The effect of water table management on the migration of phosphorus and on grain corn yields
Bibliographic record
Abstract
Due to recent research suggesting that water table management (WTM) can significantly reduce nitrate (NO3") loads in agricultural drainage, a study was carried out in 2001 and 2002 in Coteau-du-Lac, 60 km west of Montreal, to investigate the effect of water table management on the migration of phosphorus (P) via tile drainage and surface runoff. The second main objective was to study the influence of WTM on grain corn yields. Two drainage treatments were compared: conventional free drainage and WTM (combined controlled drainage and subirrigation) with a design water table depth at 0.6 m below the ground surface. Tile drainage and surface runoff were monitored and sampled automatically. Increased outflow volumes and concentrations - and therefore increased P loads - were measured in drainage water from plots under WTM. Plots under WTM also generally exhibited higher P loads in surface runoff. Higher P concentrations in surface runoff from plots under WTM were observed in surface runoff, especially during winter. Phosphorus loads from combined tile drainage and surface runoff were low compared with literature data (<0.4 kg/ha/year). However, the mean P concentrations in tile drainage were above Quebec's surface water quality standard of 0.03 mg total P/L during both growing seasons in plots under WTM, but not in plots with conventional free drainage. Mean P concentrations in surface runoff water routinely exceeded the criteria, except in plots with conventional free drainage in winter 2002. Therefore, P from tile drainage and surface runoff could contribute to the eutrophication of surface water. Based on these results, WTM increases P loads from the field, both in tile drainage and surface runoff. However, the well water used for subirrigation was found to contain P concentrations above Quebec's surface water quality standard, and this could partly explain the higher P concentrations found in water from plots under WTM. Water table management increased grain corn yields by 35% in both years. The growing seasons of 2001 and 2002 were among the driest ever recorded in Canada.
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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 | 0.000 | 0.000 |
| 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".