Future Climate Change Impacts on Snow and Water Resources of the Fraser River Basin, British Columbia
Bibliographic record
Abstract
Abstract Changes in air temperature and precipitation can modify snowmelt-driven runoff in snowmelt-dominated regimes. This study focuses on climate change impacts on the snow hydrology of the Fraser River basin (FRB) of British Columbia (BC), Canada, using the Variable Infiltration Capacity model (VIC). Statistically downscaled forcing datasets based on 12 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are used to drive VIC for two 30-yr time periods, a historical baseline (1980–2009) and future projections (2040–69: 2050s), under representative concentration pathways (RCPs) 4.5 and 8.5. The ensemble-based VIC simulations reveal widespread and regionally coherent spatial changes in snowfall, snow water equivalent (SWE), and snow cover over the FRB by the 2050s. While the mean precipitation is projected to increase slightly, the fraction of precipitation falling as snow is projected to decrease by nearly 50% in the 2050s compared to the baseline. Snow accumulation and snow-covered area are projected to decline substantially across the FRB, particularly in the Rocky Mountains. Onset of springtime snowmelt in the 2050s is projected to be nearly 25 days earlier than historically, yielding more runoff in the winter and spring for the Fraser River at Hope, BC, and earlier recession to low-flow volumes in summer. The ratio of snowmelt contribution to runoff decreases by nearly 20% in the Stuart and Nautley subbasins of the FRB in the 2050s. The decrease in SWE and loss of snow cover is greater from low to midelevations than in high elevations, where temperatures remain sufficiently cold for precipitation to fall as snow.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".