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Record W2021408664 · doi:10.1080/15715124.2014.903259

A flood risk assessment for the City of Chilliwack on the Fraser River, British Columbia, Canada

2014· article· en· W2021408664 on OpenAlexaffabout
Matthias Jakob, Kris Holm, Edgar Lazarte, Michael Church

Bibliographic record

VenueInternational Journal of River Basin Management · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsUniversity of British ColumbiaBGC Engineering (Canada)
FundersU.S. Army Engineer Institute for Water ResourcesU.S. Army Corps of Engineers
KeywordsFlood mythReturn periodFlooding (psychology)DikeFlood risk assessmentFloodplainFlood risk managementFlood mitigationPreparednessHazardEnvironmental science100-year floodWater resource managementGeographyEnvironmental planningEnvironmental resource managementHydrology (agriculture)EngineeringEcologyGeologyArchaeology

Abstract

fetched live from OpenAlex

Flood hazard management in Canada is predicated on an event of arbitrary return period – the ‘design flood’, which on the Fraser River is the flood of record, with an estimated return period of 500 years. Recent studies have demonstrated that the existing dikes will not contain design flood levels, in a location where the potential consequences of flooding have increased exponentially during the past century. This suggests that a hazard-based approach is questionable for effective flood management. A pilot flood risk assessment was completed for the City of Chilliwack, 80 km east of Vancouver. We assessed direct and indirect economic losses for three hypothetical dike breach scenarios for flood return periods from 100 to 1000 years. We estimate that total losses would exceed CND $1 billion (€720 million) for the flood scenarios examined, not including intangibles such as emotional and cultural losses, environmental contamination, or changes in the quality and abundance of aquatic and terrestrial habitat. The study concludes with recommendations that would lead to a risk-based decision-making framework for flood mitigation design and emergency preparedness.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.217
Teacher spread0.212 · 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.

Study designObservational
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

Citations5
Published2014
Admission routes2
Has abstractyes

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