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Record W1967994593 · doi:10.1080/02508060208686997

A GIS Interface Method Based on Reference Evapotranspiration and Crop Coefficients for the Determination of Irrigation Requirements

2002· article· en· W1967994593 on OpenAlexaff
Ioannis K. Tsanis, Sherif Naoum, Steven J. Boyle

Bibliographic record

VenueWater International · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEvapotranspirationCrop coefficientIrrigationEnvironmental scienceHydrology (agriculture)Penman–Monteith equationAgricultural engineeringWater resource managementAgronomyEcologyEngineering

Abstract

fetched live from OpenAlex

A GIS approach was developed to utilize spatially distributed and temporally averaged meteorological data and crop distributions and their coefficients in order to estimate irrigation requirements. The irrigation requirements were estimated as the difference between crop evapotranspiration and effective rainfall. Crop evapotranspiration was evaluated as the product of reference evapotranspiration and the crop coefficient. Reference evapotranspiration was calculated using the FAO Penman-Monteith method. Monthly effective rainfall was estimated from total monthly rainfall according to the method developed by the USDA Soil Conservation Service. In order to illustrate the applicability of this approach, a case study for the country of Greece was used. Based on the share of water use in agriculture for irrigation purposes, results obtained from this study indicate an irrigation efficiency of approximately 66 percent for the year 1991. Taking that number into account, the irrigation requirements for the year 2020 are estimated at 8,350 Mm3.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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 head0.038
GPT teacher head0.288
Teacher spread0.249 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations6
Published2002
Admission routes1
Has abstractyes

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