Numerical modeling of a potential landslide-generated tsunami in the southern Strait of Georgia
Bibliographic record
Abstract
Abstract We report results of numerical simulations of a potential subaerial landslide on the coast of Orcas Island and the resultant tsunami waves in the southern Strait of Georgia near the US/Canada border. A likely trigger is strong ground shaking during large earthquakes on the nearby Holocene active Skipjack Island fault zone. For a worst-case scenario, we assume a 0.17 $${\textrm{km}}^3$$ km 3 rigid subaerial failure on the steep northeast coast of the island, spanning the $$\sim$$ ∼ 5 km between previous landslide deposits on the adjacent seafloor. The landslide motion and resulting tsunami generation are modeled using the three-dimensional (3D) non-hydrostatics physics-based NHWAVE model. The simulated failure moves downslope with a peak velocity of 13.64ṁ/s and travels 732 m before coming to rest after 85 s in 75-m water depth. Tsunami propagation is then continued using the 2D fully nonlinear and dispersive Boussinesq wave model FUNWAVE-TVD in a succession of layered and nested grids. The modeling reveals susceptible locations, particularly as waves will arrive with little or no warning. In the near-source region, modeled waves have peak amplitudes of 15–20 m, current speeds of up to 10 m/s, and runup of up to 30 m. Smaller, but significant, wave amplitudes and runup occur throughout the region surrounding Orcas Island. In the tsunami propagation direction, runup reaches 7.5 m at Neptune Beach near Lummi Bay. Both initial and reflected waves cause significant runup (> 1.5 m) along much of the shoreline between Point Roberts and Lummi Bay.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".