Recent trends and variability in river discharge across northern Canada
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. This study presents an analysis of the observed inter-annual variability and inter-decadal trends in river discharge across northern Canada for 1964–2013. The 42 rivers chosen for this study span a combined gauged area of 5.26 × 106 km2 and are selected based on data availability and quality, gauged area and record length. Inter-annual variability in river discharge is greatest for the eastern Arctic Ocean (coefficient of variation, CV = 16 %) due to the Caniapiscau River diversion into the La Grande Rivière system for enhanced hydropower production. Variability is lowest for the study area as a whole (CV = 7 %). Based on the Mann–Kendall test (MKT), no significant (p > 0.05) trend in annual discharge from 1964 to 2013 is observed in the Bering Sea, western Arctic Ocean, western Hudson and James Bay, and Labrador Sea; for northern Canada as a whole, however, a statistically significant (p < 0.05) decline of 102.8 km3 25 yr−1 in discharge occurs over the first half of the study period followed by a statistically significant (p < 0.05) increase of 208.8 km3 25 yr−1 in the latter half. Increasing (decreasing) trends in river discharge to the eastern Hudson and James Bay (eastern Arctic Ocean) are largely explained by the Caniapiscau diversion to the La Grande Rivière system. Strong regional variations in seasonal trends of river discharge are observed, with overall winter (summer) flows increasing (decreasing, with the exception of the most recent decade) partly due to flow regulation and storage for enhanced hydropower production along the Hudson and James Bay, the eastern Arctic Ocean and Labrador Sea. Flow regulation also suppresses the natural variability of river discharge, particularly during cold seasons.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it