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Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.

NH9.16

Uncertainty Quantification in Natural Hazard and Risk Assessments: Best practices and lessons learned across different hazards (co-organized)
Convener: Paolo Frattini  | Co-Conveners: Ivica Vilibić , Yoshiyuki Kaneda , Daniela Molinari , Sergiy Vorogushyn 

Proper uncertainty quantification, this session's topic, remains a major challenge, and is inherent to many aspects of natural hazard and risk assessments across a broad range of specific or combined natural phenomena (earthquake, fluvial or coastal flood, landslides, volcano, wildfires, drought) especially in climate change conditions. Many methodological developments for uncertainty quantification have been proposed in response to the promise of improving decision making regarding risk management, facilitating risk communication and informing strategies to successfully mitigate our society's vulnerability to natural disasters. These have led to the integration of ideas from multiple communities, including mathematics, statistics, geology, geophysics, geography, climatology, hydrology, economics, education and psychology. This session invites contributions that share experiences and discuss the applicability and the successes (or failures) of uncertainty quantification methods and methodology applied to hazard and risk analysis of real cases.

Topics of interest include (but are not limited to):
(i) Novel methods for effective characterization of sensitivity and uncertainty;
(ii) Uncertainty analysis along the whole hazard-vulnerability-risk chain;
(iii) Epistemic uncertainties (e.g., model and data limitations);
(iv) Prediction validation and reduction in predictive uncertainty;
(v) Elicitation and Integration of expert judgements;
(vi) Decision-making under deep uncertainty;
(vii) visualisation and communication of uncertainty to different stakeholders.
(viii) uncertainty related to Climate Change and non-stationary conditions