A fuzzy logic-based spatial suitability model for drought-tolerant switchgrass in the United States

Switchgrass (Panicum virgatum) has been targeted by the U.S. Department of Agriculture as an exemplary bioenergy crop, however it requires a significant amount of water and experiences reduced yields in water-stressed conditions. To avoid competition for prime agricultural areas, lands that receive adequate rainfall but are marginal due to highly variable timing of rain are potentially ideal locations to grow drought-tolerant biofuels. As scientists develop a modified variety of switchgrass that can withstand periods of drought while not substantially affecting overall yield, it is important to identify the potential geographical niche for this xerophytic crop to maximize its environmental and economic sustainability. This project uses a spatial suitability modeling approach that incorporates fuzzy logic and utilizes both physical and economic variables. We assess several fuzzy overlay techniques to identify and synthesize tradeoffs between suitability criteria. Our results highlight the Great Plains region of the United States as a suitable region, and within this area we focus on Kansas for a more detailed analysis to calculate land areas within varying dryness index thresholds. For this we develop a specialized dryness index using high resolution (spatial & temporal) weather and soil data to provide a spatially explicit measure of dry spell severity for switchgrass across a landscape. We estimate that 80% of the suitable land area in Kansas falls within a dryness index equivalent to about four 22-day long dry stretches, or one 45-day long dry stretch. By identifying the dryness threshold where land area is maximized, the results of this analysis inform the development of drought-tolerant varieties of switchgrass and identify marginal areas where efforts to plant such a species may prosper.