Connecting past, present, and future trends of hydraulic and phosphorus loading in the Bay of Quinte tributaries, Ontario, Canada
Bibliographic record
Abstract
The Bay of Quinte watershed, located on the northeastern shore of Lake Ontario, Canada. Special focus is placed on the Napanee River and Wilton Creek catchments, where the presence of a subterranean network of conduits that facilitate groundwater-surface water interactions is conducive to an increase in the delivery of nutrients during storm events and can exacerbate the risk of eutrophication. Development of a rigorous modelling framework that can advance our understanding of past and present trends of streamflow and tributary phosphorus (P) concentration and loads. We also analyze future streamflow rates and P export trends in order to guide the long-term watershed management in the area. Our analysis is carried out through a comprehensive combination of data-driven and process-based models. Retrospective analysis provides evidence of a recent increase in the impact of nonpoint-source P pollution. General Circulation Models suggest a future increase in both temperature minima and maxima relative to present conditions (2002–2018). Precipitation projections are indicative of increased frequency of occurrence of high extreme precipitation events during the summer and mid-fall, when the Bay of Quinte is more susceptible to undesirable ecological shifts. Our study predicts a seasonality shift in the streamflow, with the spring freshet occurring earlier in the year accompanied by higher flow rates in the local creeks for the winter and early spring. We also examined the relationship between precipitation and streamflow across varying levels of flow regulation. Our analysis indicates that our predictive capacity declines with increased flow regulation as well as when streamflow rates are predicted by contemporaneous precipitation values.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".