Using a Gravel Quarry for Raw Water Storage: A Water Quality Modeling Case Study of the Rock Hill Quarry Reservoir
Bibliographic record
Abstract
To help improve the drought-resiliency of its potable water system, the Athens-Clarke County (ACC) Public Utilities Department (PUD) is evaluating the feasibility of using the Rock Hill Quarry (RHQ) as a future raw water storage reservoir. The quarry reservoir would store nearly 5 billion gallons of water from a local river, and supply the water as needed to the ACC PUD distribution system. To support a feasibility assessment and evaluation of water treatment options, a reservoir hydrodynamic and water quality model of the quarry was developed in CE-QUAL-W2 to simulate reservoir operations and water quality dynamics over a 10-year period for two reservoir storage sizes. In-reservoir water quality dynamics and the range of water quality constituent parameter values in water withdrawn from the multi-level outlet system were quantified. Model results indicated seasonal anoxia may form near reservoir bed sediments at relatively smaller storage levels due to thermal stratification, but this phenomenon is not observed at relatively larger storage levels. The range of modeled water quality constituent concentrations within the reservoir and in adit withdrawals was generally within primary and secondary maximum contaminant levels for public water supplies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".