Analyzing spatial and temporal variability of soil water content
Bibliographic record
Abstract
During the last two decades geoestatistical methods have been intensively used for in-depth descriptions of spatial variability. The objective of this study was to assess the spatial and temporal variability of soil water content. The measurements were taken with a TDR equipment to a 20 cm depth, in a nearly flat 1.2 ha field at the Central Experimental Farm of the Agriculture Canada, Ottawa. The soil classified as a Rideau soil series, is a clay loam soil. A square grid with 10 m spacing was laid out, resulting in 164 sampling points at which two TDR rods were installed to measure the water content down to 20 cm depth. Measurements were taken on 33 dates during the frost free months in 1987, 1988 and 1989. The spatial variability was analyzed examining the scaled semivariograms, the statistical parameters and the parameters of the models fit to individual semivariograms as a function of time. It was concluded that spatial dependence decreases as the soil gets drier and that results from one year connect almost continuously to other years. The topography and structure of topsoil horizon was the primary cause for the repeating spatial pattern of soil water content in successive samplings. The places where the mean value occurred in the field were more stable in time when there was spatial dependence. As the soil gets dryer the temporal stability of the spatial distribution tends to disappear due to the hydraulic conductivity controlling the water evaporation over the field
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".