Mitigating earthquake disasters invlolves several key components and stages, from identifying and assessing risk to reducing their impact. These components include: a) Analysis of hazards: examining the physical characteristics of ground shaking and its cascading effects on the natural/built environment. b) Vulnerability and exposure assessment: evaluating how structures and people are susceptible to hazards. c) Risk management: preparedness, rescue, relief, recovery, capacity building and overall resilience.
Given the complexity of earthquake disaster mitigation, a variety of seismic hazard and risk models can be adopted, at different spatial and temporal scales. These models incorporate diverse observations and require multi-disciplinary input. Testing and validating these methodologies, for all risk components, is essential for effective disaster mitigation.
We invite contributions on various aspects of seismic risk research and assessment, including both methodological and practical approaches. Topics include:
• Developing physical/statistical models, including those using artificial antelligence to assess earthquake risk factors such as hazard, exposure, and vulnerability. This also involves exploring innovative data collection and processing techniques, such as statistical machine learning;
• Estimating earthquake hazard and risk across different temporal and spatial scales and assessing the accuracy of these models against available observations;
• Conducting time-dependent seismic hazard and risk assessments that account for the impact of aftershocks and providing post-event information such as early warnings and alerts for effective emergency management;
• Analyzing earthquake-induced cascading effects such as landslides and tsunamis, and conducting multi-risk assessments that combine earthquakes with other hazards like flooding.
This interdisciplinary session aims to facilitate knowledge exchange and share best practices gained through various approaches. It will also highlight current deficiencies and suggest future research directions.