Uncertainty analysis in integrated assessment: the users’ perspective. Regional Environmental Change

Research output: Contribution to journalArticle

Abstract

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. Results indicate that 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.

Details

Authors
Organisations
External organisations
  • Wageningen University
  • Open University of the Netherlands
  • University of Bonn
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Social Sciences Interdisciplinary

Keywords

  • SEAMLESS Integrated Framework, Uncertainty information needs, Integrated Assessment models, Effective uncertainty analysis, Science-policy interaction
Original languageEnglish
Pages (from-to)131-143
Number of pages12
JournalRegional Environmental Change
Volume10
Issue number2
Early online date2009 Sep 30
Publication statusPublished - 2010
Publication categoryResearch
Peer-reviewedYes