Models Help Assess Biofuels' Sustainability

ARS scientists are collaborating with the U.S. Department of Agriculture's Economic Research Service (ERS), the U.S. Environmental Protection Agency, the Department of Energy, and USDA's Natural Resources Conservation Service to assess the economic impact of feedstock production. At locations around the United States, ARS scientists are evaluating how individual and combined management decisions influence different farming systems.

In one collaborative study, ARS scientists in Oregon and Texas are pairing two biophysical models to evaluate the environmental impact of land-management practices on large, complex watersheds over long periods of time. The assessment will also take into account the effects of varying soils, land use and management conditions.

The first model, called CQESTR, simulates changes in soil organic carbon based on factors such as climate, tillage management, crop rotation and crop residue removal. By incorporating the model into the Soil and Water Assessment Tool (SWAT), ARS soil scientist Hero T. Gollany, at the Columbia Plateau Conservation Research Center in Pendleton, Ore., and ARS agricultural engineer Jeffrey G. Arnold, at the Grassland Soil and Water Research Laboratory in Temple, Texas, can predict how land management practices will influence soil organic carbon, soil organic matter, water, sediment and agricultural chemical accumulation.

Another ARS model, called PGA-BIOECON, calculates the trade-offs among three important objectives: profitability, water quality and production efficiency. ARS hydrologist Gerald Whittaker, at the agency's Forage, Seed and Cereal Research Unit in Corvallis, Ore., helped develop the model. Because the model can work on many scales and on multiple objectives, its results provide information to a diverse pool of users, encompassing individual farmers and national policymakers.

Whittaker's model projects information on a variety of complex factors, providing data that could allow stakeholders to select the best management decisions to achieve their objectives.