Thermal Mitigation of Stormwater Management Pond Outflows Using Geothermal Cooling
Bibliographic record
Abstract
During warm weather, urban surfaces heat up in the sun. Runoff from these surfaces during rain events is much warmer than under natural conditions. Warming is increased in stormwater management ponds due to solar heating. Without intervention, stormwater management pond outflows often exceed temperature thresholds set for the protection of aquatic ecosystems. Several strategies and technologies exist to mitigate outflow temperatures. Using monitoring data from a recent pilot project, we present geothermal cooling as a new thermal mitigation option. The pilot was implemented in a stormwater management pond located in Brampton, Ontario in 2019. The geothermal cooling system used a surface water heat exchanger to absorb excess heat energy from the warm stormwater outflows and, via a circulating hydronic fluid in a closed circuit, it rejected that heat energy to the deep ground using a vertical borehole. A system model was developed that was in good agreement with the monitoring data. The model was used to estimate the size of a full scale system for the pond. This pilot demonstrates several key benefits of geothermal cooling. It has good performance, and it is also cost-effective, scalable, retrofittable, space efficient and highly engineerable, and it has minimal visual impact on the pond.
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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 | 0.000 | 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) | 0.000 | 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".