The influence of vegetation cover on evapotranspiration atop waste rock piles, Elk Valley, British Columbia
Bibliographic record
Abstract
Abstract Surface mining in the Elk Valley, British Columbia, involves removing vegetation, soil, and rock to access underlying metallurgical coal. Subsequent waste rock is placed into adjacent valleys, frequently burying headwater streams. Due to their coarse texture, waste rock piles increase infiltration and percolation, increasing solute transport and concentration of geochemicals in downstream surface waters. Previous research suggests that weathering solutes are transport limited, and it is hypothesized that revegetation will enhance evapotranspiration (ET) and reduce percolation through the waste rock, potentially reducing loading. This study examined the surface‐atmosphere water and energy exchanges using the eddy covariance technique for three waste rock surfaces with different levels of reclamation: (a) an ~25‐year‐old mixed coniferous forest, (b) a grass site, and (c) bare waste rock. Measurements were taken from May to October in 2013 and 2014. Soil moisture and matric suction were measured to 1‐m depth. Sap flow at the forested site was measured to partition transpiration from total ET. In all years, ET rates were greatest at the forested site, followed by the grass cover and lowest at the bare waste rock site. Growing season ET rates at the forest were 56% higher than grass in 2013 and 35% higher in 2014. At the vegetated sites, climate was the main driver of ET, with high radiation, and warm and dry conditions enhancing fluxes. Maximum ET at these sites corresponded with peak growing season, with vegetation increasing both transpiration and rainfall interception. At the bare rock site, ET was weakly related to atmospheric conditions, and ET rates briefly increased during periods following rainfall when near‐surface soil moisture was enhanced. Transpiration comprised 29% of overall ET at the forest site from late July to early October. Results suggest that vegetation establishment can be incorporated into mine reclamation plans to enhance ET rates and limit percolation, potentially reducing downstream geochemical loads.
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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".