Glacial Melt and Potential Impacts on Water Resources in the Canadian Rocky Mountains
Bibliographic record
Abstract
Abstract As a result of global climate change, glacial melt occurs worldwide. Major impacts are expected on the dynamics of aquifers and rivers in and downstream of mountain ranges. This study aims at quantifying the melt water input fluxes into the watersheds draining the Canadian Rocky Mountains and improving our knowledge about the fate of meltwater within the hydrological cycle. To this end, we use (1) time‐variable gravity data from GRACE satellites that are decomposed into water storage compartments; (2) an ensemble of glacier information: in situ observations, geodetic measurements, and a mass balance model; and (3) in situ surface water and groundwater level observations. The glacier mass balance model estimates a total ice mass change of ~43 Gt for the period 2002–2015, corresponding to an average of −3,056 (±2,275) MCM/yr (million cubic meters per year). 78% of the meltwater total flows west of the continental divide (to the Pacific Ocean), while 22% flows east of the continental divide (to the Arctic Ocean and Hudson Bay). However, the GRACE‐derived total water storage increases, suggesting that groundwater storage compensates for the glacial melt with an increase of 3,976 (±2,819) MCM/yr. A plausible explanation is that meltwater is not immediately flowing down in rivers but rather stored locally in aquifers. This hypothesis is supported by in situ river base flow observations, showing base flow increase in basins draining the ice melt, mostly west of the continental divide. Direct in situ evidences such as well water level time series are not sufficiently available to fully support this hypothesis.
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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 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".