Hydro-climatological Trend Analysis and Influences on the Discharge in the Elk River Watershed, Southeast British Columbia
Bibliographic record
Abstract
Hydro-climatological modelling in mountainous environments is difficult due to topographic and climatic variability. Therefore, observed data (1970-2009) were used to assess trends in the Elk River watershed, a region experiencing growth of its open-pit coal mining industry. The Mann-Kendall trend test identified a decrease in snow throughout the watershed, small increase in rain, and overall decrease in northern precipitation. Moreover, mid-basin increase in temperature was detected. An increase in the Fording River winter discharge, counteracted the summer decrease in total watershed discharge from 1970-1989. Linear modelling identified baseflow, precipitation, and atmospheric teleconnection patterns as strong discharge drivers; whereas, the double mass curve identified a precipitation and discharge relationship change starting after 2007. Unfortunately, efforts to incorporate the Soil Water Assessment Tool proved unsuccessful for this watershed. Overall, these hydro-climatological trends were not as synchronized as expected likely due to other variables, such as watershed buffering capabilities and/or land-cover change.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".