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Record W1601029173 · doi:10.5539/jas.v7n6p50

Crop Evapotranspiration (ET) Estimation Models: A Review and Discussion of the Applicability and Limitations of ET Methods

2015· review· en· W1601029173 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.

venuePublished in a venue whose home country is Canada.
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

VenueJournal of Agricultural Science · 2015
Typereview
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
FundersNational Institute of Food and AgricultureColorado State UniversityU.S. Department of Agriculture
KeywordsEvapotranspirationCrop coefficientEstimationPlant canopyCanopyCropField (mathematics)Variable (mathematics)Empirical modellingAgricultural engineeringMathematicsEnvironmental scienceComputer scienceGeographyForestryEngineeringEcologySimulation

Abstract

fetched live from OpenAlex

This is a review paper on existing methodologies to calculate crop evapotranspiration (ETc). We have attempted to present all the important ET estimation procedures to date starting from the simple empirical Blaney Criddle method to the complex Shuttleworth model. The common approach to calculate ETc is to estimate a reference crop ET rate (ETref) using weather variables from nearby weather station, and multiplying it by an appropriate crop coefficient (Kc). Recently, there have been attempts to calculate actual crop ET (ETa) directly without using Kc. The latter method is still in the developmental phase. This study reviews the existing literature on ET estimation and identifies research needs in the current methods and technology. The extension of the Shuttleworth model for hourly time step and the validity of the Irmak and Mutibwaa model at field level for various crops would be a good milestone for the one step ET estimation. Furthermore, there are indications that the development of a new variable canopy surface resistance (rc) model, which can be applicable for different crops at different climatic conditions, would be a good contribution in this field.

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)0.003
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 score0.982
Threshold uncertainty score0.173

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.086
GPT teacher head0.356
Teacher spread0.270 · 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