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Risk of Exceeding Extreme Design Storm Events under Possible Impact of Climate Change

2015· article· en· W1561732720 on OpenAlexafffundabout
Chun‐Chao Kuo, Thian Yew Gan

Bibliographic record

VenueJournal of Hydrologic Engineering · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Alberta
FundersWestern Canada Research GridCompute CanadaNational Center for Atmospheric Research
KeywordsStormEnvironmental scienceClimate changeReturn periodClimatologyStorm trackFlooding (psychology)MM5MeteorologyFlood mythGeographyPrecipitationGeology

Abstract

fetched live from OpenAlex

Given the risk of intensive storms (the probability of exceeding certain storm intensity one or more times within the project life) of central Alberta is expected to change in the future, a new risk chart is proposed which represents the nonlinear relationship between storm intensity, design project life, and the risk of intensive storms being exceeded within the project life. First, a comparison between estimated risk charts of the past (1914–1995) and the present (1984–2010) for central Alberta shows that the risk of intensive storms occurring has increased for all storm durations in recent years, and the risk had been higher for storms of large return periods (≥50 year). Given a design project life of 50 years, the average increase in risk is 9%. Second, the uncertainty associated with projecting the risk of intensive storms occurring in 2011–2100 was assessed by considering three special reports on emissions scenarios (SRESs) of four global climate models (GCMs) dynamically downscaled by a regional climate model (RCM), i.e., MM5. Based on storms simulated by MM5 for central Alberta forced by SRES climate scenarios of Intergovernmental Panel on Climate Change (IPCC) for 2011–2100, the median risk for short-duration storms (≤1 h) of a design project life of 25 and 50 years is projected to increase up to 37 and 38%, respectively. In other words, climate change impact could increase the vulnerability of central Alberta to the hazards of flooding by intensive storms in future. The proposed risk chart presents the risk in a straightforward and meaningful way which will be useful for the long-term planning and engineering design of municipal infrastructure.

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)0.002
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 score0.138
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.000
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 head0.095
GPT teacher head0.273
Teacher spread0.178 · 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

Citations14
Published2015
Admission routes3
Has abstractyes

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