Evaluation and Demonstration of Stormwater Dry Wells and Cisterns in Millburn Township, New Jersey
Bibliographic record
Abstract
Since 1999, the Township of Millburn has required dry wells to accommodate additional flows from newly developed areas in order to mitigate local drainage and water quality problems.The primary objective of this USEPA funded project was to investigate the effectiveness of the Township of Millburn's use of on-site dry wells to limit stormwater flows into the local drainage system.This objective was achieved by collecting and monitoring the performance of dry wells during both short and long periods.The water quality beneath dry wells and in a storage cistern was also monitored during ten rain events.There were varying levels of dry well performance in the area, but most were able to completely drain within a few days.However, several had extended periods of standing water that may have been associated with high water tables, poorly draining soils (or partially clogged soils), or detrimental effects from snowmelt on the clays in the soils.The infiltration rates all met the infiltration rate criterion of the state guidelines for stormwater discharges to dry wells, but not the state regulations that allow only roof runoff to be discharged to dry wells and those that prohibit dry well use in areas of shallow water tables.Overall, most of the Millburn dry wells worked well in infiltrating runoff.The findings reported in this paper indicate that the dry wells did not significantly change any of the water quality concentrations of the effluent water compared to the influent water.The cistern system did result in significant reductions in bacteria levels.Although the dry wells provided no significant improvements in water quality for constituents of interest in the infiltrating water, they resulted in reduced mass discharges of flows and pollutants to surface waters and reduced runoff energy, a major cause of local erosion problems.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".