Hydrological sustainability of in-pit reclaimed oil sands landforms under climate change
Bibliographic record
Abstract
Development of robust reclamation designs would require understanding the relative effects of climate change on the water budget of reclaimed Athabasca oil sands landforms (Alberta, Canada). A surplus water budget is critical to sustain pit lakes and periodically freshen localized surface water ponds within the closure landscape. In this study, four hypothetical future climate scenarios were developed from statistically downscaled RCP2.6 and RCP8.5 climate projections and used in a hydrological model to investigate the potential effects of climate change on the water budget of an in-pit reclaimed oil sands mine landform. The four scenarios allowed the assessment of climate change effects for endpoints that bracket a range of future climate conditions on the water balance of the landform. Surface water and groundwater flow and chloride transport were simulated for the 2024–2100 period using daily climate forcing and the results were compared with equivalent responses under historical climate (1944–2020). The results suggest that the hydrological behavior under historical and RCP2.6 scenarios is similar. The climatic water deficit (potential evapotranspiration exceeding precipitation) will rise significantly under the RCP8.5 scenario. However, the modeling suggests that the water budget of the landform will not be too different from the early 21st century prolonged dry climate period. The chloride released from the landform under the different projected and historical climate scenarios also remained similar. Although evapotranspiration increases and leads to relatively drier conditions, a modest increase in precipitation helps maintain a surplus water budget in most years. The results demonstrate that incorporating future climate projections into water balance analyses is crucial to understand the potential reductions in runoff depths.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".