Integrated Land and Water Scenarios of the Raisin River Watershed Using the SWAT Model
Bibliographic record
Abstract
Abstract This paper investigates the linkage between Canada's National Agri-Environmental Standards Initiative (NAESI) Biodiversity and Water themes by studying how patterns in terrestrial habitat, generated through land cover scenario modelling, influence water quality and quantity in the Raisin River watershed in southeastern Ontario. NAESI developed nonregulatory performance standards that define ideal and achievable levels of environmental quality. The indicators used to investigate the scenario risks included sediment and nutrient concentrations. The SWAT (Soil and Water Assessment Tool)-2005 model was calibrated and validated from 1985 to 2006 for current land cover and five other scenarios: potential natural vegetation (PNV); high biodiversity conservation (HBC); moderate biodiversity conservation; agricultural intensification with limited application of conservation direction; and agricultural intensification with no consideration of conservation direction (ANC). Scenario comparisons are provided for the average annual flow, and concentrations of total suspended sediment (TSS), total nitrogen, and total phosphorus for five watershed locations. The PNV scenario predicted the lowest total flows, and sediment and nutrient concentrations, and the ANC scenario predicted the highest sediment and nutrient concentrations. The SWAT median values for the HBC, "Current," and ANC scenarios at the outlet all exceeded the Ideal Performance Standards, except for the median TSS concentration of the HBC scenario.
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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 | 0.005 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".