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Record W2257980014 · doi:10.14796/jwmm.r246-03

Geoprocessing Tools for Surface and Basement Flooding Analysis in SWMM

2013· article· en· W2257980014 on OpenAlexvenueno aff
Eric White, James Knighton, Gary Martens, Matthew Plourde, Rajesh Rajan

Bibliographic record

VenueJournal of Water Management Modeling · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeoprocessingBasementGeologyCivil engineeringEngineeringRemote sensing

Abstract

fetched live from OpenAlex

A geoprocessing routine was used for the development of a modified combined sewer conveyance system model to aid in defining the magnitude of basement backups and surface flooding, which often occur in older urban areas served by combined sewer systems. Detailed stage-storage relationships (including both basement and surface flooding storage) were developed utilizing standard GIS tools, a geospatial sewer network, building footprint boundaries, and a high resolution digital elevation model. In addition to representing more accurate stage-storage volumes in SWMM, the routing of surface floodwater was also simulated. Predicted peak water elevations in the conveyance system were then post-processed in GIS to determine the location within each subcatchment where basement or surface flooding was experienced. This approach, when compared to a more traditional sewer system hydraulic model, resulted in more accurate flood volume and depth calculations. Additionally, this routine produced a more accurate representation of street and building flood inundation within the study area.

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.

How this classification was reachedexpand

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.034
GPT teacher head0.226
Teacher spread0.192 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2013
Admission routes1
Has abstractyes

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