Evidence of Deep Hydraulically Active Fractures in Clay Deposits (Québec, Canada) and Numerical Simulation of Their Impacts on Groundwater Flow and Slope Stability
Bibliographic record
Abstract
Abstract This study applies cross-correlation analysis to hydraulic head data from a large network of vibrating-wire piezometers installed in sensitive glaciomarine clay deposits across the St. Lawrence and Saguenay-Lac St-Jean Lowlands in Quebec, Canada. The results reveal the presence of hydraulically active fractures near slopes, extending to depths of up to 16 meters. These findings challenge traditional models that assume clay deposits remain unfractured below a shallow weathered zone, commonly referred to as the crust. The presence of fractures facilitates rapid groundwater movement, leading to significant variations in hydraulic head that were previously believed to be attenuated at depth due to the clay’s low permeability. To assess the broader implications, we compared field data with the results of steady-state groundwater flow models that incorporate fracture scenarios. Two slope geometries with contrasting groundwater flow dynamics were analyzed, each under different fracture configurations. The hydrogeological modeling outcomes were then integrated into a slope stability model to examine how fractures influence stability. The results indicate that fractures can enhance hydraulic head by acting as preferential pathways for infiltration. However, they may also lower hydraulic head by accelerating water discharge through the slope face. Consequently, from a hydrogeological standpoint, fractures can stabilize or destabilize slopes depending on the prevailing groundwater flow system. Since this study focuses exclusively on the hydrogeological effects of fractures, future research should explore their coupled hydromechanical impacts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".