Assessing spatial uncertainties of land allocation using a scenario approach and sensitivity analysis: A study for land use in Europe

Land change model outcomes are vulnerable to multiple types of uncertainty, including uncertainty in input data, structural uncertainties in the model and uncertainties in model parameters. In coupled model systems the uncertainties propagate between the models. This paper assesses uncertainty of changes in future spatial allocation of agricultural land in Europe as they arise from a general equilibrium model coupled to a spatial land use allocation model. Two contrasting scenarios are used to capture some of the uncertainty in the development of typical combinations of economic, demographic and policy variables. The scenario storylines include different measurable assumptions concerning scenario specific drivers (variables) and parameters. Many of these assumptions are estimations and thus include a certain level of uncertainty regarding their true values. This leads to uncertainty within the scenario outcomes. In this study we have explored how uncertainty in national-level assumptions within the contrasting scenario assumptions translates into uncertainty in the location of changes in agricultural land use in Europe. The results indicate that uncertainty in coarse-scale assumptions does not translate into a homogeneous spread of the uncertainty within Europe. Some regions are more certain than others in facing specific land change trajectories irrespective of the uncertainty in the macro-level assumptions. The spatial spread of certain and more uncertain locations of land change is dependent on location conditions as well as on the overall scenario conditions. Translating macro-level uncertainties to uncertainties in spatial patterns of land change makes it possible to better understand and visualize the land change consequences of uncertainties in model input variables.

► A global scale general equilibrium model was coupled to a spatial land allocation model to simulate changes in land use.
► Uncertainty in growth rates of GDP and population was translated into uncertainties of the location of land use change.
► Uncertainties have strong, scenario dependent, spatial variation