MétaCan
Menu
Back to cohort
Record W2591213454 · doi:10.14796/jwmm.c425

Modeling Investigation to Support Integrated Water Management in Southern Ontario: Considering Climate Change and Urbanization

2017· article· en· W2591213454 on OpenAlexaffvenueabout
M. de Lange, Edward A. McBean

Bibliographic record

VenueJournal of Water Management Modeling · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsUrbanizationClimate changeEnvironmental resource managementEnvironmental planningGeographyEnvironmental scienceWater resource managementOceanographyEconomic growthGeologyEconomics

Abstract

fetched live from OpenAlex

Confronted with an array of water management related challenges, Canadian municipalities are beginning to appreciate the myriad benefits of integrating initiatives for municipal water management. This integrated approach to water governance is intended to maintain the integrity of water sources, reduce damages from flooding, and promote environmental health through collaborative water management initiatives at a catchment level. In the interest of assessing the impact of urban development on flood risk, a model was developed to simulate the hydrological impacts of upstream development on downstream communities for a small catchment in Southern Ontario. Runoff hydrographs were determined through USEPA SWMM simulations for (1) pre-development, (2) post-development (status quo), and (3) green infrastructure development. The runoffs from these three scenarios are described using climate adjusted design storms of duration 1 h, 6 h and 24 h at return frequencies of 2 y, 10 y and 100 y. The effects of these events on flood risk to downstream communities were evaluated using a HEC-RAS simulation of a 2 km river reach.

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 score0.068
Threshold uncertainty score0.605

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 science0.0000.001
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 head0.047
GPT teacher head0.236
Teacher spread0.188 · 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

Citations7
Published2017
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Water Management ModelingSame topicHydrology and Watershed Management StudiesFrench-language works237,207