Climate change impacts on agriculture dominated Canadian watershed
Bibliographic record
Abstract
Agricultural water management plays a vital role in the food production and food security(Abbaspour, et al. 2007).Improper management of agriculture leads to local or far field water quality.Runoff from an agriculture land is considerably enriched with different kinds of nutrients, sediments, and pesticides. Nutrient loadings carried with the runoff has caused eutrophication to various degrees and scales, from small and large bays around the Great Lakes (e.g., Green Bay in Lake Michigan) to wide-scale eutrophication in some of the Great Lakes themselves (e.g., Lake Erie)(Inamdar, S. and Naumov, A. 2006)..Water quality and watershed management programs are highly benefitted from simulation models since the advent of computer-based watershed models( Daggupati et al. 2018). To this extent, present study used Soil and Water assessment Tool (SWAT) to investigate the climate change impacts on nutrient loadings primarily occur from runoff from a Canadian agriculture dominated watershed. We found that non-point source pollutants especially total N and total P originating from agriculture land is decreasing during mid and late century projections. Streamflow during winter and fall is projected to increase compared to historical period.
 Keywords: SWAT modeling, climate change impact, non-point source pollution
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 teacher head, 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".