which fields were the most likely sources of the nitrate. With this information, the water supplier could focus on improving crop management on those fields, rather than less important fields. In the second situation, a town is planning to build a plant biomass processing facility to make ethanol or other transportation fuels. We analyzed the likely crop yields and energy production of corn, soybean, and alfalfa for all fields within 25 miles of the town. We found that alfalfa would produce much higher yields of both biomass and energy than soybean, especially on certain soils, and alfalfa would improve the efficiency of corn production. Because it is easier to interpret for most nonscientists, data presented in the form of maps can be more helpful than in other forms.
The use of GIS in concert with simple or complex simulation modeling provides an unparalleled way to generate new data and to help a variety of audiences understand spatial patterns of data. From improved understanding, policy incentives can be crafted to reduce adverse environmental impacts of agricultural production at lower costs than would be necessary otherwise. In this chapter, two case studies demonstrate how GIS and modeling can be used to understand how crop selection and soils interact to effect environmental outcomes across an agricultural landscape. We addressed the needs of two distinctly different audiences: 1) a public drinking water supplier faced with increasing nitrate in a ground water source; and 2) a variety of stakeholders involved with planning a new biomass conversion facility to produce renewable fuels from grain or cellulosic feedstock. In both cases, the GIS output documents the benefits of the perennial legume alfalfa (Medicago sativa L.) in particular landscape areas and provides a mechanism to compare alfalfa with corn (Zea mays L.) and soybean [Glycine max (L.) Merr.].