Exploring the Potential for Sustainable Future Bioenergy Production in the Arkansas-White-Red River Basin

Bioenergy production in the US has been projected to increase in the next few years and this has raised concerns over environmentally sustainable production. Specifically, there are concerns that managing lands to produce bioenergy feedstocks in the Mississippi-Atchafalaya River Basin (MARB) may have impacts over the water quality in the streams draining these lands and hamper with efforts to reduce the size of the Gulf of Mexico's "Dead Zone" (hypoxic waters). However, with appropriate choice of feedstocks and good conservation practices, bioenergy production systems can be environmentally and economically sustainable. We evaluated opportunities for producing 2nd generation cellulosic feedstocks that are economically sustainable and improve water quality in the Arkansas-White-Red (AWR) river basin, which is major part of the MARB. We generated a future bioenergy landscape by downscaling county-scale projections of bioenergy crop production produced by an economic model, POLYSYS, at a market price of $60 per dry ton and a 1% annual yield increase. Our future bioenergy landscape includes perennial grasses (switchgrass and miscanthus), short-rotated woody crops (poplar and willow) and annual crops (high yield sorghum, sorghum stubble, corn stover and wheat straw). Using the Soil and Water Assessment Tool (SWAT) we analyzed changes in water quality and quantity by simulating a baseline scenario with the current landscape (2014 land cover) and a future scenario with the bioenergy landscape. Our results over the AWR indicate decreases in median nutrient and sediment loadings from the baseline scenario. We also explored methods to evaluate if conservation practices (such as reducing fertilizer applications, incorporating filter strips, planting cover crops and moving to a no-till system) can improve water quality, while maintaining biomass yield. We created a series of SWAT simulations with varying levels of conservation practices by crop and present our methods towards identifying future scenarios that may minimize water quality and maximize biomass yields.