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Record W4378651184 · doi:10.1002/ird.2840

Potential of implementing irrigation in rainfed agriculture in Quebec: A review of climate change‐induced challenges and adaptation strategies

2023· review· en· W4378651184 on OpenAlex

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueIrrigation and Drainage · 2023
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsClimate changeAgricultureIrrigationRainfed agricultureSustainabilityEnvironmental scienceWater resourcesGrowing seasonGeographyWater resource managementAdaptation (eye)Agricultural productivityAgroforestryAgronomyEcology

Abstract

fetched live from OpenAlex

Abstract Leading to growing‐season water stress, eastern Canada's evolving climate has disrupted the region's rainfed farming systems. Accordingly, this review was conducted to assess the status of irrigation, climate‐induced challenges and opportunities and the impact of adaptation strategies on economic returns and the environment in Quebec's agricultural regions. While irrigation is limited mainly to high‐value crops, controlled drainage with sub‐irrigation (CDSI) has been implemented at a limited number of field sites. Given the greater rainfall variability and rising number of growing‐season heatwave events anticipated, previous studies have mainly focused on developing climate change adaptation practices. The present study identified two research gaps: (i) a lack of analyses of drought frequency and its effect on root zone soil moisture, crop ET, crop phenology and agricultural production at a regional scale under historical and future climates and (ii) a lack of regional‐scale studies addressing climate change adaptation options, including supplementary irrigation, and their potential effects on economic return and water resources under a changing climate. Additional studies must address these gaps for the development of climate change adaptation practices to secure food demand and water sustainability.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.113
GPT teacher head0.326
Teacher spread0.214 · 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