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Record W2216829808 · doi:10.1080/07011784.2015.1089190

The 2013 flood event in the South Saskatchewan and Elk River basins: Causes, assessment and damages

2015· article· en· W2216829808 on OpenAlexafffundvenueabout
John W. Pomeroy, Ronald E. Stewart, Paul H. Whitfield

Bibliographic record

VenueCanadian Water Resources Journal / Revue canadienne des ressources hydriques · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsEnvironment and Climate Change CanadaUniversity of ManitobaSimon Fraser UniversityUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDamagesFlood mythHydrology (agriculture)Environmental scienceDrainage basinGeographyEvent (particle physics)Water resource managementGeologyArchaeologyCartographyGeotechnical engineering

Abstract

fetched live from OpenAlex

In late June 2013, heavy rainfall and rapidly melting alpine snow triggered flooding throughout much of the southern half of Alberta. Heavy rainfall commenced on 19 June and continued for 3 days. When the event was over, more than 200 mm and as much as 350 mm of precipitation had fallen over the Front Ranges of the Canadian Rocky Mountains. Tributaries to the Bow River including the Ghost, Kananaskis, Elbow, Sheep and Highwood, and many of their tributaries, all reached flood levels. The storm had a large spatial extent causing flooding to the north and south in the Red Deer and Oldman Basins, and also to the west in the Elk River in British Columbia. Convergence of the nearly synchronous floodwaters downstream in the South Saskatchewan River system caused record high releases from Lake Diefenbaker through Gardiner Dam. Dam releases in Alberta and Saskatchewan attenuated the downstream flood peak such that only moderate flooding occurred in Saskatchewan and Manitoba. More than a dozen municipalities declared local states of emergency; numerous communities were placed under evacuation order in Alberta and Saskatchewan. The media reported that more than 100,000 people needed to evacuate their homes, and five people died. At CAD$6 billion, the Province of Alberta estimated that it was the costliest natural disaster in Canadian history. At their peak, the water levels were the highest in the past 60 years, and nearing those of historic events of the late 1800s and early 1900s where records exist. There was major damage to infrastructure roads, bridges and culverts. Downtown Calgary was inundated, as were many communities such as High River and Bragg Creek. Debris flows and debris torrents affected communities such as Canmore and Exshaw, and isolated many mountain communities including closing the TransCanada Highway for several days. Environment Canada called it the “Flood of Floods.” Insured losses of CAD$2 billion included thousands of cars and homes demolished and damaged by backed-up sewers. Flood damage losses and recovery costs from the flood are projected to exceed CAD$6 billion.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.218
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations159
Published2015
Admission routes4
Has abstractyes

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