Contribution of Overland and Tile Flow to Runoff and Nutrient Losses from Vertisols in Manitoba, Canada
Bibliographic record
Abstract
This study quantified the contributions of overland and tile flow to total runoff (sum of overland and tile flow) and nutrient losses in a Vertisolic soil in the Red River valley (Manitoba, Canada), a region with a cold climate where tile drainage is rapidly expanding. Most annual runoff occurred as overland flow (72–89%), during spring snowmelt and large spring and summer storms. Tile drains did not flow in early spring due to frozen ground. Although tiles flowed in late spring and summer (33–100% of event flow), this represented a small volume of annual runoff (10–25%), which is in stark contrast with what has been observed in other tile‐drained landscapes. Median daily flow‐weighted mean concentrations of soluble reactive P (SRP) and total P (TP) were significantly greater in overland flow than in tile flow ( p < 0.001), but the reverse pattern was observed for NO 3 –N ( p < 0.001). Overland flow was the primary export pathway for both P and NO 3 –N, accounting for >95% of annual SRP and TP and 50 to 60% of annual NO 3 –N losses. Data suggest that tile drains do not exacerbate P export from Vertisols in the Red River valley because they are decoupled from the surface by soil‐ice during snowmelt, which is the primary time for P loss. However, NO 3 –N loading to downstream water bodies may be exacerbated by tiles, particularly during spring and summer storms after fertilizer application. Core Ideas Overland flow was the primary pathway for runoff and nutrient loss at field edge. Most runoff and nutrient loss occurred during spring snowmelt and rain events. Tile drains are unlikely to exacerbate P losses from Vertisolic soils. Tile drains may enhance N loading in this region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".