Level of service (LOS) assessment of stormwater infrastructure systems: a case study for cost-benefit analysis of low-impact development practices
Bibliographic record
Abstract
Stormwater infrastructure system (SWIS) is a main component of a municipal infrastructure system that safely passes excess runoff, controls floods, and manages pollutant discharges. A comprehensive literature review has revealed that stormwater infrastructure level of service (LOS) assessment, an important step in asset management, has been abstractly defined. LOS assists in infrastructure performance assessment as well as investment decision-making. This research proposes a methodological framework for LOS assessment of SWIS and adopts the proposed method in asset management decision-making. A hierarchical framework was developed to assess the LOS by using key performance indicators. The proposed framework was demonstrated in a case study for a municipality in Southwestern ON. To improve the LOS of sub-catchments with low LOS, low-impact development (LID) controls were proposed. The cost-benefit analysis revealed that an investment of $110 950 in LIDs could increase the LOS by 26.4% (from medium to good).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".