Agricultural residues have significant potential as a feedstock for bioenergy production, but removing these residues from the land can have negative impacts on soil health. Because of this computational tools are needed that can help guide decisions on the amount of agricultural residue that can be sustainably removed. Models and datasets that can support decisions about sustainable agricultural residue removal are available; however, no tools currently exist that are capable of simultaneously addressing all of the environmental factors that can limit the availability of residue for bioenergy production. This paper presents an integrated framework of models and data that provide a coupled a set of environmental process models and databases that can support agricultural residue removal decisions. Specifically the RUSLE2, WEPS, and Soil Conditioning Index models have been integrated together with the disparate set of databases providing the soils, climate, and management practice data required. The integrated system has been demonstrated for two example cases. In the first case the potential impact of agricultural residue removal is explored. In the second case an aggregate assessment of the agricultural residues available bioenergy production in the state of Iowa is performed.