Controls on Tributary–Junction Fan Distribution Along the Chaudière River, Québec, Canada
Bibliographic record
Abstract
This study investigates the morphometric and anthropogenic controls governing the occurrence and spatial distribution of tributary–junction fans (TJFs) along the Chaudière River, Québec, Canada. Using GIS-based morphometric analysis, field validation, and multivariate statistics (PCA, CART, LDA), 142 tributary watersheds were analyzed, of which 41 display fan-shaped depositional features. Basin relief, drainage density, contributing area, and slope–area coupling emerge as the dominant predictors of TJF development, delineating an intermediate energy domain where sediment supply and transport capacity become balanced enough to allow partial geomorphic coupling at confluence nodes. CART analysis identified approximate slope and area thresholds (slope < 9°, area > 20 km2; 66% accuracy), while LDA achieved 76%, indicating that morphometry provides useful but incomplete predictive power. These moderate performances reflect the additional influence of event-scale hydrological forcing and unquantified Quaternary substrate heterogeneity typical of postglacial terrain. Beyond morphometry, anthropogenic disturbance exerts a secondary but context-dependent influence, with moderately disturbed watersheds (10–50% altered) showing higher frequencies of fans than both highly engineered (>50%) and minimally disturbed (<10%). This pattern suggests that land-use modification can locally reinforce or offset morphometric predisposition by altering sediment-routing pathways. Overall, TJFs function as localized sediment-storage buffers that may be periodically reactivated during high-magnitude floods. The combined effects of basin geometry, land-use pressures, and hydroclimatic variability explain their spatial distribution. The study provides an indicative, process-informed framework for evaluating sediment connectivity and depositional thresholds in cold-region fluvial systems, with implications for geomorphic interpretation and hazard management.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".