Feasibility of the Application of Integrated Stormwater Management for Land-Restricted Lakeside Villages: The Case Study of Portland, Ontario
Bibliographic record
Abstract
Many semi-urbanized lakeside villages face the problem of surface water quality deterioration owing to uncontrolled discharge of stormwater or the interaction of onsite wastewater disposal systems with the surface water. Traditional stormwater best management practices (BMPs), such as large-scale detention ponds, may not be feasible solutions for these villages, due to their small size and limited resources. The potential of lot-level stormwater BMPs, as part of a drainage-basin-based stormwater management plan, is investigated for a typical lakeside village in Portland, Ontario. HEC-HMS is used to estimate the optimum baseline storage of stormwater for the existing drainage basin. The effectiveness of rear yard ponding is obtained by comparing the integrated onsite storage provided by all applicable lots in the village to the baseline storage required. The movement of phosphorus is monitored at a typical lot to investigate the potential of enhanced flushing of subsurface wastewater effluent by ponded stormwater. Results from this study indicate that lot-level BMPs on their own will not provide much reduction in runoff volumes; however, they may form part of a larger integrated management plan once other potential issues with their implementation (including the possible flushing of wastewater constituents into the groundwater) are also addressed. This study does provide some useful information for water managers, as they seek solutions to water servicing issues in these small settings.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".