Impacts of Changing Climatic Conditions in the Upper Thames River Basin
Bibliographic record
Abstract
This paper presents the application of the inverse approach in the study of high and low flows due to changing climatic conditions in the Upper Thames River basin, southwestern Ontario. The inverse approach is an alternative to statistical downscaling of global circulation model outputs, typically used in climate change studies. At the core of the inverse approach is a weather generator model that uses locally observed climate data, together with outputs from global circulation models, to generate an arbitrary long record of regional climatic conditions. A base case and two climate scenarios are produced by a weather generator, whose output is used as input into: (a) an event hydrologic model (for high flows); and (b) a continuous hydrologic model (for low flows). Changing hydrologic conditions are identified through frequency analysis for both flood and low flow hydrographs (obtained as outputs from hydrologic models). Changes in local water resources management practices, guidelines and design standards are recommended on the basis of the analysis of altered climates and their impacts on the hydrologic flow regime.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".