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Integrated assessment modelling advances in Netherlands
Integrated Assessment Modelling
Researchers at the renowned Wageningen University have published new data on environment and change that looks at the role of end users in the development of uncertainty analysis in integrated assessment modelling, using the SEAMLESS Integrated Framework as a case study.
According to the researchers:
Integrated Assessment (IA) models aim at providing information and decision-support to complex problems. This paper argues that uncertainty analysis in IA models should be user-driven in order to strengthen science-policy interaction.
We suggest an approach to uncertainty analysis that starts with investigating model users' demands for uncertainty information. These demands are called ''uncertainty information needs''. Identifying model users' uncertainty information needs allows focusing the analysis on those uncertainties which users consider relevant and meaningful.
As an illustrative example, we discuss the case of examining users' uncertainty information needs in the SEAMLESS Integrated Framework (SEAMLESS-IF), an IA model chain for assessing and comparing alternative agricultural and environmental policy options. The most important user group of SEAMLESS-IF are policy experts at the European and national level.
Uncertainty information needs of this user group were examined in an interactive process during the development of SEAMLESS-IF and by using a questionnaire. Users' information requirements differed from the uncertainty categories considered most relevant by model developers. In particular, policy experts called for addressing a broader set of uncertainty sources (e.g. model structure and technical model setup).
The findings highlight that investigating users' uncertainty information needs is an essential step towards creating confidence in an IA model and its outcomes. This alone, however, may not be sufficient for effectively implementing a user-oriented uncertainty analysis in such models.
As the case study illustrates, it requires to include uncertainty analysis into user participation from the outset of the IA modelling process.
The SEAMLESS project examined developed science and a computerised framework for integrated assessment of agricultural systems and the environment. The integrated project was funded by the EU Framework Programme 6 (Global Change and Ecosystems) and ran from 2005 till March 2009. SEAMLESS involved 29 research institutions from thirteen European countries, Mali and the USA. It sought to facilitate translation of policy questions into alternative scenarios that can be assessed through a set of indicators that capture the key economic, environmental, social and institutional issues of the questions at stake.
Lead author Silke Gabbert and colleagues published their study in the journal Regional Environmental Change.
Citation
Silke Gabbert, Martin van Ittersum, Carolien Kroeze, Serge Stalpers, Frank Ewert and Johanna Alkan Olsson. 2010. "Uncertainty analysis in integrated assessment: the users' perspective". Regional Environmental Change 10(2):131-143.
