Spatial and temporal characteristics in streamflow-related hydroclimatic variables over western Canada. Part 1: 1950–2010
Bibliographic record
Abstract
A large portion of the freshwater in western Canada originates as snowpack from the northern Rocky Mountains. Temperature and precipitation in the region control the amount of snow accumulated and stored throughout the winter, and the intensity and timing of melt during the spring freshet. Therefore, trends in temperature, precipitation, snow accumulation, and snowmelt over western Canada are examined using the Mann-Kendall non-parametric test and an original geographic information system (GIS)-based approach to trend analysis on a newly produced high-resolution gridded climate dataset for the period 1950–2010. Temporal and spatial analyses of these hydroclimatic variables reveal that daily minimum temperature has increased more than daily maximum temperature, particularly during the cold season, and at higher elevations, contributing to earlier spring melt. Precipitation has decreased throughout the cold season and increased in the warm season, particularly in the northern half of the study area. Snow accumulation has decreased through all months of the year while snowmelt results indicate slight increases in mid-winter melt events and an earlier onset of the spring freshet. This study provides a summary of detected trends in key hydroclimatic variables across western Canada regarding the effects these changes can have on the spring freshet and streamflow throughout the region.
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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 | 0.004 |
| 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) | 0.001 | 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".