Water quality evaluation under climate change impacts for Canagagigue Creek watershed in southern Ontario
Bibliographic record
Abstract
With SDSM downscaling based on historical weather data, this thesis develops the future weather scenario with climate change consideration during 2015-2044, and then uses the scenario as input to the calibrated and validated hydrologic model, SWAT for water quantity and quality analysis, focusing on stream flow, sediment erosion and transportation at a watershed level. This thesis concludes that SDSM is able to simulate the daily historical temperature more efficiently than daily precipitation. Warmer winters and hotter summers may be expected during 2015-2044; higher mean and variance of the amounts of precipitation in summer may be expected without statistic significance; the future stream flows may have longer low flow periods extending from summer to fall, and severe annual water resources deficiency may be highly possible during 2015-2044 due to increased evapotranspiration. As a result, sediment transport capacity of reaches may decrease, and thus sediment deposition may be common phenomena.
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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 | 0.000 | 0.001 |
| 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".