COMPARISON OF INTERANNUAL VARIABILITY MODES AND TRENDS OF SEASONAL PRECIPITATION AND STREAMFLOW IN SOUTHERN QUEBEC (CANADA)
Bibliographic record
Abstract
ABSTRACT The interactions between precipitation, streamflow and groundwater are very complex. In cold temperate regions characterized by harsh winters, winter streamflow is mainly derived from aquifers that are recharged in the spring, during snowmelt, and in the fall, when evapotranspiration is subdued. Despite this complexity, the modes and trends in the interannual variability of spring (April, May, June and July) streamflow and fall (August, September, October and November) precipitation and streamflow were compared to the modes and trends in the interannual variability of winter (December, January, February and March) streamflow in southern Quebec from 1950 to 2000. Results indicate that the variability modes are identical for all four of these hydro‐climatic variables: two modes (south‐east and east modes) on the south shore of the St. Lawrence River on either side of the 47°N and a single mode (south‐west mode) on the north shore. As for the trend, a significant increase in winter streamflow was observed on the north shore. This increase is comparable to that observed in spring streamflow, which suggests that winter streamflow on the north shore is mainly derived from groundwater recharge during the spring. Moreover, both spring and winter streamflows are positively correlated to the North Atlantic Oscillation climate index. On the south shore, south of the 47°N, a significant decrease was observed in the trend of the interannual variability of winter streamflow, this in spite of a significant increase in fall precipitation and streamflow. An increase in evaporation (decreased infiltration) due to a shift from forest cover to agricultural land cover in this region could account for this. However, fall precipitation and streamflow and winter streamflow are significantly correlated to the Atlantic Multidecadal Oscillation winter index. This correlation is negative with the first two variables but positive with the third. This study suggests that, in southern Quebec, the interannual variability of winter streamflow is mainly affected by spring recharge in non‐agricultural catchments (east and south‐west modes) and by farming in agricultural catchments (south‐east mode). Copyright © 2011 John Wiley & Sons, Ltd.
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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".