Water quality trends in the last decade for ten watersheds dominated by diffuse pollution in Québec (Canada)
Bibliographic record
Abstract
The aim of this work is to evaluate and discuss river water quality trends over the last decade in ten watersheds where diffuse pollution represents more than half of the annual load of phosphorus (P) and nitrogen (N). Trend analyses taking into account flow data indicate a significant reduction of total P in eight rivers, of ammonia N in five rivers, of nitrate + nitrite in four rivers, of total filtered N in three rivers and of suspended solids in two rivers. An increase of turbidity was observed in four rivers and, for fecal coliforms, no trends. P decrease can be explained by reduced mineral P inputs on cropped lands related to means such as agro-environmental fertilization plans and addition of phytase in pig and poultry feed. However, for seven of them, median P concentrations remain at least two times greater than the Québec water quality guideline for protection of rivers against eutrophication. Concentrations of other parameters remain problematic in some rivers too. These results indicate the need to continue the efforts for further diffuse pollution reduction. Future work should better quantify actions taken at the watershed scale to reduce diffuse pollution.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".