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February 16, 2026Environmental Modelling & Software2 citationsOpen Access

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

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JSJulius SchlumbergerDGDavid GoldVFValeria Di Fant

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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 towards 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. • Introduce a first catalogue of DMDU tools and resources compiled via a community-wide survey. • 28 resources and 16 tools classified using an established DMDU taxonomy. • Introductory guidance dominates; method-specific resources are limited. • Three tools support all DMDU analysis components but face scalability issues. • Online catalogue offers a living platform for practitioners and researchers.

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Cite This Study

Schlumberger et al. (2026) studied this question.

synapsesocial.com/papers/6a1562d75347fbb1739fb272https://doi.org/10.1016/j.envsoft.2026.106900
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