Thermal Pollution Mitigation in Cold Water Stream Watersheds Using Bioretention
Bibliographic record
Abstract
Abstract This study examines the use of bioretention as a strategy to reduce the thermal impact associated with urban stormwater runoff in developing cold water stream watersheds. Temperature and flow data were collected during 10 controlled runs at a bioretention facility located in Blacksburg, Virginia. It was determined that bioretention has the ability to reduce the temperature of thermally charged stormwater runoff received from an asphalt surface. Significant reductions in peak and average temperatures ( p < 0.001) were observed. However, this facility was unable to consistently reduce the temperature below the threshold for natural trout waters in Virginia. The ability of bioretention to reduce runoff volume and peak flow rate also serves to reduce the hydrothermal impact. An average thermal pollution reduction of nearly 37 MJ/m 3 was calculated using an adopted threshold temperature of 20°C. Based on the results of this study, it was concluded that properly designed bioretention systems have the capability to reduce the thermal impact of urban stormwater runoff on cold water stream ecosystems.
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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 | 0.000 |
| 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".