Performance assessment of soil moisture sensors under controlled conditions in laboratory setting and recommendations for field deployment
Bibliographic record
Abstract
A three-dimensional intermediate test system with the ability to control boundary conditions and soil moisture variations was developed. The setup had the advantage of being able to accurately characterize the heterogeneity through packing with test soils with well-defined properties and to control the boundary and initial conditions that are not possible in field settings. A distributed soil moisture sensor system was tested under controlled conditions in the test facility before field deployment. The developed 3-D tank has dimensions of L=4.87 m, W= 2.44 m packed to a depth of 0.40 m. The tank was packed with a heterogeneous configuration using five uniform silica sand with the effective sieve numbers #70, #16, #8, #12/30, and #20/30 (Accusands Unimin Corp Ottawa, MN), respectively. Soil moisture variations were monitored using 30 soil moisture sensors (ECH2O EC-5 and 5TE, TEROS12). The testing focused on observing and recording soil moisture patterns and the performance of the sensors under various imbibition and drainage scenarios expected in the field. The sensors were able to successfully capture the complex spatial and temporal variations of the soil moisture in the tank. Each sensor was individually calibrated for each type of the test sands used to provide unique fitting parameters relating to the sensor’s measured voltage to known water content. During the experiments, the head at one of the boundaries was kept constant, resulting in full saturation at this boundary that was captured by the sensors. Based on the time-series data, the variations in the specific properties of the sand in the packing led to different saturations. The varying hydraulic properties of the packed sand affected the water flow and soil moisture dynamics that were captured by the sensors. Even under such highly controlled test conditions in laboratory settings, heterogeneities resulting from packing imperfections and compaction introduced some uncertainties in the measurements. These observations suggest the importance of incorporating any available information on the natural heterogeneity when designing sensor deployment strategies in the field.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".