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Record W2241942020 · doi:10.5539/mas.v10n1p139

Study on Movement of Water and Salt through Soil Column and Utilization of Hydrus-1D Program to Simulate Five Scenarios of Crop Production in Salt Affected Paddy Soil

2015· article· en· W2241942020 on OpenAlexvenueno aff
Panom Chaiyasit, Piya Duangpatra, Visoot Verasan, Varawoot Vudhivanich

Bibliographic record

VenueModern Applied Science · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRice Cultivation and Yield Improvement
Canadian institutionsnot available
FundersKasetsart University
KeywordsHydraulic conductivitySoil waterBulk densityChemistrySoil scienceHydrology (agriculture)Environmental scienceGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

An experiment was conducted on the purpose to study movement of water and salt through soil column. Salt-affected paddy soil was assessed for its relevant transport parameters consisting of the hydraulic and the solute transport parameters. The hydraulic parameters included soil hydraulic conductivity (Ks) and the van Genuchten’s parameters (θs, θr, α, and n). In this experiment the solute transport parameters was referred to the coefficient of Langmuir’s isotherm which consisted of kd and η. Experience showed that hydraulic parameters were sensitive to changes of soil bulk density (ρb). Therefore pedotransfer functions describing the relations between these parameters with ρb were established. Straight line functions were found for θs and n, exponential functions were found for α and Ks, and logarithmic function was found for θr. Packing the soil in the physical column inevitably caused horizontal differentiation of different ρb. Bulk density of each layer was estimated by analysis of water flow through soil column at steady-state. Then ρb of each layer was calculated from the relation Ks (ρb). After the ρb was known the van Genuchten’s parameters were calculated from the pedotransfer functions. A physical column of 4 inches diameter and 50 cm length was constructed. Sodium chloride solution EC 6 dS/m was fed on soil surface during the process of salinization and the feeding solution was changed to fresh water during the process of desalinization. Breakthrough solution was analyzed for Na concentration and the breakthrough curves were constructed. The relevant parameters as well as initial and boundary conditions were fed into Hydrus-1D on the purpose to simulate the breakthrough curves. Statistical comparison results using t-test and RMSE suggested that Hydrus-1D could be used successfully to monitor transport of water and salt through soil column. Five scenarios concerning water and solute transport through soil profile under rice and mung bean cropping were simulated using Hydrus-1D. Simulation results suggested that continuous flooding was the most efficient way to leach soluble salts down to ground water. Wet/dry irrigation scheme for rice production could drain salts only when rice crop was in the first period of growth where crop water uptake was small. During later stages of growth concentration profile of Na remained almost unchange indicating negligible downward movement of salts. Leaving the soil to dry naturally during the dry season caused upward accumulation of salt to the degree smaller than cultivating mung bean since water content and hence the diffusion coefficient of the soil were higher and more favorable for upward salt diffusion than in the former case. Inserting the capillary rise hindering soil layer underneath mung bean root zone was found to retard upward diffusion of salt to the degree comparable to leaving the soil to dry naturally.

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)0.000
metaresearch head score (Gemma)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.057
GPT teacher head0.288
Teacher spread0.231 · 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
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

Citations1
Published2015
Admission routes1
Has abstractyes

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