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Record W2031845209 · doi:10.4141/s05-113

Potential impacts of climate change on water availability for crops in the Okanagan Basin, British Columbia

2006· article· en· W2031845209 on OpenAlexaffvenueabout
D. Neilsen, C. A. S. Smith, Grace C. Frank, W. Koch, Younes Alila, Wendy Merritt, William Taylor, Mark Barton, Jonah Hall, Stewart Cohen

Bibliographic record

VenueCanadian Journal of Soil Science · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of British ColumbiaAgriculture and Agri-Food Canada
Fundersnot available
KeywordsEnvironmental scienceClimate changeEvapotranspirationPrecipitationGrowing seasonHadCM3Hydrology (agriculture)TranspirationCropAgronomyGeographyEcologyGeneral Circulation ModelBiologyGCM transcription factorsMeteorologyGeology

Abstract

fetched live from OpenAlex

Crop water demand in the Okanagan Basin was determined for 1961 to 1990, 2010 to 2039, 2040 to 2069, and 2070 to 2099. Daily station temperature data were spatially interpolated to a 1 × 1 km grid and adjusted for elevation. Daily precipitation data were estimated across four climatic regions. Output from three global climate models (GCM), CGCM2, CSIROMk2 and HadCM3 was used to create future daily climate. Daily potential evapo-transpiration (grass reference) was estimated from an empirical relationship between Bellani- plate atmometer readings, temperature and extra-terrestrial solar radiation, and then modified by crop coefficients for all crops except pasture. Depending on GCM, projected water demand increased by 12–20% (2010 to 2039), 24–38% (2040 to 2069) and 40–61% (2070 to 2099). Possible elevated CO 2 effects on stomatal conductance, which may reduce water demand, were not accounted for. Comparisons with modeled Okanagan Lake inflows indicated that, on average, high water demand and low supply scenarios coincided. In one sub-basin, supply and demand thresholds were exceeded 1 yr in 6 (HadCM3) in the 2050s and at least 1 yr in 4 for all GCMs by the 2080s, and existing water supply infrastructure may be inadequate. Crop growing seasons were defined empirically from growing degree days or threshold temperatures. The growing season lengthened up to 30–35% leading to higher demand in fall and shortages due to low stream flows. Key words: Evapotranspiration, growing degree days, growing season, GIS, PRISM

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 score0.448
Threshold uncertainty score0.519

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 studies0.0000.001
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 head0.006
GPT teacher head0.184
Teacher spread0.177 · 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

Citations45
Published2006
Admission routes3
Has abstractyes

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