Projected Hydroclimatic Changes in Two Major River Basins at the Canadian West Coast Based on High-Resolution Regional Climate Simulations
Bibliographic record
Abstract
Abstract The impact of anthropogenic climate change on water resources and flood and drought risk is of great interest for impact modeling and to inform adaptation strategies. Here an analysis of hydroclimatic changes in the Fraser and Athabasca River basins in western Canada is presented, based on an ensemble of climate projections, which have been dynamically downscaled to 10-km resolution using the Weather Research and Forecasting Model in two configurations. The GCM ensemble comprises four independent integrations of the Community Earth System Model under the representative concentration pathway 8.5. Basin-integrated changes in the seasonal cycle of hydroclimatic variables, and the variability of water supply and flood and drought risk, are considered. It is found that fall and winter precipitation generally increase by 20%–30% toward the end of the century, while changes in summer precipitation are smaller and associated with high model uncertainty. Furthermore, a reduction in snowfall and an increase in evapotranspiration are projected. However, projected impacts on water resources east and west of the Rocky Mountains are quite different: in basins closer to the coast (west of the Rocky Mountains) higher temperatures lead to a transition from predominantly solid to liquid precipitation and a significantly weaker spring freshet, followed by drier summers. In the lee of the Rocky Mountains the spring freshet remains largely unaffected and in summer the increase in evapotranspiration (ET) is compensated by increasing precipitation, so that water balance changes appear to be small. It is further found that a shift in runoff seasonality near the coast may lead to significantly increased flood risk in fall.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".