Worldwide increasing bioenergy production is on the political agenda. It
is well known that bioenergy production comes at a cost – several trade-offs with
food production, water quality and quantity issues, biodiversity and ecosystem
services are known but a quantification of these trade-offs is missing. Hence, we
show in this study an analysis of trade-offs between bioenergy production, food
production, water quality and water quantity aspects in the Parthe catchment in
Central Germany. The analysis is based on using SWAT and a multi-objective
genetic algorithm (NSGA II). The genetic algorithm is used to find Pareto-optimal
configurations of crop rotation schemes. The Pareto-optimality describes solutions
in which an objective cannot be improved without decreasing other objectives. This
allows us to quantify the costs at which several levels of increase in bioenergy
production come and to derive recommendations for policy makers.