Multi-criteria, multi-objective and uncertainty analysis for agro-energy spatial modelling

The worldwide increase in the use of biomass as a Renewable Energy Source raises the issue of introducing crops dedicated to energy production into rural landscapes. The purpose of this paper is to set-up a GIS based multi-criteria approach to assess a range of possibilities for perennial energy crops conversion. The presented method was implemented at the regional level in the Yorkshire and the Humber Region in Northern UK. The first phase of the study aims to set-up a land capability model for the specific purpose of assessing the potential of different typologies of perennial energy crops, on the basis of specific pedo-climatic and topographic factors. The model output illustrates a range of potentials for energy crop conversion that can be explored in the given landscape. In the second phase a uncertainty analysis of the land capability model was performed through a simulation approach in order to interpret the influence of assumptions and uncertainty on input data and model parameters. The last phase of the study allows allocating the energy crop conversion area according to specific environmental constraints, nature protection targets, food production priorities and land capability values. The land allocation output gives a rather restrictive energy crop penetration scenario, where more than half of the conversion area is allocated to cropping systems with low land degradation potential. This scenario represents a preliminary regional analysis of the energy crop potential in terms of theoretically available conversion areas. The final results also show that the areas with highest environmental risks correspond to the areas with both the lowest suitability for energy crop cultivation and the highest model uncertainty.

► A land capability and allocation model was applied for various energy crop systems.
► The physical land parameters were evaluated under uncertainty conditions.
► The lower capability matches with the higher environmental risks and model error.
► The conversion scenario is restrictive in accordance with land conservation targets.
► Factor weights should be considered for ecological requirements of specific plants.