Thermal Enrichment of Stream Temperature by Urban Storm Waters
Bibliographic record
Abstract
The paper reviews and models thermal enrichment of an urban stream due to storm water. The study area is in the city of Portage, Michigan, which drains into Portage Creek through the Consolidated Drain. Continuous temperature has been monitored for the last year and half. Results suggest that pavement runoff affects the stream temperature. Portage Creek is a cold water habitat for fish such as trout. Temperature is one of the water quality parameters that affect cold water aquatic habitats. Especially during summer, impervious surfaces heat and rainwater carries heat to the streams. This phenomenon has not been previously modeled. The paper develops the concepts of heat flux between runoff and its surrounding, such as heat flux between runoff and the paving, paving and the substrate, rain drops and the paving, and runoff water and atmosphere etc. These processes include wet and dry conditions, time of the day and night, and conditions before rain, during rain, and after rain. A simplified spreadsheet model to simulate the heat budget for runoff from urban pavement is presented. The model requires detailed inputs for urban runoff at a fine time step. PCSWMM is used to simulate runoff and provide input to the thermal enrichment model.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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 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".