Demonstration of Managed Aquifer Recharge in a Coastal Plain Aquifer: Lessons Learned
Bibliographic record
Abstract
Abstract The sustainable water initiative for tomorrow (SWIFT) is a 378,000 m 3 /day (100 MGD) managed aquifer recharge (MAR) program designed by the Hampton Roads Sanitation District (HRSD) to rehabilitate the Potomac Aquifer System (PAS) in the Coastal Plain of Eastern Virginia. Groundwater is a primary water source in Eastern Virginia with over 93% of reported use derived from the PAS. Starting in May 2018, HRSD has operated a 3780 m 3 /day (1.0 MGD) MAR demonstration facility at the SWIFT Research Center (SWIFT‐RC) in Suffolk, Virginia. The primary aim of the SWIFT‐RC is to demonstrate, at a meaningful scale, the feasibility of MAR using deep well recharge into confined PAS hydrostratigraphic unit. The SWIFT‐RC employs advanced water treatment technology to bring secondary effluent from an HRSD wastewater treatment plant to drinking water standards. Lessons learned include the evaluation and selection of a multiple barrier carbon‐based treatment system to ensure water quality and maintain geochemical compatibility between MAR water and native groundwater, and the evaluation and selection of aluminum chlorohydrate for stabilizing aquifer clays immediately around the well to accept the fresher recharge water. The distribution of flow in the SWIFT‐RC multiscreen recharge well and associated well injectivity were variable with time resulting from changing conditions in the well. Dynamic recharge well performance was quantified through the combined analysis of intrinsic and artificial tracer transport, in situ flowmeter testing, and water level analysis. Monitoring well nests and a depth‐discrete sampling system supported a robust sampling plan to analyze chemical transport and attenuation in SWIFT‐RC groundwater.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".