Hydrological behaviour of an unregulated eastern slope river under changing historical climate
Bibliographic record
Abstract
The Elbow River is an eastern slope river with headwaters in the Rocky Mountains in Alberta whose major end-use is a critical source of municipal water for Calgary. Overwinter precipitation in its watershed falls primarily as snow and accumulates as snowpack until spring melt. Precipitation falls mainly as rain from May until October. The river is unregulated above Calgary’s water supply reservoir, and its relatively undeveloped watershed makes it ideal for examining potential climate change impacts on river hydrology. Available historical hydrometeorological data (1967 to 2015) from the basin were assessed to study its hydrological behaviour under a changing climate. The analysis showed significant upward trends in both flow and precipitation variables, especially from 1979 to 2015. Significant increases in both annual flow volume and annual maximum daily flow (AM-flow), and later seasonal occurrence of AM-flow, were not observed in other eastern slope rivers. Although these changes could attenuate predicted water supply shortages, they could also potentially increase flood magnitudes. The analysis also revealed that three sub-watersheds, which are approximately equal in geographic area, contributed differing flow volumes during the high-flow season (May to October). The upper watershed contributed most (∼68%), followed by the middle (∼26%) and lower (∼6%) watersheds, on average. Extreme high-flow events (ie >90th percentile AM-flow) were strongly related to high rainfall events, but not significantly related to snowpack loss (or melt). Moderate AM-flows were positively related to both the cumulative snowpack loss before the high-flow season and the cumulative antecedent precipitation prior to the AM-flow, suggesting that the antecedent soil moisture conditions could play a role. Predictions of climate change impacts on this eastern slope river’s hydrology should thus consider the effects of meteorological variables and the moisture conditions of the watershed.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".