Numerical simulation of the landslide‐generated tsunami in Kitimat Arm, British Columbia, Canada, 27 April 1975
Bibliographic record
Abstract
It remains challenging to predict and estimate potential damage from tsunamis using computer models. One of the approaches to validate models is to compare their results with site observations. We carried out numerical modeling for both the underwater landslide and the associated tsunami that occurred near Kitimat, British Columbia, Canada on 27 April 1975. A few observations of high water marks along the coastline indicated 8.2 m tsunami waves. Previous survey results of the seafloor showed that a landslide traveled about 5 km down the axis of the fjord from its source areas on the sidewall of the fjord, near the head of the inlet, and on the lower Kitimat River delta. We modeled the subaqueous slope failure as a Bingham visco‐plastic fluid (debris flow) based on previous geotechnical investigations at the site, and numerically solved the landslide‐generated tsunami wave and debris flow equations using a finite‐volume Godunov‐type scheme. This method resolves abrupt wave and landslide front interactions and remains oscillation‐free. The computed motion of the debris flow is generally consistent with observations; simulations indicate that the failure propagated approximately 4.5 km down the fjord axis from its inception point. We have found that computed amplitudes for the tsunami wave crest at the coast of Kitimat Arm were between 6 and 11 m; these values are somewhat higher than previous simplistic solitary wave theory estimates of 6.3 m and observations of 8.2 m.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".