Keywords

ecosystem services, trade-off, optimization, bioenergy, agriculture, water quality

Start Date

1-7-2012 12:00 AM

Description

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.

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Jul 1st, 12:00 AM

Quantifying Trade-offs between Bioenergy Production, Food Production, Water Quality and Water Quantity Aspects in a German Case Study

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.