Stormwater Runoff Reduction Achieved by Green Roofs: Comparing SWMM Method to TR-55 Method
Bibliographic record
Abstract
This research uses the EPA Storm Water Management Model (SWMM) to simulate runoff generated by impervious roofs and green roofs. Simulation results are compared with previous simulation results using Natural Resources Conservation Service Technical Release-55 (tr-55) and measurement by the British Columbia Institute of Technology (BCIT). Findings show that SWMM's Green-Ampt method can calculate more accurate runoff coefficients of impervious roofs than tr-55's Curve Number method. Annual runoff coefficients are 0.88 by SWMM, 0.6 by tr-55 and 0.93 by BCIT's measurement. However, using SWMM's Green-Ampt method alone does not accurately simulate green roof runoff. Green roof runoff is more accurately simulated by combining the Green-Ampt method with evapotranspiration of green roofs. According to BCIT's measurement, runoff reduction rates of monitored green roofs are 24% and 21%. As determined by combining the Green-Ampt method with evapotranspiration of green roofs, the potential runoff reduction achieved by green roofs is 20%.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".