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Record W4411629985 · doi:10.1016/j.ejrh.2025.102562

Streamflow generation, hydroclimatic changes, and flood mechanisms in the Sheep River basin on the eastern slopes of the Canadian Rockies

2025· article· en· W4411629985 on OpenAlexafffundabout
Cuauhtémoc Tonatiuh Vidrio‐Sahagún, Harshini Sendhil, Jianxun He, B Newton, M. Cathryn Ryan, S. J. Birks, Nadine Taube

Bibliographic record

VenueJournal of Hydrology Regional Studies · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsAlberta Environment and Protected AreasUniversity of Calgary
FundersAlberta Innovates
KeywordsStreamflowFlood mythStructural basinDrainage basinClimatologyGeographyHydrology (agriculture)GeologyPhysical geographyGeomorphologyCartographyArchaeology

Abstract

fetched live from OpenAlex

Study region The Sheep River basin on the Canadian Rockies’ Eastern Slopes of the Rocky Mountains, whose upper basins are unregulated and undeveloped. Study focus We investigated streamflow generation, hydroclimatic changes, and flood-generating mechanisms using parsimonious statistical methods and over 50 years of hydroclimate data at multiple spatial (sub-basin and entire basin) and temporal (annual, seasonal, monthly, and daily) scales. New hydrological insights for the region The upper mountainous basin generated ∼95 % of open-water streamflow, with ∼66 % from the upper-south basin, where rain, snowmelt, and the streamflow coefficient were higher. Annual and open-water precipitation declined in the lower basin, but overwinter precipitation slightly increased basin-wide. Overwinter snowpack loss increased in the lower basin, and snowpack loss seasonality weakened. Air temperature increased across all basins. Despite these climatic changes, streamflow remained unchanged, likely due to groundwater’s buffering effect. Open-water streamflow was primarily driven by rainfall, with additional rapid and slow snowmelt contributions. Overwinter streamflow was predominantly sustained by groundwater, but early snowmelt also contributed. Finally, extreme floods were triggered by heavy precipitation, although high antecedent basin wetness conditions influenced all floods. These findings highlight (i) the importance of mountainous basins in streamflow generation, (ii) the key role of groundwater on streamflow, and (iii) the need to consider complex and diverse hydrologic processes for water supply and flood management in the Sheep River basin under climate change.

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)0.001
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 score0.205
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.029
GPT teacher head0.239
Teacher spread0.209 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

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