Year: 2025
Type: conference-paper
Abstract: Climate change poses significant risk to civil infrastructure systems, exacerbated by epistemic uncertainties (also known as deep uncertainty) arising from limited knowledge about climate change.Consistently accounting for these epistemic uncertainties in developing decision support for the planning, design, and assessment/adaptation of civil infrastructure systems presents a critical challenge for society.This study introduces a risk-informed decision support framework that incorporates a new approach to represent epistemic uncertainty in decision-making.In particular, the proposed approach assigns probabilities to relevant climate scenarios based on expert opinions (e.g., from climate scientists, engineers), reflecting the degree of belief they hold about the likelihood of different future projections.This probabilistic representation of epistemic uncertainty differs from conventional robust decision-making approaches, such as the minimax regret (MMR), which typically relies on non-probabilistic methods.A case study compares the proposed approach with MMR, showing that the proposed approach is more effective on selecting decisions that are both optimal and robust based on the associated risk, whereas MMR focuses solely on robustness while neglecting the optimality.
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4411489294