Evaluating How Landform Design and Soil Covers Influence Groundwater Recharge in a Reclaimed Watershed
Bibliographic record
Abstract
Abstract Landscape‐scale reconstruction and prescription of soil cover systems following oil sands mining is challenging due to the quality of available reclamation materials and the subhumid climate of the Boreal Plains of Canada. In an experimental reclaimed watershed (Sandhill Fen Watershed), basin‐scale upland landforms (i.e., hummocks) were designed to provide groundwater to adjacent lowlands, necessitating adequate recharge following establishment of forest vegetation. Volumetric water contents, soil water pressure heads, and groundwater levels were monitored for four years throughout the watershed and used to calibrate and verify numerical models in HYDRUS. Using a variably saturated two‐dimensional domain, we identified a threshold‐like relationship between recharge (or upflux) and upland hummock height, where upland hummocks not tall enough to limit root water uptake from the saturated zone decreased recharge or resulted in net upflux. Recharge varied with soil cover texture (higher in coarser‐textured) and associated soil hydraulic parameters. Furthermore, scenario tests indicated the importance and relative influence that maximum rooting depths, forest floor placement thicknesses, and leaf area indices (all associated with forest development) had on recharge. Simulations utilizing a historical climate record indicated that interannual climatic variability was as influential as variation in soil cover texture in determining recharge. Reclamation practitioners should recognize that the water balances of reconstructed landscapes are largely influenced by the trade‐off between optimizing forest productivity and sourcing water to downgradient landscape positions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".