A Review of Regional and National Meteorological Networks offering soil moisture sensors and a review of the analytical methodology
Bibliographic record
Abstract
Soil moisture is a significant factor in Earth’s hydrological cycles that influences weather, drought, climate, and water resources on land and in water bodies. However, throughout most of the 20th century, soil moisture received less attention and was not included in many hydrological studies. In the 1978, J. W. Deardorff with the United States’ National Center for Atmospheric Research started to demonstrate the relationship between soil moisture and meteorologic conditions. Just two years later in 1980, G. C. Topp at the University of Toronto developed the Topp Equation - the first empirical calibration for soil moisture using time domain reflectometry (TDR). Additionally, that same year, M. T. van Genuchten published the van Genuchten Equation, which established a numerical relationship between soil moisture an unsaturated hydrologic head. Starting in the 1990s, the United States Department of Agriculture began using impedance-based soil moisture sensor technology to equip SNOTEL sites for water shed scale water supply forecasts. Since then, numerous large-scale regional meteorological networks incorporate soil moisture sensors, often referred to as ‘mesonets’, have emerged worldwide. Soil water dynamics is complex often not well understood. Analytical methods using electromagnetic principles rely on the behavior and distribution electromagnetic energy in soil, making the operational theory of commercial sensors unclear at times. Soil moisture exhibits significant variabilities in space and time, as well as being influenced by hydrological and mineralogical properties of the soil. These factors give rise to several misconceptions about soil moisture monitoring. This presentation discusses the growing importance of soil moisture as a critical parameter of the Earth’s hydrological cycle. This discussion also focuses on the objective and goals of North American soil moisture monitoring networks. Furthermore, the availability and emerging electromagnetic sensor technologies are reviewed. Lastly, calibration and validation soil sensors are also examined.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".