Nutrient delivery by groundwater discharge to headwater streams in agricultural catchments
Bibliographic record
Abstract
Abstract Nutrient concentrations in riparian groundwater are variable from site to site, making it challenging to use these data to quantify nutrient fluxes contributed by groundwater discharge to headwater streams. Instead, we define event‐excluded baseflow (BFEE), and use stream discharge data and stream samples collected during BFEEto estimate groundwater discharge and loading of nutrients to the streams. Based on this method, in two study catchments (Thames River basin, Ontario, Canada) groundwater discharge during BFEEcontributed about 30% of the total streamflow and 20%–30% of the total loading of soluble reactive phosphorus (SRP) and nitrate. Previous estimates of baseflow using hydrographic separation techniques indicate that groundwater discharge likely contributes even larger fractions, ~50%–60% of flow in these catchments. We infer that groundwater likely contributes ~40% of the annual SRP load and ~ 50%–60% of the nitrate‐N load. These results indicate that groundwater discharge plays an important role in the nutrient loading to headwater streams. This reinforces the findings of earlier studies that have inferred a dominant influence of legacy reservoirs of nutrients in the subsurface of similar agricultural catchments on the loads of these nutrients in headwater streams.
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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 | 0.000 | 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".