Using automated soil water content measurements to estimate soil water budgets
Bibliographic record
Abstract
The distribution of precipitation into the components of a soil water budget has a profound impact on crop growth, groundwater recharge, soil erosion, and groundwater and surface water contamination levels. The main objectives of this study were to develop a new method of measuring soil water balances and to demonstrate the use of the method in examining differences between partitioning of water in conventional tillage (CT) and no-tillage (NT) management systems. Hourly precipitation, evapotranspiration, and changes in soil water storage data were collected automatically over a 3-yr period at a field site near Elora, Ontario. Runoff and interception were calculated as the difference between measured increases in soil water storage and total rainfall during each significant rain event when the soil was not frozen. Drainage was then calculated, as it was the only component of the soil water balance not measured. The amount of soil water stored in the NT system was greater than the CT system during the latter part of the study as the NT system aged. The amount of drainage calculated for a 3 -yr period was greater for CT than the NT treatment, a result that is contrary to many previous studies. The measured amount of runoff plus interception was greater in the NT versus CT treatment. Since NT is generally accepted as a means of reducing runoff, this result could be due to the enhanced amount of interception by the crop residue left on the surface of the NT treatment. Key words: Soil water balance, water content reflectometer, drainage, runoff, tillage, time series
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".