Influence of Landscape and Cropping System on Phosphorus Mobility within the Pike River Watershed of Southwestern Quebec: Model Parameterization and Validation
Bibliographic record
Abstract
The hydrology, erosion processes and phosphorus mobility were modelled for the 630 km2 Pike River watershed, an important Quebec tributary of Lake Champlain. Given the recurring issue of cyanobacterial blooms in Missisquoi Bay, intervening to reduce the influx of phosphorus to the bay became a priority and led to an agreement between the governments of the province of Quebec and the state of Vermont. The model's parameterization was supported by a characterization and spatial representation of agricultural landscapes and production systems according to a field-scale partitioning of cultivated lands into over 2,400 hydrological response units, each distinctive in its combination of soil properties, topography, fertilizer inputs, and inclusion within one of 99 subwatersheds in the region under study. The model's calibration and validation were based on data from four hydrometric stations as well as the monitoring of water quality at the outlet of two small (six to eight km2) experimental watersheds of contrasting physical attributes. A differential setting of baseline values for the upstream and downstream portions of the watershed led to a better matching of hydrological model output to measured discharge on different branches of the Pike River, as well as a closer reproduction of sediment and phosphorus loads at the outlet of the two reference basins. On a watershed scale, the model-derived sediment and phosphorus loads showed a clear spatial pattern: under present soil and crop management methods, over 50% of modelled phosphorus loads originated over roughly 10% of the watershed's area. Typically, these areas showed high surface runoff depths, high erosion rates or significant phosphorus enrichment of the topsoil.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".