The Use of "Enhanced" Moisture Store-And-Release Cover Systems over Reactive Mine Waste in Cold and Warm Semi-Arid Climates
Bibliographic record
Abstract
Moisture store-and-release cover systems utilize the high evaporative demand in semi-arid and arid climates to reduce the infiltration of meteoric waters to underlying reactive mine waste. This paper describes the benefits of adding a thin, reduced hydraulic conductivity layer below the overlying non-compacted layer to "delay" the downward percolation of infiltrating moisture and enhance the overall performance of the cover system. The additional cover layer is not required to be a high quality "barrier" layer and therefore does not necessarily require a clay-rich material. For example, a compacted waste rock layer as a result of haul truck traffic on top of a dump lift could serve as the low hydraulic conductivity layer. A one-dimensional numerical modeling program was used to compare the performance of a conventional moisture store-and-release cover system and an "enhanced" moisture store-and-release cover system. The modeling program was based on actual climate conditions and measured soil properties from a cold semi-arid site in northern Canada and a warm semi-arid site in Australia. Two cover system alternatives examined at each site found a decrease in the average annual net percolation for the enhanced store-and-release cover system of approximately 4%-7% of annual precipitation compared to the conventional store-and-release cover system. Analysis of the simulations showed net percolation occurred during the spring after snow melt and following the autumn rainfall events at the northern Canadian site and after intense rainfall events during the rainy season at the Australian site. The thin, reduced hydraulic conductivity layer improved the performance of the store-and-release cover system by holding water within the cover system for an increased period of time, allowing increased actual evapotranspiration in the subsequent dry periods.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".