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Record W2767259393 · doi:10.2166/nh.2017.024

Future streamflow simulation in a snow-dominated Rocky Mountain headwater catchment

2017· article· en· W2767259393 on OpenAlex
Ram P. Neupane, Jan Adamowski, Joseph D. White, Sandeep Kumar

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHydrology research · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsStreamflowEnvironmental scienceHydrology (agriculture)PrecipitationDrainage basinSnowClimate changeCatchment hydrologySnowmeltSoil and Water Assessment ToolClimatologyGeologyGeographyMeteorologyOceanography

Abstract

fetched live from OpenAlex

Abstract The Rocky Mountains in North America are comprised of headwater snow catchments that provide sustained seasonal flow downstream. Changes in streamflow over the last half century in these basins may be associated with changing climate with increased temperature and variable precipitation, shifting seasonal hydrology. We investigated potential changes in future hydrology in a Rocky Mountain headwater catchment by simulating water budgets of the Athabasca River located in Jasper National Park, Canada. Potential hydrologic changes were predicted using a calibrated version of the Soil and Water Assessment Tool (SWAT). Future discharge and other parts of the catchment water budget were projected based on the global circulation model (GCM) derived from the Special Report on Emission Scenarios (SRES) for the latter part of the century (2081–2099). A projected decrease in future precipitation resulted in reduced mean annual streamflow, by up to 86%, compared to the baseline period for the catchment. Projected summer streamflow decreased from 58 to 39%. Streamflow increased from 13 to 26% during the spring, dampening the dominance of summer peak-flow hydrology. Colder winters for the future scenarios increase the overall proportion of precipitation as winter snowfall. However, dramatically lower precipitation estimated for this basin will drive water limits for the future.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.037
GPT teacher head0.354
Teacher spread0.317 · 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