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Record W2011363173 · doi:10.1002/hyp.7320

Spatial variation of snowmelt and sublimation in a high‐elevation semi‐desert basin of western Canada

2009· article· en· W2011363173 on OpenAlexaffabout
Scott I. Jackson, Terry D. Prowse

Bibliographic record

VenueHydrological Processes · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of VictoriaEnvironment and Climate Change Canada
Fundersnot available
KeywordsSnowmeltEnvironmental scienceSnowSnowpackHydrology (agriculture)Atmospheric sciencesMicroclimateMeltwaterGeologyGeographyMeteorology

Abstract

fetched live from OpenAlex

Abstract The Okanagan Basin, a semi‐desert region of western Canada, is currently experiencing rapidly increasing pressure on its water resources from development and population increases, exacerbated by changes in climate. The major source of freshwater in the region originates from the melt of high‐elevation snowpacks, about which little is currently known, including the proportion of the peak snowpack lost to sublimation. To better understand the hydrologic regime of this snow resource, a detailed field program was conducted during the 2007 snowmelt season. Specifically, peak annual snow distribution, ablation‐season surface‐energy exchange and mass balance were measured in a forested high‐elevation catchment of the Okanagan Basin. During the snowmelt period, 1–4% of the peak annual snow‐water equivalent (SWE) was lost to sublimation in open sites—averaging 0·4 mm d −1 . Melt and sublimation rates increased significantly with elevation, and were observed to be higher and more variable in the open sites than under forest canopies. The largest sublimation events (>0·25 mm d −1 ) were associated with low atmospheric vapour pressure, temperatures below 0 °C, and higher than average wind speeds. Condensation occurred under highly stable conditions in the boundary layer when sensible heat fluxes exceeded net radiative inputs to the snow surface. Melt rates were driven almost entirely by sensible heat fluxes and exceeded 30 mm d −1 during large‐scale advection events. The results from this study will allow water managers to better predict the amount of water available for ecological, agricultural and municipal needs. This work also provides the basis for assessing changes in snow surface energetics due to ongoing salvage cutting in forested areas affected by the current mountain pine‐beetle outbreak. Copyright © 2009 John Wiley & Sons, Ltd and Her Majesty the Queen in right of Canada.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.014
GPT teacher head0.199
Teacher spread0.184 · 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 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

Citations35
Published2009
Admission routes2
Has abstractyes

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