Evaluation of Future Streamflow Patterns in Lake Simcoe Subbasins Based on Ensembles of Statistical Downscaling
Bibliographic record
Abstract
Future streamflow patterns of three subbasins, i.e., East Holland, Beaver, and Pefferlaw River basins, located in the upstream of Lake Simcoe of Canada are assessed for 2021–2099. The individual set of parameters of a conceptual hydrological model, HBV (Hydrologiska Byråns Vattenbalansavdelning)-light, are first calibrated for these three subbasins. The calibrated model was validated and further used to estimate the future streamflow driven by statistically downscaled projected precipitation and air temperature from the Pacific Climate Impacts Consortium under Representative Concentration Pathways 8.5 and 4.5 scenarios. The uncertainty of annual streamflow, hydrograph, flow duration curve (FDC), and flood frequency were evaluated. The results reveal that the annual streamflows of the Beaver and Pefferlaw River Basins (PRB) are projected to slightly increase in 2020–2099 while the annual streamflows of the East Holland River Basin (EHRB) are expected to be similar in 2020–2099. The monthly streamflow in winter is projected to increase but to decrease in spring across three subbasins. Based on the projected FDCs, daily streamflow of EHRB and PRB will likely increase by 2070–2099.
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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 | 0.001 |
| 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 | 0.000 |
| 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".