Modelling streamflow and phosphorus fluxes in the Lake of the Woods watershed
Bibliographic record
Abstract
This study provides an evaluation of streamflow and the spatial and temporal variability of phosphorus (P) fluxes for the transboundary Lake of the Woods (LoW) watershed using the Canadian version of the Soil and Water Assessment Tool (CanSWAT). The model calibration and validation generally indicate good performance for the simulated flow, especially for the Rainy River, the main tributary to LoW, while the sediment and nutrient calibration performance was satisfactory. Model results indicated Rainy River is the primary source of total phosphorus (TP), contributing about 88% of the external non-point source (NPS) and point source P loads to LoW, with the majority being NPS. Simulated TP loads varied seasonally with over approximately 60% occurring during the spring period and varied spatially across the LoW watershed. TP yields tended to be lower upstream of Rainy Lake in the Precambrian Shield (a.k.a., Canadian Shield) and higher downstream of Rainy Lake in the Glacial Lake Agassiz lakebed, particularly in the Lower Rainy and Little Fork sub-watersheds. Point sources along the Rainy River constituted the largest anthropogenic TP source. Tributary P loads estimated by the model were also used in a simple lake mass-balance model that suggested 32–46% of TP load to LoW was retained within the lake.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".