Parameterization and Application of Agricultural Best Management Practices in a Rural Ontario Watershed Using PCSWMM
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As agricultural production has continued to expand and intensify around the world, many models have been developed in an attempt to accurately predict the downstream impacts on water quality and quantity due to changes in on-farm management practices. In rural watersheds with complex stormwater conveyance systems, models designed for agricultural landscapes tend to inadequately represent the spatial and temporal resolution required in the simulation of hydraulic systems. The Storm Water Management Model (SWMM) was originally developed for urban watershed modelling, but its robust hydraulic simulation capabilities have been applied in conjunction with new tools developed within PCSWMM in order to simulate the downstream impacts of a suite of agricultural best management practices (BMPs) in a watershed in rural Ontario, Canada. Three simulation scenarios were run and results are reported for a single model subcatchment. Results show general agreement with literature reported nutrient reduction values, but more testing of these capabilities is required.
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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 | 0.001 |
| 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 it