Increasing discharge from the Mackenzie River system to the Arctic Ocean
Bibliographic record
Abstract
Abstract The Mackenzie River, Canada's longest and largest river system, provides the greatest Western Hemisphere discharge to the Arctic Ocean. Recent reports of declining flows have prompted concern because (1) this influences Arctic Ocean salinity, stratification and polar ice; (2) a major tributary, the Peace River, has large hydroelectric projects, and further dams are proposed; and (3) the system includes the extensive and biodiverse Peace–Athabasca, Slave and Mackenzie deltas. To assess hydrological trends over the past century that could reflect climate change, we analysed historic patterns of river discharges. We expanded the data series by infilling for short gaps, calculating annual discharges from early summer‐only records (typical r2 > 0.9), coordinating data from sequential hydrometric gauges (requiring r2 > 0.8) and advancing the data to 2013. For trend detection, Pearson correlation provided similar outcomes to non‐parametric Kendall's τ and Spearman's ρ tests. There was no overall pattern for annual flows of the most southerly Athabasca River (1913–2013), while the adjacent, regulated Peace River displayed increasing flows (1916–2013, p < 0.05). These rivers combine to form the Slave River, which did not display an overall trend (1917–2013). The more northerly, free‐flowing Liard River is the largest tributary and displayed increasing annual flows (1944–2013, p < 0.01, ~3.5% per decade) because of increasing winter, spring, and summer flows, and annual maximum and minimum flows also increased. Following from the tributary contributions, the Mackenzie River flows gradually increased (Fort Simpson 1939–2013, p < 0.05, ~1.5% per decade), but the interannual patterns for the Liard and other rivers were correlated with the Pacific Decadal Oscillation, complicating the pattern. This conclusion of increasing river flows to the Arctic Ocean contrasts with some prior reports, based on shorter time series. The observed flow increase is consistent with increasing discharges of the large Eurasian Arctic drainages, suggesting a common northern response to climate change. Analyses of historic trends are strengthened with lengthening records, and with the Pacific Decadal Oscillation influence, we recommend century‐long records for northern rivers. Copyright © 2016 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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".