Modeling Investigation to Support Integrated Water Management in Southern Ontario: Considering Climate Change and Urbanization
Bibliographic record
Abstract
Confronted with an array of water management related challenges, Canadian municipalities are beginning to appreciate the myriad benefits of integrating initiatives for municipal water management. This integrated approach to water governance is intended to maintain the integrity of water sources, reduce damages from flooding, and promote environmental health through collaborative water management initiatives at a catchment level. In the interest of assessing the impact of urban development on flood risk, a model was developed to simulate the hydrological impacts of upstream development on downstream communities for a small catchment in Southern Ontario. Runoff hydrographs were determined through USEPA SWMM simulations for (1) pre-development, (2) post-development (status quo), and (3) green infrastructure development. The runoffs from these three scenarios are described using climate adjusted design storms of duration 1 h, 6 h and 24 h at return frequencies of 2 y, 10 y and 100 y. The effects of these events on flood risk to downstream communities were evaluated using a HEC-RAS simulation of a 2 km river reach.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".