Climate change effect on water quantity in southern Ontario watersheds
Bibliographic record
Abstract
Effective adaptation to climate change requires knowledge of how climate will change and how the changes will affect the environment. The objective of this research is to examine the impacts of climate change on water resources (streamflow and runoff). Daily future climate change scenarios at the watershed scale have been developed using ClimGEN, a stochastic weather generator, linked with CGCM2 outputs. The developed climate scenarios are then transformed into river flows of two study watersheds by CANWET, a hydrologic model specifically tailored to meet the needs of Ontario Environmental policies and regulations. The climate change scenario evaluated suggests decreases of monthly runoff and streamflow for spring and summer, and a significant increase for winter. The predicted results suggest that earlier spring peak flows, and more even distribution of spring peaks can be expected under the future climate scenario although average annual streamflow and runoff are expected to decrease. The findings of this research can provide information for policy makers to identify and eliminate barriers and disincentives to adaptation.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".