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Record W2013154402 · doi:10.1175/jhm-d-14-0033.1

Hydroclimatic Aspects of the 2011 Assiniboine River Basin Flood

2014· article· en· W2013154402 on OpenAlexaffabout
Julian Brimelow, Kit K. Szeto, Barrie Bonsal, John Hanesiak, Bohdan Kochtubajda, Fraser A. Evans, Ronald E. Stewart

Bibliographic record

VenueJournal of Hydrometeorology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsAlberta Environment and Protected AreasMcMaster UniversityEnvironment and Climate Change CanadaUniversity of Manitoba
Fundersnot available
KeywordsFlood mythEnvironmental sciencePrecipitationSnowmeltFlooding (psychology)ClimatologyHydrometeorologyStructural basinFlood forecastingSpring (device)Flash floodDrainage basin100-year floodHydrology (agriculture)SnowStreamflowMeteorologyGeographyGeology

Abstract

fetched live from OpenAlex

Abstract In the spring and early summer of 2011, the Assiniboine River basin in Canada experienced an extreme flood that was unprecedented in terms of duration and severity. The flood had significant socioeconomic impacts and caused over $1 billion (Canadian dollars) in damage. Contrary to what one might expect for such an extreme flood, individual precipitation events before and during the 2011 flood were not extreme; instead, it was the cumulative impact and timing of precipitation events going back to the summer of 2010 that played a key role in the 2011 flood. The summer and fall of 2010 were exceptionally wet, resulting in above-normal soil moisture levels at the time of freeze-up. This was followed by record high snow water equivalent values in March and April 2011. Cold temperatures in March delayed the spring melt, resulting in the above-average spring freshet occurring close to the onset of heavy rains in May and June. The large-scale atmospheric flow during May and June 2011 favored increased cyclone activity in the region, which produced an anomalously large number of heavy rainfall events over the basin. All of these factors combined generated extreme flooding. Japanese 55-year Reanalysis Project (JRA-55) data are used to quantify the relative importance of snowmelt and spring precipitation in contributing to the unprecedented flood and to demonstrate how the 2011 flood was unique compared to previous floods. This study can be used to validate and improve flood forecasting techniques over this important basin; the findings also raise important questions regarding floods in a changing climate over basins that experience pluvial and nival flooding.

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 score0.412
Threshold uncertainty score0.998

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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

Citations15
Published2014
Admission routes2
Has abstractyes

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