Phosphorus loading to nearshore waters from legacy septic system groundwater plumes in a Great Lakes coastal community
Bibliographic record
Abstract
Groundwater impacted by wastewater effluent from household septic systems, common in coastal communities, is a recognized phosphorus (P) source to nearby lakes. However, the long-term impact of neighbourhood-scale septic system decommissioning (i.e., conversion to sewer connections) on this P loading is not well understood or quantified. The objective of this study was to investigate long-term P loading to Nottawasaga Bay from groundwater plumes of decommissioned septic systems in the coastal community of Wasaga Beach. Detailed groundwater sampling characterized a legacy P plume from a septic system decommissioned 35 years ago, revealing elevated soluble reactive phosphorus concentrations extending over 40 m and reaching the shoreline. Sorption and dispersion parameters required for neighbourhood-scale modelling were derived by simulating this persistent, long but thin P plume using a numerical model. Numerical simulations of P plumes from > 800 septic systems, 0.01–1.6 km from the shoreline and active < 65 years before decommissioning, revealed P mass discharge to the lake started after ~30 years and will continue for > 4000 years. Relatedly, the extended P transport meant the annual mass discharge rate to the lake was consistently < 1.3% of the annual mass input rate from septic systems to the aquifer, though it varied over time according to the septic systems’ distance from shore.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".