Evaluating the Hydrological Performance of a Water Square with 2D Modeling and In Situ Monitoring
Bibliographic record
Abstract
In situ monitoring and numerical modeling tools are essential to quantify the advantages of stormwater management infrastructures and to improve their future designs. Such infrastructures offer effective solutions for decreasing runoff volume and mitigating surface sewer overflow issues in urban environments. This paper assesses the hydraulic and hydrologic performance of a stormwater management infrastructure using numerical modeling and in situ monitoring for a water square called Place des Fleurs-de-Macadam, located in a dense urban area in Montreal, Canada. This floodable park comprises a detention pond and bioretention cells that redirect and accumulate surface water from adjacent streets, enabling water infiltration and preventing excess water from surcharging the sewer system. The performance of the water square was evaluated with a coupled 1D/2D model in PCSWMM, as well as in situ monitoring, which was carried out by a flood test on site. The associated rainfall event was a three-hour rainfall of 62 mm, equivalent to a 100-year event for this area. Results obtained by numerical modeling and in situ monitoring indicated that urban stormwater runoff can be effectively mitigated. For the tested rainfall event, simulation and in situ monitoring results showed that the water square reduced the runoff volume by 98% and delayed outflows by two hours.
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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 | 0.002 | 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 | 0.000 |
| 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".