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Record W200714432

The Impact of Rochester Storm Sewers on the Water Quality of the Lower Genesee River: A Modeling Approach Using PCSWMM

2014· dissertation· en· W200714432 on OpenAlex
Lindsay Dressel

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSUNY Digital Repository Support (State University of New York System) · 2014
Typedissertation
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSanitary sewerStormEnvironmental scienceHydrology (agriculture)Water qualityWater resource managementCombined sewerStormwaterGeographyEnvironmental engineeringEngineeringMeteorologyGeotechnical engineeringSurface runoff
DOInot available

Abstract

fetched live from OpenAlex

The lower Genesee River suffers from beneficial use impairments from the mouth of the river at Lake Ontario to the New York State Barge Canal due to industrial and municipal sources, storm sewers, and urban runoff. In urban areas, nonpoint source pollution from stormwater runoff is known to be a dominant factor in water quality. An assessment of the lower Genesee River was initiated to determine impacts from the canal, storm sewers, combined sewer overflows, and a wastewater treatment plant. To accomplish this, an integrated approach combining water quality sampling, statistical analysis, and modeling was employed. A cluster analysis was performed on samples taken during hydrometeorologic events to determine natural groupings in storm sewer sites based on water quality. These events and results of the cluster analysis were used to calibrate and validate a model of the Rochester storm sewer network (ROCSWMM) using hydrologic modeling tool PCSWMM (Storm Water Management Model). Model-predicted flows, total phosphorus (TP) loads, and total suspended solid (TSS) loads to the Genesee River for 2012 were 19,197,116 m3, 2,277 kg P, and 625,694 kg, respectively. More than 50% of the total flow and 27% of the TP load discharged to the Genesee River from the storm sewer network came from the Merrill sewershed. The Irondequoit sewershed was the second largest contributor of stormwater (2,659,179 m3) and TP load (481 kg), and over half of the TSS load was contributed by the Merrill (29%) and KenElm (24%) sewersheds. Precipitation events resulted in four combined sewer overflows (CSOs) in 2012. Water from these discharges have extremely high concentrations of nutrients (727 ?g P/L to 4,180 ?g P/L), sediment (156 mg/L to 810 mg/L), and E. coli (282,720 MPN/100mL to 483,920 MPN/100mL.) Kodak King’s Landing Wastewater Treatment Plant (WWTP) was a large point source of water and pollutant loads to the Genesee River accounting for 0.5% of the total flow and 1.3% of the TP load of the Genesee River. Low impact developments (LIDs) were simulated in ROCSWMM to determine theoretical reductions in flows and loads to the Genesee River from the storm sewer network. Converting 25% of subcatchment impervious area to porous pavement reduced flow and TP and TSS loads by up to 15% and treating ten percent of impervious roof runoff with rain barrels could reduce flows and loads up to eight percent. Further research should be conducted to determine the placement of LIDs within subcatchments that will achieve the greatest reduction of inputs into the sewer system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.216
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it