Herbicide and Nutrient Transport from an Irrigation District into the South Saskatchewan River
Bibliographic record
Abstract
Pesticides and nutrients can be transported from treated agricultural land in irrigation runoff and thus can affect the quality of receiving waters. A 3-yr study was carried out to assess possible detrimental effects on the downstream water quality of the South Saskatchewan River due to herbicide and plant nutrient inputs via drainage water from an irrigation district. Automated water samplers and flow monitors were used to intensively sample the drainage water and to monitor daily flows in two major drainage ditches, which drained approximately 40% of the flood-irrigated land within the irrigation district. Over three years, there were no detectable inputs of ethalfluralin into the river and those of trifluralin were less than 0.002% of the amount applied to flood-irrigated fields. Inputs of MCPA, bromoxynil, dicamba and mecoprop were 0.06% or less of the amounts applied, whereas that for clopyralid was 0.31%. The relatively higher input (1.4%) of 2,4-D to the river was probably due its presence in the irrigation water. Corresponding inputs of P (as total P) and N (as nitrate plus ammonia) were 2.2 and 1.9% of applied fertilizer, respectively. Due to dilution of the drainage water in the river, maximum daily herbicide (with the exception of 2,4-D) and nutrient loadings to the river would not have resulted in significant concentration increases in the river water. There was no consistent remedial effect on herbicides entering the river due to passage of the drainage water through a natural wetland. In contrast, a considerable portion of the nutrients entering the river originated from the wetland.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".