Concentration‐discharge relationships derived from a larger regional dataset as a tool for watershed management
Bibliographic record
Abstract
Abstract Concentration‐discharge (C‐Q) relationships have been widely used to assess the hydrochemical processes that control solute fluxes from streams. Here, using a large regional dataset we assessed long‐term C‐Q relationships for total phosphorus (TP), soluble reactive phosphorus (SRP), total Kjeldahl nitrogen (TKN), and nitrate (NO 3 ) for 63 streams in Ontario, Canada, to better understand seasonal regional behavior of nutrients. We used C‐Q plots, Kruskal‐Wallis tests, and breakpoint analysis to characterize overall regional nutrient C‐Q relationships and assess seasonal effects, anthropogenic impacts, and differences between “rising” and “falling” hydrograph limbs to gain an understanding of the dominant processes controlling overall C‐Q relationships. We found that all nutrient concentrations were higher on average in catchments with greater levels of anthropogenic disturbance (agricultural and urban land use). TP, SRP, and TKN showed similar C‐Q dynamics, with nearly flat or gently sloping C‐Q relationships up to a discharge threshold after which C‐Q slopes substantially increased during the rising limb. These thresholds were seasonally variable, with summer and winter thresholds occurring at lower flows compared with autumn and greater variability during snowmelt. These patterns suggest that seasonal strategies to reduce high flows, such as creating riparian wetlands or reservoirs, in conjunction with reducing related nutrient transport during high flows would be the most effective way to mitigate elevated in‐stream concentrations and event export. Elevated rising limb concentrations suggest that nutrients accumulate in upland parts of the catchment during drier periods and that these are released during rain events. NO 3 C‐Q patterns tended to be different from the other nutrients and were further complicated by anthropogenic land use, with greater reductions on the falling limb in more disturbed catchments during certain seasons. There were few significant NO 3 hydrograph limb differences, indicating that there was likely to be no dominant hysteretic pattern across our study region due to variability in hysteresis from catchment to catchment. This suggests that this nutrient may be difficult to successfully manage at the regional scale.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".