Field Water Balance Closure with Actively Heated Fiber-Optics and Point-Based Soil Water Sensors
Bibliographic record
Abstract
While traditional soil water sensors measure soil water content (SWC) at point scale, the actively heated fiber-optics (AHFO) sensor measures the SWC at field scale. This study compared the performance of a distributed (e.g., AHFO) and a point-based sensor on closing the field water balance and estimating the evapotranspiration (ET). Both sensors failed to close the water balance and produced larger errors in estimated ET (ETε), particularly for longer time periods with >60 mm change in soil water storage (ΔSWS), and this was attributed to a lack of SWC measurements from deeper layers (>0.24 m). Performance of the two sensors was different when only the periods of ˂60 mm ΔSWS were considered; significantly lower residual of the water balance (Re) and ETε of the distributed sensor showed that it could capture the small-scale spatial variability of SWC that the point-based sensor missed during wet (70–104 mm SWS) periods of ˂60 mm ΔSWS. Overall, this study showed the potential of the distributed sensor to provide a more accurate value of SWS at field scale and to reduce the errors in water balance for shorter wet periods. It is suggested to include SWC measurements from deeper layers to better evaluate the performance of the distributed sensor, especially for longer time periods of >60 mm ΔSWS, in future studies.
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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) | 0.001 | 0.003 |
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; both teacher heads agree on what is shown here.
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".