Comparison of CANWET and HSPF for water budget and water quality modeling in rural Ontario
Bibliographic record
Abstract
This study comparatively evaluates the Hydrological Simulation Program-FORTRAN (HSPF) model and the Canadian ArcView Nutrient and Water Evaluation Tool (CANWET) for non-point source pollution (NPS) management in rural Ontario watersheds. Both models were calibrated, validated, and applied to a 52 km2 headwater rural watershed known as the Canagagigue Creek near Elmira in the Grand River basin, Ontario, Canada. A comparison of the simulated and observed values for stream flow, surface runoff, subsurface runoff, evapotranspiration, and sediment yield showed that (Better Assessment Science Integrating Point and Nonpoint Sources) BASINS/HSPF and CANWET models have similar capabilities to simulate various hydrological processes at the watershed scale. The seasonal stream flow comparison between observed and simulated values from HSPF and CANWET showed Nash-Sutcliffe efficiency (Nash-E) coefficients of 0.80 and 0.72, respectively. The monthly comparison between the simulated and observed stream flow yielded Nash-E coefficients of 0.88 and 0.94 for HSPF and CANWET, respectively. Overall, both models predicted the components of the annual, seasonal, and monthly water budget accurately. There was a considerable difference in the monthly simulated sediment yield by both models. This difference is consistent with the surface runoff variation predicted by both models. Both models predicted sediment yield with early winter and spring storms which is typical for southern Ontario.
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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 | 0.007 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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 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".