Diavik Waste-Rock Project, Northwest Territories, Canada: Predicting Field-Scale Waste-Rock Drainage Quality from Humidity-Cell Experiments
Bibliographic record
Abstract
Abstract The prediction of water quality from waste-rock stockpiles is an important aspect of mine planning and closure. These predictions are complex, and a well-documented mechanistic approach can provide greater confidence in the results. In this study, humidity-cell experiments (1-kg sample) conducted at 5° and 22°C were used to estimate the effluent water quality and release rates of oxidation products from small-scale (12 t) field-based lysimeters. A comparison between estimated total mass loadings from laboratory humidity cells and total mass loadings from field lysimeters at the Diavik diamond mine, Northwest Territories, Canada, was completed for a five-year period. Measured temperature, S content, and surface area values were used as the primary scaling variables in these estimates. The release rate of SO42− from humidity cells with varying S content (ranging from 0.02–0.18 wt % total S) were normalized to the surface area of sulfide (mol m–2 sulfide S–1 sec–1) from each humidity cell. The resulting variability in SO42− release rates for waste-rock types were within one order of magnitude. The release rates of SO42− from the humidity cells were used to estimate the release rates from waste rock in the field with an average of 0.053 wt % total S. The results suggest that the measured annual total mass loading in the field was within the range predicted from the normalized annual total mass loadings using the surface area of sulfide from the humidity cells, with some discrepancies. Variation in annual loading at the field scale, presumably due to variability in precipitation and flushing, resulted in year-to-year discrepancies. Predictions of Fe and Ni release rates did not capture the field lysimeter results well, likely as a result of variations in geochemical conditions between laboratory and field-scale experiments (i.e., pH, mineral solubility) and also physical and geochemical heterogeneity that is not fully captured in the material characterization at each scale. The results indicate that, at this scale, annual total mass loadings can be estimated using small-scale humidity cells with a mechanistic approach if a thorough characterization of the waste rock is completed to better refine the release rates.
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".