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Record W2006419818 · doi:10.2166/wst.2006.293

Influence of natural vs. anthropogenic stresses on water resource sustainability: a case study

2006· article· en· W2006419818 on OpenAlexaboutno aff
Jessica Fennell, A. Zawadzki, C. Cadman

Bibliographic record

VenueWater Science & Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsStructural basinEnvironmental scienceHydrology (agriculture)Water resourcesGroundwaterDeforestation (computer science)Drainage basinAgricultureLand useClimate changeWater balanceSurface waterWater resource managementGeographyGeologyOceanographyEnvironmental engineeringEcology

Abstract

fetched live from OpenAlex

Climate change has been identified as a major influence on basin water balances. However, land use and water use practices have also been identified as players. This case study was completed to better understand a changing water balance affecting a major basin in Alberta. The Beaver River basin is located in east central Alberta. Much of the basin has been developed for agricultural use; however, a number of heavy oil operations also exist. Both sectors use surface and groundwater. Evidence exists that the basin hydrology has changed since the mid-1970s. Coincidently, it was at this time that much of the land was cleared for agricultural development and commercial-scale oil development began. Oil industry use of water was suspected as the main cause for the changes observed. To investigate this further, data from regional hydrometric and meteorological stations were assessed along with water well hydrographs and historical satellite images. A significant correlation was found between basin responses and a climate phenomenon known as the Pacific decadal oscillation. Although the correlation between the Pacific decadal oscillation and basin hydrology appeared strong, deforestation for agricultural development also seemed to have an effect. Use of the local water resources was found to be of minor significance.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.197
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.232
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2006
Admission routes1
Has abstractyes

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