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

IF 5.2 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software Pub Date : 2026-03-01 Epub Date: 2026-02-16 DOI:10.1016/j.envsoft.2026.106900

Julius Schlumberger , David Gold , Valeria Di Fant , Gundula Winter , Mehmet Ümit Taner , Jan Kwakkel

{"title":"A review of tools and resources to support Decision-Making Under Deep Uncertainty","authors":"Julius Schlumberger , David Gold , Valeria Di Fant , Gundula Winter , Mehmet Ümit Taner , Jan Kwakkel","doi":"10.1016/j.envsoft.2026.106900","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"198 ","pages":"Article 106900"},"PeriodicalIF":5.2000,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Modelling & Software","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1364815226000472","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/2/16 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}

引用次数: 0

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.

Abstract Image

查看原文本刊更多论文

深度不确定性下支持决策的工具和资源综述

深度不确定性下的决策（DMDU）为复杂决策提供了鲁棒性、适应性策略支持。然而，DMDU的实际应用仍然有限，部分原因是获取资源的途径分散，以及缺乏现有工具的清单。本研究介绍了一个全面的工具和资源目录。通过结构化调查和专家启发，我们确定了支持DMDU研究和实践的28种资源和16种工具，并使用已建立的DMDU分类法对它们进行分类。我们的分析揭示了对DMDU应用的理论和方法的介绍性指导的重点，对与水有关的应用有一些偏见。关于如何实现现有框架的技术性、特定于方法的资源仍然有限。我们的结果确定了支持所有核心DMDU组件的工具，尽管它们突出了持久的可伸缩性挑战。由此产生的在线目录为在实践中扩大DMDU的使用提供了基础，并打算作为一个生活的，社区驱动的平台。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Environmental Modelling & Software 工程技术-工程：环境

CiteScore

9.30

自引率

8.20%

发文量

241

审稿时长

60 days

期刊介绍： Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.