Glacier Meltwater Contributions and Glaciometeorological Regime of the Illecillewaet River Basin, British Columbia,
Bibliographic record
Abstract
ABSTRACT This study characterizes the meteorological parameters influencing glacier runoff and quantifies recent glacier contributions to streamflow in the Illecillewaet River basin, British Columbia. The Illecillewaet is a glacierized catchment that feeds the Columbia River, with terrain, glacial cover, and topographic relief that are typical of Columbia River headwaters basins in southwestern Canada. Meteorological and mass balance data collected on Illecillewaet Glacier are used to develop and constrain a distributed model for glacier melt, based on temperature and absorbed solar radiation. The melt model is applied to all of the glaciers in the Illecillewaet River basin for the summers of 2009 to 2011. Modelled glacier runoff for the three years has an average value of 112 ± 12 × 106 m3, approximately 10 % of Illecillewaet River yields for 2009 to 2011. Glaciers contributed 25 % to August flows for the three years. On average, 66 % of modelled glacial discharge is derived from the seasonal snowpack, with the remaining 34 % resulting from the melting of glacier ice and firn. For the lowest flow year in the basin, 2009, snow and ice melt from glaciers in the basin contributed 14 % and 33%, respectively; 81 % of the August glacier runoff is derived from glacier storage (ice and firn). Climate sensitivity studies for Illecillewaet Glacier indicate that the glacier mass balance is strongly influenced by summer temperature, with a net balance change of −0.6 metres of water equivalent (m w.e.) under a 1°C warming. A 30 % increase in winter precipitation is needed to offset this. Our values are initial estimates, and long-term
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".