Remote Predictive Mapping 5. Using a Lidar Derived DEM to Test the Influence of Variable Overburden Thickness and Bedrock on Drainage and Basin Morphology
Bibliographic record
Abstract
A 4–m lidar digital elevation model (DEM) provides sufficient resolution to examine the impact of variable till cover on the incision history of multiple small (5 km2) catchments in eastern Canada. The study site was selected because it has homogeneous bedrock geology that dips parallel to the land surface, is tectonically stable, has undergone common base level changes, and has a common ice history, with variable overburden thickness, from thin cover in the west to thick cover in the east. Basin morphometrics were compared for similar-size basins that have variable till cover thicknesses. Basins with thicker till cover are wider and show differences in hypsometries compared to those where till cover is thin. Two basins representing end members of till thickness were measured for stream discharge and water chemistry. Thick till (> 1 m) on the eastern half of North Mountain retards infiltration sufficiently to promote overland flow and accelerate incision relative to areas with thinner till. Till thickness and continuity therefore are expected to impede the achievement of steadiness and may also delay stream power law relationships in larger catchments until till cover has been effectively eroded.SOMMAIREUn modèle altimétrique numérique (MAN) par lidar 4 m offre une résolution suffisante pour étudier l'impact des divers dépôts de till sur l'histoire de l'érosion linéaire de multiples petits (5 km2) bassins versants dans l'Est du Canada. Le site d'étude a été choisi parce que sa géologie est homogène et que son pendage est parallèle à la surface du sol, qu’il est tectoniquement stable, qu’il a subi des changements similaires du niveau de base d’érosion, de même qu’ une histoire glaciaire similaire, avec une épaisseur de mort-terrain variable, d’une couverture mince à l'ouest jusqu'à une couverture épaisse à l'est. La morphométrie du bassin a été comparée à celle de bassins de taille semblable aux épaisseurs de till variables. Les bassins aux couvertures de till plus épaisses sont plus larges et montrent des différences hypsométriques comparé à ceux aux couvertures minces. Deux bassins représentant les termes extrêmes de l'épaisseur du till ont été mesurées quant au débit du courant et à la chimie de l'eau. Les till épais (>1 m) sur la moitié est du mont Nord retardent l'infiltration, ce qui favorise l'écoulement en surface et accélèrent l’érosion linéaire par rapport aux zones couvertes de couches de till plus minces. On s’attend donc à ce que l'épaisseur de la couche de till et sa continuité agissent comme une entrave à la stabilité et puissent aussi retarder les effets de la loi de puissance de l’écoulement dans les grands bassins récepteurs jusqu'à ce que la couverture de till a été effectivement érodée.
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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".