Economic benefits of controlled tile drainage: Watershed Evaluation of Beneficial Management Practices, South Nation River basin, Ontario
Bibliographic record
Abstract
Controlled tile drainage (CTD) is an agricultural beneficial management practice that can boost crop yields and reduce water and nutrient export from fields to surface water systems. This study examined on-farm incremental net benefits resulting from retrofitting existing tile drainage systems with inline water level control structures that control tile drainage. Corn and soybean yields (2005–2009) were respectively about 3 and 4% higher from CTD fields relative to conventionally drained fields at an experimental watershed associated with the Watershed Evaluation of Beneficial Management Practices (WEBs) program located in the South Nation river basin in eastern Ontario. The marginal cost of CTD employed in this experimental watershed was ∼Can (2006) $30 ha−1. The benefit–cost ratio was 2.6 for corn and 1.6 for soybean. A crude estimate of a payback period (without cost share) was from 3 to 4 years. Assuming all cropland in the entire South Nation river watershed where CTD is suitable, will be under CTD, the net present value of this practice is estimated to yield on farm annually about $(2006) 4 million for both crops. A crude estimate of non-user off-farm benefits of implementing CTD in this manner was ∼$0.4 million per year.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".