Estimation of historical earthquake-induced liquefaction in Fraser River delta using NBCC 2020 GMPEs in deterministic and probabilistic frameworks
Bibliographic record
Abstract
Paleo-liquefaction features of sand dykes and sand blows were identified in the 1990s at multiple host sediments in the Fraser River delta in southern British Columbia all younger than 3500 BP. These paleo-liquefaction sites could be linked to Cascadia subduction earthquakes. Empirical magnitude-bound relationships are often used to estimate paleo-earthquake magnitudes. To determine the lower bound magnitude of Cascadia interface earthquakes that could have generated the paleo-liquefaction features, we use ground motion prediction equations for interface earthquakes from the sixth Canadian seismic hazard model of the 2020 National Building Code of Canada. We estimate the minimum M and its peak ground acceleration (amax) of an interface earthquake required to initiate paleo-liquefaction in the study region. Starting with three full-rupture deterministic scenarios of varying source-to-site distance, we determine the minimum M required from Cascadia subduction zone interface mega-thrust earthquakes to induce liquefaction in the Fraser River delta spans 8.0–8.9 with a corresponding amax range of 0.09–0.13g. We also perform a back-calculation paleo-liquefaction analysis in a probabilistic framework to incorporate aleatory uncertainties (cone penetration resistance, groundwater table, and amax) and epistemic uncertainties (liquefaction simplified model) via the Monte Carlo simulation. The developed probabilistic methodology is also applicable to a forward liquefaction assessment and other liquefaction sites globally. The median M from this probabilistic paleo-liquefaction for the four investigated sites lies between 8.8 and 9.0. Our probabilistic results also reveal that Cascadia interface earthquakes with M > 8.9 lead to a 31%–57% probability of liquefaction triggering in the Fraser River delta. In addition, we developed deterministic and probabilistic magnitude-bound curves specific to Cascadia interface earthquakes and representative site class E conditions. These curves provide more accurate magnitude estimations for predicting seismic-induced liquefaction from Cascadia interface earthquakes for sites in the Pacific Northwest than empirical bound curves.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".