Planning Level Modeling of E. coli levels in a Suburban Watershed Using PCSWMM
Bibliographic record
Abstract
Scajaquada Creek, NY is an important urban stream in the Niagara River watershed, as it flows through suburban neighborhoods and high profile historical areas in the city of Buffalo.It is listed in the Department of Environmental Conservation's (DEC) statewide 2010 Section 303d List of Impaired Waters because of bacteria and dissolved oxygen impairments related to sewer overflows and urban runoff.This project used PCSWMM to model the hydrology of the headwater areas of Scajaquada Creek, from Lancaster to the Buffalo city line.Eight cross sections were surveyed along Scajaquada Creek for model input and seven subbasins were delineated.Daily flow data from a United States Geographical Survey (USGS) gauge station located at the Buffalo city line for the years 1989, 1990, 1992 and 1994 were used to calibrate and validate the model.Linear regression and the Nash-Sutcliffe coefficient of efficiency were used to assess goodness of fit.Model parameter values were very stable from year to year; r 2 values between observed and modeled flows ranged from 0.63 to 0.66 and Nash-Sutcliffe values ranged from 0.60 to 0.76.E. coli samples were collected at several sites along the creek, but most of the sampling focus to date has been at the USGS gauge station.Geometric mean E. coli levels in all seasons were higher at this site for storm events as compared to dry weather samples.Geometric mean E. coli levels during warmer months (May-early September) were higher for both storms
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".