A review of tools and resources to support Decision-Making Under Deep Uncertainty

  • Julius Schlumberger
  • , David Gold*
  • , Valeria Di Fant
  • , Gundula Winter
  • , Mehmet Ümit Taner
  • , Jan Kwakkel
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Decision-making under Deep Uncertainty (DMDU) offers approaches to support robust, adaptive strategies for complex decision-making. However, practical uptake of DMDU remains limited, partly due to fragmented access to resources and a lack of an inventory of available tools. This study introduces a comprehensive catalogue of tools and resources. Through a structured survey and expert elicitation, we identify 28 resources and 16 tools that support DMDU research and practice and classify them using an established DMDU taxonomy. Our analysis reveals a focus on introductory guidance regarding theory and methods of DMDU application, with some bias toward water-related applications. Technical, method-specific resources on how to implement existing frameworks remain limited. Our results identify tools supporting all core DMDU components, though they highlight persistent scalability challenges. The resulting online catalogue provides a foundation for expanding the use of DMDU in practice and is intended as a living, community-driven platform.

Original languageEnglish
Article number106900
JournalEnvironmental Modelling and Software
Volume198
DOIs
Publication statusPublished - Mar 2026

Bibliographical note

Publisher Copyright:
© 2026 The Authors

Keywords

  • Decision-support
  • Deep uncertainty
  • Exploratory modeling
  • Resources
  • Tools

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