Enlargement and evolution of a semi‐alluvial creek in response to urbanization
Bibliographic record
Abstract
Abstract The impact of urbanization on stream channels is of interest due to the growth of cities and the sensitivity of stream morphology and ecology to hydrologic change. Channel enlargement is a commonly observed effect and channel evolution models can help guide management efforts, but the models must be used in the proper geologic and climatic context. Semi‐alluvial channels characterized by a relatively thin alluvial layer over clay till and a convex channel profile in a temperate climate are not represented in currently available models. In this study we: (i) assess channel enlargement; and (ii) propose a channel evolution model for an urban semi‐alluvial creek in Toronto, Canada. The system is 90% developed with an imperviousness of approximately 47%. Channel enlargement is assessed by comparing 50 year old construction surveys, a recent survey of a relic channel, low‐precision surveys of channel change over a 15 year period, and high‐precision surveys over a three year period. The enlargement ratio of the channel since 1958 is 2.6, but could be as high 8.2 in comparison with the pre‐urban channel. When the increase in flow capacity is considered, the enlargement ratio is 1.9 since 1958 and up to 6.0 in comparison with the pre‐urban channel. Channel enlargement continues in the contemporary channel at an estimated rate of 0.23 m2/year. A five stage model is presented to describe channel evolution in the lower reaches. In this model the coarse lag material from glacial sources provides a natural resilience to the bed and incision occurs only after the increased flows from urbanization are combined with higher slopes as a result of channel straightening or avulsions. Further research should be done to assess stream behaviour close to an identified geologic control point. Copyright © 2018 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".