Nutrient release in drainage discharge from organic soils under two different agricultural water management systems
Bibliographic record
Abstract
Abstract The release of available nitrogen (N) and phosphorus (P) from agricultural tile drainage contributes to eutrophication in water bodies. To mitigate the harmful impact of nutrient release, drainage water management (DWM) has been proposed as a beneficial management practice that will limit N and P in tile drainage discharge. This study, conducted in the organic soils of the Holland Marsh, Ontario, assessed the nutrient water quality for 2 years (2015–2016) under DWM systems: controlled drainage (CD) comprising a series of stackable gates to manually control the water table level; and pumped drainage (PD) which uses a submersible pump within a collector well that discharges effluent when activated. The latter is the common method of field drainage in the Holland Marsh, however, there is limited comparable research for either DWM system. The data were separated into growing and fallow seasons as well as winter, spring, and summer seasons for trend analysis (winter: October–February; spring: March–May; summer: June–September). The nitrate (NO3‐N) concentrations, under CD, were found to be on average higher during the winter season (7.64 mg L−1) compared to the growing season (3.76 mg L−1). Furthermore, total N concentrations are positively correlated to discharge (R > 0.55). The average total P concentration increased during the summer period following fertilization; however, there was no correlation between P and drainage discharge throughout the duration of the study. The P concentrations depended more on nutrient inputs, rather than the discharge under CD. The log regression statistical relationship showed significant differences in nutrient levels compared to the mean at both sites, however, greater differences were found under CD. Under PD, the NO3‐N concentrations showed significant seasonal trends between the spring and winter (Pr > t: 0.0061) and summer (Pr > t: <0.0001). Overall, both CD and PD can reduce the amount of tile drain discharge, but the concentrations of N and P are not significantly reduced.
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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 | 0.000 | 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".