Seeking More Cost-Efficient Design Criteria for Infiltration Trenches
Bibliographic record
Abstract
For many jurisdictions, the current design criteria for low-impact development practices (LIDs) including infiltration trenches require LIDs to provide enough storage capacity to store catchment runoff from the location’s 90th-percentile storm. The 90th-percentile storm used in Ontario, Canada, has a depth of approximately 25 mm. This study examines the performances and costs of infiltration trenches built in Ontario but sized to accommodate alternative storm depths ranging from 5 to 50 mm. Analytical equations are used to determine the runoff reduction ratios of infiltration trenches, and a cost estimation tool specifically developed for LIDs is used to estimate their overall costs. Results indicate that the current 90th-percentile storm criterion is probably too high and not cost efficient. An evidence-based methodology for selecting more appropriate design criteria is proposed. Using this methodology, it was found that the economically more efficient design criterion for Ontario averages about 20–22 mm for different design cases. Significant savings can be realized if a lower design criterion is implemented. The proposed methodology is therefore recommended for jurisdictions seeking more cost-efficient design criteria.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".