Improving water storage of reclamation soil covers by fractionation of coarse-textured soil
Bibliographic record
Abstract
Dobrovolskaya, Y. V., Chau, H. W. and Si, B. C. 2014. Improving water storage of reclamation soil covers by fractionation of coarse-textured soil. Can. J. Soil Sci. 94: 489–501. Mining operations cause considerable land disturbance as well as the accumulation of large amounts of waste rock. Capping waste rock with a soil cover has proven to be a reliable, long-term reclamation technique. This study examines the question of whether it is possible to attain a considerable increase in water storage capacity (WSC) by separating coarse-textured soil into particle size fractions and layering them into a soil cover. Additionally, this study investigated whether preferential flow can be mitigated by increasing the number of layers and extending the interlayer transitions in fine-over-coarse-textured soil systems. Intermittent and constant infiltration experiments were conducted on homogeneous covers composed of natural sand, two-layered covers with abrupt and gradual interlayer transitions as well as on a four-layered cover under initially air-dry and field capacity (FC) conditions. Water storage capacities were determined from a sampling of soil covers’ water content at FC. Infiltration experiments showed that all tested covers under all initial and boundary conditions had limited susceptibility to preferential flow. Increasing the number of layers and extending the interlayer transitions had a stabilizing effect on the wetting front. Water storage capacities and residence time increased with the increased number of layers. Overall, it has been shown that it is possible to improve the WSC of coarse-textured soil by fractionation and layering of it into a relatively fine-over-coarse soil system.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".