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Record W2519898953 · doi:10.1002/hyp.10957

Changes to flood peaks of a mountain river: implications for analysis of the 2013 flood in the Upper Bow River, Canada

2016· article· en· W2519898953 on OpenAlexaffabout
Paul H. Whitfield, John W. Pomeroy

Bibliographic record

VenueHydrological Processes · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of SaskatchewanEnvironment and Climate Change Canada
Fundersnot available
KeywordsSnowmeltFlood mythStreamflowHydrology (agriculture)Drainage basinClimate changeEnvironmental scienceStormGlacierPhysical geographySnowGeographyGeologyMeteorologyOceanography

Abstract

fetched live from OpenAlex

Abstract The mountain headwater Bow River at Banff, Alberta, Canada, was subject to a large flood in June 2013, over which considerable debate has ensued regarding its probability of occurrence. It is therefore instructive to consider what information long‐term streamflow discharge records provide about environmental change in the Upper Bow River basin above Banff. Though protected as part of Banff National Park, since 1885, the basin has experienced considerable climate and land cover changes, each of which has the potential to impact observations, and hence the interpretations of flood probability. The Bow River at Banff hydrometric station is one of Canada's longest‐operating reference hydrological basin network stations and so has great value for assessing changes in flow regime over time. Furthermore, the station measures a river that provides an extremely important water supply for Calgary and irrigation district downstream and so is of great interest for assessing regional water security. These records were examined for changes in several flood attributes and to determine whether flow changes may have been related to landscape change within the basin as caused by forest fires, conversion from grasslands to forest with fire suppression, and regional climate variations and/or trends. Floods in the Upper Bow River are generated by both snowmelt and rain‐on‐snow (ROS) events, the latter type which include flood events generated by spatially and temporally large storms such as occurred in 2013. The two types of floods also have different frequency characteristics. Snowmelt and ROS flood attributes were not correlated significantly with any climate index or with burned area except that snowmelt event duration correlated negatively to the Pacific Decadal Oscillation. While there is a significant negative trend in all floods over the past 100 years, when separated based on generating process, neither snowmelt floods nor large ROS floods associated with mesoscale storms show any trends over time. Despite extensive changes to the landscape of the basin and in within the climate system, the flood regime remains unchanged, something identified at smaller scales in the region but never at larger scales. Copyright © 2016 John Wiley & Sons, Ltd.

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)0.002
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 score0.023
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.018
GPT teacher head0.239
Teacher spread0.221 · 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

Citations48
Published2016
Admission routes2
Has abstractyes

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