Navigating scientific modelling and uncertainty: Insights from hazard, risk, and impact scientists in disaster risk management (DRM)
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Date
2025-02-15
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Elsevier Ltd
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(c) 2025 The Author/s
CC BY 4.0
CC BY 4.0
Abstract
Scientific models have long been used as an important tool in assisting in decision-making in Disaster Risk Management (DRM). However, it is commonly understood that uncertainty in these models significantly influences the integration of model outputs into decision-making processes, presenting a challenge for effective uncertainty communication. This paper explores how scientists in DRM approach modelling and uncertainty.
We conducted seventeen in-depth qualitative interviews in Aotearoa, New Zealand, with scientists working on DRM. We provided an overview of the varied approaches and key factors influencing their processes for model characterisation and communicating uncertainties. We used Reflective Thematic Analysis to construct key themes, including (a) model development and characterisation, (b) accountability and opinion, (c) communication approach and challenges, and (d) collaboration for effective uncertainty communication.
We found that different DRM scientists have different disciplinary and experiential training, experience, and interaction with decision-makers. These factors greatly influence their choices regarding scientific modelling and communication of uncertainty. The lack of a generally accepted guideline for a best practice approach to uncertainty communication is a key barrier to successfully incorporating uncertainties into DRM decision-making. We suggest that a better collaboration between scientists and decision-makers throughout the lifecycle of the model development process is a way forward for effective communication of uncertainty in DRM decision-making.
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Dhungana A, Hudson Doyle E, McDonald G, Prasanna R. (2025). Navigating scientific modelling and uncertainty: Insights from hazard, risk, and impact scientists in disaster risk management (DRM). International Journal of Disaster Risk Reduction. 118.