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Record W3185463963 · doi:10.5194/hess-2021-349

Recent hydrological response of glaciers in the Canadian Rockies to changing climate and glacier configuration

2021· article· en· W3185463963 on OpenAlexafffundabout
Dhiraj Pradhananga, John W. Pomeroy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsCanmore Museum and Geoscience CentreUniversity of Saskatchewan
FundersGlobal Water FuturesNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaEnvironment and Climate Change CanadaUniversity of TorontoParks CanadaCanada First Research Excellence FundCanada Research ChairsWilfrid Laurier UniversityCanada Foundation for InnovationAlberta Environment and Parks
KeywordsGlacierGlacier mass balanceSnowGeologyMeltwaterFirnGlacier morphologyElevation (ballistics)Climate changeClimatologyDigital elevation modelCryospherePhysical geographyIce streamGeomorphologySea iceOceanographyGeographyRemote sensing

Abstract

fetched live from OpenAlex

Abstract. Mountain snow and ice greatly influence the hydrological cycle of alpine regions by regulating both the quantity and seasonal variations of water availability downstream. This study considers the combined impacts of climate and glaciers changes due to recession on the hydrology and water balance of two high-elevation basins in the Canadian Rockies. A distributed, physically based, uncalibrated glacier hydrology model developed in the Cold Regions Hydrological Modelling platform (CRHM) was used to simulate the glacier mass balance and basin hydrology of Peyto and Athabasca Glacier basins in Alberta. Bias-corrected reanalysis data were used to drive the model. The model calculates the water balance of a glacierized basin, influenced by the surface energy and mass balance, and considering redistribution of snow by wind and avalanches. It was set up using hydrological response units based on elevation bands, surface slope and aspect, as well as changing land cover. Aerial photos, satellite images and Digital Elevation Models (DEM) were assimilated to represent the changing configurations of glacier area and the exposure of ice and firn. Observations of glacier mass balance, snow and glacier ice surface elevation changes at glacier and alpine tundra meteorological stations and streamflow discharge at the glacier outlets were used to evaluate the model performance. Model results indicated that both basins have undergone continuous glacier loss over the last three to five decades, leading to a 6–31 % reduction in glacierized area, a 78–109 % increase in ice exposure, and changes to the elevation and slope of the glacier surfaces. Diurnal temperature ranges are increasing, mainly due to increasing summer maximum daily temperatures. Annual precipitation is not changing much, but rainfall ratios are increasing. Basin hydrology was simulated over two periods, 1965–1975 and 2008–2018, using observed glacier configurations. The results show that changes in both climate and glacier configuration caused changes in melt rates and runoff, and a shift of peak flows from August to July. Glacier melt contributions increased from 27–61 % to 43–59 % of annual discharges. Recent discharges were 3–19 % higher than in the 1960s and 1970s. The results suggest that increased exposure of glacier ice and lower surface elevation due to glacier thinning were less influential in increasing streamflow than climate warming. Streamflow from these glaciers continues to increase.

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)0.000
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 score0.017
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.029
GPT teacher head0.233
Teacher spread0.204 · 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

Citations1
Published2021
Admission routes3
Has abstractyes

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