Probabilistic Multi-hazard Shaking-Tsunami Risk Assessment for the District of Tofino, British Columbia, Canada, Subjected to Megathrust Cascadia Subduction Events
Bibliographic record
Abstract
Canada has a high likelihood of facing significant earthquake threats in the future. On the Pacific coast, southwestern British Columbia is exposed to significant seismic hazards and secondary hazards (e.g., tsunamis and geohazards), originating from the Cascadia subduction zone. The Cascadia region involves the thrusting movements of the Juan de Fuca, Gorda, and Explorer Plates, which subduct underneath the North American Plate. A scenario of particular concern to residents and emergency managers is the future occurrence of a moment magnitude (M) 9.0-class megathrust earthquake in Cascadia. The scientific challenges in assessing the potential hazards and risks for residents and assets in British Columbia include the characterization of the earthquake rupture of future major Cascadia events and the modeling of their multi-hazard cascades which affect the population and built environment simultaneously. Coastal municipalities and communities in Vancouver Island face urgent needs for operational decision-support tools that provide accurate performance assessments of infrastructures under multi-hazard actions. This study presents a probabilistic earthquake-tsunami hazard model for the Cascadia subduction zone using information available in the literature regarding earthquake occurrence, earthquake rupture pattern, earthquake fault plane, and earthquake source characteristics. The earthquake occurrence and rupture models for the Cascadia subduction zone are developed by incorporating the time-dependency of earthquake occurrence, represented by a renewal process, and by adopting a stochastic source modeling approach, which allows considering heterogeneous earthquake slip distributions. Subsequently, a probabilistic earthquake-tsunami risk analysis is performed by focusing on the District of Tofino, British Columbia, which is exposed to the Cascadia subduction zone. The results produce multi-hazard curves for strong motions and tsunamis and identify critical scenarios at different return period levels that are relevant for earthquake risk management, which can be used to highlight the relative impacts of shaking and tsunami risks. The results are beneficial for creating a joint mapping of shaking and tsunami hazards and risks for coastal communities in Canada and for promoting multi-hazard risk mitigation actions against future Cascadia events.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".