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Record W1969983379 · doi:10.4296/cwrj3502115

Assessing On-Farm Irrigation Water Use Efficiency in Southern Ontario

2010· article· en· W1969983379 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.

fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Water Resources Journal / Revue canadienne des ressources hydriques · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaGovernment of Ontario
KeywordsEnvironmental scienceIrrigationWater conservationIrrigation schedulingDeficit irrigationIrrigation managementLow-flow irrigation systemsIrrigation statisticsFarm waterWater resource managementWater contentWater useAgricultureWater resourcesGrowing seasonAgricultural engineeringSoil waterAgronomyGeographyEngineeringSoil science

Abstract

fetched live from OpenAlex

Abstract For high-value horticultural crop production in southern Ontario, irrigation is an essential ingredient in overcoming insufficient rainfall and achieving stabilized crop production. In a context where competition for limited water resources intensifies due to the expansion of the agricultural sector, increasing urban development and tourism, and potential climate change impacts, conserving water through efficient irrigation has become a key solution in addressing this growing challenge. The implementation of advanced soil water monitoring technologies and water budgeting methods for improved irrigation scheduling is examined with regard to water conservation and thus as a means to cope with competing demands for limited water supplies. During the 2007 growing season, soil moisture was measured using two sensors at four field sites (comprising a total of six irrigated zones as two sites include two different irrigation/production systems) in southern Ontario. Irrigation water consumption was measured by flow meters at three sites. In addition, a survey was administered to collect information on growers' current irrigation scheduling practices. On-farm irrigation performance was assessed by comparing calculated tomato, green bell pepper, strawberry and peach water requirements (using the water budget method) with growers' estimates of irrigation water use and with soil moisture measurements taken during the growing season. Four out of the six irrigated zones were excessively irrigated, while in one zone, water was insufficiently applied. The crop water requirements were met efficiently exclusively in one zone where tomatoes were grown. Overall, the results of this research show that by implementing advanced soil moisture monitoring technologies, growers can increase precision in water application and reduce the uncertainty in their current irrigation scheduling practices. Dans le sud de l'Ontario, l'irrigation est essentielle à la production de cultures horticoles à haute valeur ajoutée afin de compenser l'insuffisance de précipitations et stabiliser la production des cultures. Dans un contexte où la compétition pour les ressources limitées en eau s'intensifie en réponse à l'expansion du secteur agricole, à la croissance du développement urbain et du tourisme, ainsi qu'aux impacts potentiels des changements climatiques, conserver l'eau grâce à des techniques d'irrigation économes est devenue une solution incontournable pour affronter ce défi grandissant. L'implémentation de technologies avancées de surveillance de la teneur en eau dans le sol et d'un bilan hydrique, pour améliorer les pratiques d'irrigation programmée, est examinée afin de conserver l'eau et ainsi mieux faire face aux demandes concurrentielles pour les ressources limitées en eau. Au cours de la saison de croissance de 2007, l'humidité du sol a été mesurée avec deux sondes pour quatre sites (comprenant un total de 6 zones irriguées) situés dans le sud de l'Ontario. Les quantités d'eau utilisées pour irriguer étaient mesurées par des compteurs de débit installés sur trois sites. De plus, les producteurs ont répondus à un questionnaire ayant pour mandat de recueillir de l'information concernant leurs pratiques actuelles d'irrigation programmée. La performance d'irrigation à l'échelle de la ferme a ensuite été évaluée en comparant les besoins en eau de tomates, poivrons verts, fraises et pêches (calculés à l'aide d'un bilan hydrique) avec la quantité d'eau d'irrigation utilisée telle qu'estimée par les producteurs, ainsi qu'avec les mesures d'humidité du sol prises au cours de la saison de croissance. Dans cinq des six zones irriguées, la quantité d'eau appliquée était soit excessive, soit insuffisante. Une application d'eau d'irrigation excessive a été détectée dans quatre des zones alors qu'une application insuffisante a été observée dans une des zones. Les besoins en eau des cultures ont été comblés efficacement dans une seule zone. Somme toute, les résultats de cette étude montrent qu'en implémentant les technologies avancées de surveillance d'humidité dans le sol, les producteurs pourraient généralement économiser de l'eau en réduisant l'incertitude actuellement imbriquée dans leurs pratiques d'irrigation programmée.

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 categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.951
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.212
Teacher spread0.185 · 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