Abstract
With accelerating climate change, the impacts of natural hazards will compound and cascade, making them more complex to assess and manage. At the same time, tools that help decision-makers choose between different management options are limited. This study introduces a visual analytics dashboard prototype (https://www. pathways-analysis-dashboard.net/, last access: 18 October 2025) designed to support pathways analysis for multi-risk Disaster Risk Management (DRM). Developed through a systematic design approach, the dashboard employs interactive visualisations of pathways and their evaluation, including Decision Trees, Parallel Coordinates Plots, Stacked Bar Charts, Heatmaps, and Pathways Maps, to facilitate complex, multi-criteria decision-making under uncertainty. We demonstrate the utility of the dashboard through an evaluation with 54 participants at varying levels and disciplines of expertise. Depending on the expertise (non-experts, adaptation / DRM experts, pathways experts), users were able to interpret the options of the pathways, the performance of the pathways, the timing of the decisions, and perform a system analysis that accounts for interactions between the sectoral DRM pathways with precision between 71 % and 80 %. Participants particularly valued the dashboard’s interactivity, which allowed for scenario exploration, added additional information on demand, or offered additional clarifying data. Although the dashboard effectively supports the comparative analysis of pathway options, the study highlights the need for additional guidance and onboarding resources to improve accessibility and opportunities to generalise the prototype developed to be applied in different case studies. Tested as a standalone tool, the dashboard may have additional value in participatory analysis and modelling. This study underscores the value of visual analytics for the DRM and Decision Making Under Deep Uncertainty (DMDU) communities, with implications for broader applications across complex and uncertain decision-making scenarios.
| Original language | English |
|---|---|
| Pages (from-to) | 4089-4113 |
| Number of pages | 25 |
| Journal | Natural Hazards and Earth System Sciences |
| Volume | 25 |
| Issue number | 10 |
| Early online date | 22 Oct 2025 |
| DOIs | |
| Publication status | Published - 2025 |
Bibliographical note
Publisher Copyright:© Author(s) 2025.
Funding
A portion of the research discussed in this report was carried out during the Young Scientists Summer Pro-gramme (YSSP) at the International Institute for Applied Systems Analysis (IIASA) in 2023. We want to thank all 21 participants in our group discussions and semi-structured interviews, along with the 54 survey participants to test the dashboard, whose contribution was critical for meaningful research. Finally, Julius Schlumberger acknowledges the contributions of Dana Stuparu and Sarah Wright, who volunteered to discuss early versions of the visualisations and provided valuable feedback and ideas. This research has been supported by the European Union’s Horizon 2020 research and innovation programme (grant no. 101003276), the European Research Council, H2020 European Research Council (grant no. 884442), and the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (grant no. VI.Veni.222.169). This research has been supported by the European Union's Horizon 2020 research and innovation programme (grant no. 101003276), the European Research Council, H2020 European Research Council (grant no. 884442), and the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (grant no. VI.Veni.222.169).
| Funders | Funder number |
|---|---|
| European Research Council | |
| International Institute for Applied Systems Analysis | |
| Horizon 2020 Framework Programme | 101003276 |
| H2020 European Research Council | 884442 |
| Nederlandse Organisatie voor Wetenschappelijk Onderzoek | VI.Veni.222.169 |