The effect of soil electrical conductivity on moisture determination using time-domain reflectometry in sandy soil
Bibliographic record
Abstract
A series of laboratory experiments was conducted, in order to systematically explore the effect of soil electrical conductivity on soil moisture determination using time domain reflectometry (TDR). A Moisture Point MP-917 soil moisture instrument (E.S.I. Environmental Sensors Inc., Victoria, BC, Canada) was used to measure propagation time (time delay) of a step function along a probe imbedded in fine sand with different moisture and salinity. The volumetric soil water content was independently determined using a balance. With the help of the diode-switching technique, MP-917 could detect the reflection from the end of the probe as the electrical conductivity of saturated soil extract (ECe) increased to 15.29 dS m−1. However, the relationship between volumetric soil water content and propagation time expressed as T/Tair (the ratio of propagation time in soil to that in air over the same distance) deviated from a linear relationship as the conductivity exceeded 3.72 dS m−1. At the same water content, the time delay in a saline soil was longer than that in a non-saline soil. This leads to an over-estimation of volumetric soil water content when the linear calibration was applied. A logarithmic relationship between volumetric soil water content and T/Tair has been developed and this relation includes soil electrical conductivity as a parameter. With this new calibration, it is possible to precisely determine the volumetric water content of highly saline soil using TDR. Key words: Time domain reflectometry, time delay, bulk electrical conductivity (σ), volumetric soil water content (θ), relative permittivity or dielectric constant (εr), propagation velocity Vp
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".