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- Title
Regression modeling of subjective probability of river inundation with epistemic uncertainty: a short-term panel data analysis.
- Authors
Hidaka, Ken; Ikegai, Mirai; Masuda, Satoki
- Abstract
Lack of sufficient knowledge about flood risk can lead to "don't know" responses or non-response in risk perception surveys, and incorrect treatment of these responses can lead to bias in the results. In this study, we focus on the possibility that the "50%" response actually means "fifty-fifty" and thus reflects epistemic uncertainty in the subjective probability of river flooding. We conduct an analysis that introduces a concomitant-variable latent class model as a method to adjust for this epistemic uncertainty. The results of the analysis accounting for epistemic uncertainty suggest that risk communication, such as simulated evacuation experiences and flood-related information distribution, increases subjective probability. Moreover, the proportion of latent classes with epistemic uncertainty decreased with each successive wave of the survey, thereby suggesting that knowledge acquisition and learning through the demonstration experiment led to a reduction in epistemic uncertainty. The analysis using the evacuation decision-making model also suggested that the introduction of subjective probability contributed to improving the likelihood of the model. These results suggest that knowledge acquisition through risk communication and short-term panel survey can lead to correct risk perception estimations and influence evacuation decisions.
- Subjects
EPISTEMIC uncertainty; PANEL analysis; REGRESSION analysis; DATA analysis; RISK perception; KNOWLEDGE acquisition (Expert systems); EARTHQUAKE hazard analysis
- Publication
Natural Hazards, 2024, Vol 120, Issue 7, p6343
- ISSN
0921-030X
- Publication type
Article
- DOI
10.1007/s11069-024-06446-y