Characterizing the impacts of seismic lines on the water budget of a Boreal Watershed in Alberta (Western Canada)
Bibliographic record
Abstract
A 706 km 2 watershed located in a heavily industrialized region near Fox Creek, Alberta, Canada. Petroleum exploration has increasingly disturbed boreal ecosystems in North America. Seismic lines are one of the major footprints of the petroleum industry: they form cleared linear corridors in forests and their regeneration is generally poor. For this study, field measurements of soil, vegetation, water and snow were conducted on 5 paired (seismic line and adjacent undisturbed area) sites located in lowland and upland ecosites, and a 1-D physically based hydrologic model, the Simultaneous Heat and Water Model (SHAW), was used to investigate the impacts of seismic lines on the water budget over a year. Field measurements indicate that parameters, including soil water content and temperature, vary according to a complex combination of factors and are highly site-specific between seismic lines and undisturbed areas. Hydrological modeling of the two ecosites (lowland and upland) showed up to a 33 % reduction in evapotranspiration and a decrease in percolation (leading to none) below the root zone on seismic lines. Considering that there are 2300 km of seismic lines in the study area and that 36 % of the forest has been cleared for industrial activities, these results suggest that the water budget is impacted by anthropogenic lineaments. Climate change will likely intensify these impacts. • Field measurements of soil, vegetation, water and snow were done on 5 paired sites. • Soil moisture and temperature conditions were highly site specific. • Hydrologic modeling showed lower ET and percolation on seismic lines. • Anthropogenic lineaments in the boreal forest impact the water budget.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".