Quantifying chloride retention and release in urban stormwater management ponds using a mass balance approach
Bibliographic record
Abstract
Abstract Chloride (Cl − ) in urban waterways largely originates from runoff containing deicing salts. Cl − is retained in watersheds after deicing ends, resulting in deleterious effects on aquatic biota. Stormwater management ponds (SWMPs), designed to mitigate ‘flashy’ urban runoff response, are known to impact pollutant transport. However, there is little information on what role SWMPs play in the timing and magnitude of Cl − transport over different timescales. This study quantifies the mass of Cl − retained in two SWMPs over varying timescales. Both ponds are in an urbanizing watershed in south‐central Ontario; one drains a commercial area, the other, a residential area. High frequency measurements of water level and specific conductivity, from which flow and Cl − concentration were derived, were taken with sensors at pond inlets and outlets. For one SWMP, data were also collected upstream and downstream of the confluence of the pond outflow and the receiving creek to quantify the in‐stream response to Cl − ‐laden pond outflows. The findings suggest that SWMPs likely play a role in watershed‐scale Cl − retention; one SWMP consistently retained Cl − while the other had variable retention and release of Cl − . In the receiving creek, Cl − concentrations downstream of the pond exceeded the acute toxicity threshold for aquatic organisms twice as often as concentrations upstream of the pond, and Cl − pulses corresponded to Cl − release events from the pond. The results of this study suggest that SWMPs concentrate spatially distributed salt inputs and modify the timing and magnitude of their release to receiving streams. Stream reaches that receive water inputs from SWMPs may be more vulnerable to Cl − toxicity than reaches that do not receive flow via SWMPs. The results of this study will help parameterize the role of SWMPs in watershed‐scale Cl − transport models and geospatial models of salt vulnerable areas.
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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".