The Effects of Multiple Beneficial Management Practices on Hydrology and Nutrient Losses in a Small Watershed in the Canadian Prairies
Bibliographic record
Abstract
Most beneficial management practices (BMPs) recommended for reducing nutrient losses from agricultural land have been established and tested in temperate and humid regions. Previous studies on the effects of these BMPs in cold-climate regions, especially at the small watershed scale, are rare. In this study, runoff and water quality were monitored from 1999 to 2008 at the outlets of two subwatersheds in the South Tobacco Creek watershed in Manitoba, Canada. Five BMPs-a holding pond below a beef cattle overwintering feedlot, riparian zone and grassed waterway management, grazing restriction, perennial forage conversion, and nutrient management-were implemented in one of these two subwatersheds beginning in 2005. We determined that >80% of the N and P in runoff at the outlets of the two subwatersheds were lost in dissolved forms, ≈ 50% during snowmelt events and ≈ 33% during rainfall events. When all snowmelt- and rainfall-induced runoff events were considered, the five BMPs collectively decreased total N (TN) and total P (TP) exports in runoff at the treatment subwatershed outlet by 41 and 38%, respectively. The corresponding reductions in flow-weighted mean concentrations (FWMCs) were 43% for TN and 32% for TP. In most cases, similar reductions in exports and FWMCs were measured for both dissolved and particulate forms of N and P, and during both rainfall and snowmelt-induced runoff events. Indirect assessment suggests that retention of nutrients in the holding pond could account for as much as 63 and 57%, respectively, of the BMP-induced reductions in TN and TP exports at the treatment subwatershed outlet. The nutrient management BMP was estimated to have reduced N and P inputs on land by 36 and 59%, respectively, in part due to the lower rates of nutrient application to fields converted from annual crop to perennial forage. Overall, even though the proportional contributions of individual BMPs were not directly measured in this study, the collective reduction of nutrient losses from the five BMPs was substantial.
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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 | 0.000 |
| 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".