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Record W1957384487 · doi:10.1155/2015/861805

Groundwater—Surface Water Interactions in a Mountain-to-Coast Watershed: Effects of Climate Change and Human Stressors

2015· article· en· W1957384487 on OpenAlexafffundabout
S. B. Foster, D. M. Allen

Bibliographic record

VenueAdvances in Meteorology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsSimon Fraser University
FundersMinistry of Forests, Lands and Natural Resource Operations
KeywordsWatershedGroundwaterSnowpackHydrology (agriculture)Groundwater rechargeSnowmeltSurface waterPrecipitationEnvironmental scienceClimate changeSpring (device)EstuarySubstrate (aquarium)GeologyGeographySnowOceanographyGeomorphologyAquiferMeteorology

Abstract

fetched live from OpenAlex

Watersheds located within a mountain to coast physiographic setting have been described as having a highly interconnected surface water and groundwater environment. The quantification of groundwater—surface water interactions at the watershed scale requires upscaling. This study uses MIKE SHE, a coupled numerical model, to explore the seasonally and spatially dynamic nature of these interactions in the Cowichan Watershed on Vancouver Island, British Columbia, Canada. The calibrated model simulates a transition of the Cowichan River from mostly gaining within the valley, to losing stream near the coast where groundwater extraction is focused. Losing and gaining sections correlate with geological substrate. Recharge across the watershed accounts for 17% of precipitation. Climate change is projected to lessen snowpack accumulation in the high alpine and alter timing of snowmelt, resulting in higher spring and winter river discharge and lower summer flows.

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 score0.156
Threshold uncertainty score0.626

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 science0.0000.001
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 head0.018
GPT teacher head0.284
Teacher spread0.267 · 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

Citations26
Published2015
Admission routes3
Has abstractyes

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