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Record W4392167504 · doi:10.18280/i2m.230103

Comparative Assessment of Water Distribution in Constant Versus Variable Rate Irrigation Systems

2024· article· en· W4392167504 on OpenAlexvenueno aff
Zeena M. Alomari, Thair Jabbar Mizhir Alfatlawi

Bibliographic record

VenueInstrumentation Mesure Métrologie · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsnot available
Fundersnot available
KeywordsVariable (mathematics)IrrigationConstant (computer programming)Environmental scienceMathematicsStatisticsEconometricsComputer scienceMathematical analysisBiologyAgronomy

Abstract

fetched live from OpenAlex

This research explores the effectiveness of a cutting-edge smart irrigation sprinkler system, which boasts an adjustable water distribution feature.Utilizing a technique known as nozzle-pulsing combined with a variable-speed control mechanism, the system is capable of varying its water discharge rates.The evaluation encompassed measuring flow rates for both the system as a whole and its individual nozzles, as well as assessing travel speed and the uniformity and precision in water delivery.Performance metrics such as CU, DUlq, CV, MAE, MBE, and NRMSE were employed to determine the irrigation system's distribution uniformity and application accuracy.Field testing was conducted in the months of August and September 2023, under varying wind conditions with careful timing to reduce evaporative losses.The prevailing weather conditions were characterized by an absence of rainfall, with ambient temperatures ranging from 25 to 38C and relative humidity spanning 9 to 35%.Results revealed that the system adeptly modulated irrigation rates between 0 to 25 mm and altered travel speeds from 0 to 3 m/min.The implementation of pulsing to deliver variable volumes of water exerted a negligible effect on the nozzle flow rates, evidenced by an average application error below 6%.The smart sprinkler system achieved an average CU of 89.7% versus 83.8%, an average DUlq of 87.0% versus 76.8%, and an average NRMSE of 19.33% versus 25.84%, paralleling the performance of traditional systems.The study concluded that the described Variable Rate Irrigation (VRI) system is capable of matching the precision and consistency of Constant Rate Irrigation (CRI) systems.The water distribution's consistency and precision were found to be statistically unaffected by the sprinkler cycling rate, cycle duration, or system movement speed (P > 0.05).This opens the door to more accurate and consistent irrigation scheduling for agricultural applications using a novel lateral-move irrigation system endowed with VRI technology, which is vital for water-efficient irrigation practices.This finding underscores the potential of variable-rate sprinkler irrigation as a tool to enhance water management strategies.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.186

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 head0.052
GPT teacher head0.322
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

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 designBench or experimental
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

Citations0
Published2024
Admission routes1
Has abstractyes

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