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Record W4409698073 · doi:10.1007/s44292-025-00035-9

Moisture transport to British Columbia’s upper Nechako Watershed associated with three atmospheric rivers

2025· article· en· W4409698073 on OpenAlexafffundabout
Tamar Richards‐Thomas, Stephen J. Déry

Bibliographic record

VenueDiscover Atmosphere · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of Northern British Columbia
FundersEnvironment and Climate Change CanadaUniversité du Québec à Montréal
KeywordsWatershedEnvironmental scienceMoistureHydrology (agriculture)Atmospheric sciencesMeteorologyClimatologyGeographyGeology

Abstract

fetched live from OpenAlex

Abstract Atmospheric rivers (ARs) that reach British Columbia’s (BC’s) Coast Mountains undergo orographic lifting, leading to intense precipitation that impacts the region’s hydroclimatology. To assess the impact of ARs on the upper Nechako Watershed, the Tahtsa Ranges Atmospheric River Experiment (TRARE) collected detailed hydrometeorological data in this region during September and October 2021. For three case studies, primary pathways of moisture transport, water vapor budgets, and constancy of moisture transport across the upper Nechako Watershed are identified and quantified using TRARE observational and ERA5 reanalysis datasets. ARs associated with Events 3 and 5 had a southwest-to-northeast path with minimal temporal moisture variability. In contrast, Event 10 primarily followed a southeasterly-to-northwesterly pathway exhibiting more variable moisture transport. Although Events 3 and 5 are associated with weak ARs and Event 10 is indirectly linked to bombogenesis, they all contributed similar amounts (~ 10 9 kg s −1 ) to the water vapor budget for the upper Nechako. Additionally, stronger winds and higher steadiness of moisture transport are associated with copious precipitation across the upper Nechako, particularly along the basin’s southern and western boundaries. ARs that impact the upper Nechako therefore play a crucial role in replenishing water resources that sustain ecological systems, aquatic habitat, hydropower generation, and domestic water consumption.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.268
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.182
Teacher spread0.179 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

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