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Record W4392577629 · doi:10.5194/egusphere-egu24-12002

Ground-penetrating radar can ascertain the influence of biochar on soil wetting

2024· preprint· en· W4392577629 on OpenAlex
Lakshman Galagedara, Sashini Pathirana, Manokararajah Krishnapillai

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBiocharWettingGround-penetrating radarEnvironmental scienceRemote sensingRadarSoil scienceGeologyComputer scienceMaterials scienceEngineeringWaste managementComposite materialTelecommunications

Abstract

fetched live from OpenAlex

Incorporating biochar (BC) as a soil amendment has become a prominent agricultural management practice since it has many advantages. Most soils amended with BC have shown improvements in soil physical and hydraulic properties, including bulk density, soil porosity, water retention, field capacity, and permanent wilting point. Ground-penetrating radar (GPR) is a non-destructive geophysical technique that is used to study soil properties and state variables. Yet, there is a lack of research studying the influence of amendments on soil hydrology using GPR.  Therefore, this study was aimed at evaluating the ability of GPR in assessing the effect of BC on soil hydrology. The experiment was conducted under laboratory conditions using plastic containers measuring 28.6 cm in length, 20 cm in width and 16.4 cm in height. These plastic containers were filled up to 14 cm height with three different treatments (T); T1 (100% Sand+0% BC), T2 (99.5% Sand+0.5% BC), and T3 (98% Sand+2% BC) on a mass basis. Soil moisture sensors were placed horizontally at 2, 7, and 12 cm depths while packing the containers. The GPR data were collected using 1000 MHz center frequency transducers by keeping transmitter and receiver on opposite sides of the container (zero-offset profiling survey) at 20 cm antenna offset. Data were collected before, during, and after the wetting process over a one-hour timeframe. A 204 mL of water was applied every 4 min (13 times) to increase the soil water content at each time by 2% from initial water content. The GPR data were processed, and radargrams were prepared to observe the wetting front movement. Soil water contents were estimated utilizing the travel time of the GPR direct wave through the treatment media. GPR travel time and moisture sensor data were compared in each treatment. The GPR estimated soil water contents correlated well with moisture sensor data (correlation coefficient (r)>0.93) in all three treatments. Results have shown that the travel time of GPR direct wave responded differently for three treatments. The rate of change in GPR estimated soil water content over time exhibits an increase with the percentage of BC (T1

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)0.000
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 score0.388
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.015
GPT teacher head0.266
Teacher spread0.251 · 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

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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