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Record W4283212128 · doi:10.1111/jac.12614

Improving the estimation of soil water evaporation based on days after wetting

2022· article· en· W4283212128 on OpenAlexfundno aff
Élvis da Silva Alves, Lineu Neiva Rodrigues, Fernanda Laurinda Valadares Ferreira

Bibliographic record

VenueJournal of Agronomy and Crop Science · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Apoio à Pesquisa do Distrito FederalCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorEmpresa Brasileira de Pesquisa AgropecuáriaUniversity of the Fraser Valley
KeywordsLysimeterEvaporationWettingEnvironmental scienceSoil sciencePan evaporationSoil waterHydrology (agriculture)Materials scienceGeotechnical engineeringGeologyComposite materialMeteorologyGeography

Abstract

fetched live from OpenAlex

Abstract Soil evaporation constitutes a major pathway of water loss in agriculture. Understanding its dynamics in the face of drying and soil cover is fundamental to improve both simulation models and the sustainability of production systems. Thus, the objective of this study was to estimate soil evaporation as a function of drying and percentage of soil cover. Three experiments were carried out in three different periods. In each of the periods, in parallel and in an adjacent area, an experiment was carried out to evaluate the influence of weighing micro‐lysimeter (ML) height on the estimation of direct soil evaporation. The experiments were installed with a completely randomized design. For the experiments that measured evaporation as a function of cover, the treatments consisted of six different percentages of cover of the internal area of the ML (0%, 10%, 25%, 50%, 75% and 100%), with four replicates, using artificial plants to cover the soil. The experiments that estimated evaporation as a function of ML height were conducted with eight repetitions and three different ML heights (100, 200 and 300 mm). It was observed that the accumulated evaporation up to 25 days after wetting was 52% and 53% lower in micro‐lysimeters with 100 mm height, compared to those with 200 and 300 mm height, respectively, for all experiments. The new model developed to calculate soil evaporation as a function of the days after wetting and percentage of soil cover showed excellent performance (NSE > 0.95).

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.267

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 studies0.0000.000
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 head0.004
GPT teacher head0.182
Teacher spread0.178 · 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 designSimulation or modeling
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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

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