Future water security under climate change: a perspective of the Grand River Watershed
Bibliographic record
Abstract
Abstract Climate change poses a threat to the water security of the Grand River Watershed (GRW) by altering the precipitation patterns and other weather variables, which affect streamflow and freshwater availability. Therefore, in this study, a Soil and Water Assessment Tool (SWAT) model for the GRW, Ontario, Canada, was used to assess the blue and green water scarcity for future periods for future sustainable management of freshwater resources in the region. The ensemble results predicted a warmer and wetter future for the GRW. The ensemble model result, when considering both emission scenarios and future periods, showed that blue water (BW) is projected to increase by 23–40% while green water storage (GWS) is projected to experience an overall decrease (2–8%). The results suggested that BW may become more scarce compared to green water in the future. The scarcity of BW is primarily due to the projected increase in population growth and water demand in the watershed. Green water scarcity in some regions indicated that changes in irrigation might be needed in the future in some parts of the watershed. The results indicate that the careful planning is essential for future water management in GRW.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".