Some aspects of the hydroclimatology of the Quesnel River Basin, British Columbia, Canada
Bibliographic record
Abstract
Abstract In conjunction with available climate data, surface runoff is investigated at 12 gauges in the Quesnel watershed of British Columbia to develop its long‐term (1926–2004) hydroclimatology. At Quesnel itself, annual mean values of air temperature, precipitation and runoff are 4·6 °C, 517 and 648 mm, respectively. Climate data reveal increases in precipitation, no significant trend in mean annual air temperature, but an increasing trend in mean minimum temperatures that is greatest in winter. There is some evidence of decreases in winter snow depth. On the water year scale (October–September), a strong positive correlation is found between discharge and precipitation (r = 0·70, p < 0·01) and a weak negative correlation is found between precipitation and temperature (r = − 0·36, p < 0·01). Long‐term trends using the Mann‐Kendall test indicate increasing annual discharge amounts that vary from 8 to 14% (12% for the Quesnel River, p = 0·03), and also a tendency toward an earlier spring freshet. River runoff increases at a rate of 1·26 mm yr−1 m−1 of elevation from west to east along the strong elevation gradient in the basin. Discharge, temperature and precipitation are correlated with the large‐scale climate indices of the Pacific Decadal Oscillation (PDO) and El‐Niño Southern Oscillation (ENSO). Copyright © 2009 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 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) | 0.004 | 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".