A Storm Water Runoff Model For Open Windrow Composting Sites
Bibliographic record
Abstract
Precipitation that falls on compost sites picks up organic material from the windrows and the composting pad. The resulting runoff can contain high levels of nutrients, suspended solids, and organic matter, making it unsuitable for direct release into a receiving water body. Many jurisdictions require that the runoff from these sites be collected in a detention pond. Unfortunately, some of the recommended or required procedures for quantifying the volume of runoff from these sites are based on archaic or inappropriate hydrologic models. The development of better hydrologic models for open composting operations has been hampered by a lack of basic information regarding rainfall/runoff relationships at windrow composting sites. In this paper, a standard hydrologic model — the unit hydrograph method – is used to model the hydrology of a small, paved composting site. The model results compare well with field data collected at the site over a six month period. The volume of runoff predicted by the model was within 5% of the measured runoff volume for each of seventeen runoff events observed at the site over the study period. The results suggest that other industry standard hydrologic models can be adapted for use at open composting sites to account for the presence of large quantities of organic material on the site.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".