Spatial interpolation of improved groundwater recharge estimates on coarse textured soils
Bibliographic record
Abstract
Groundwater recharge estimation is of fundamental significance to meet the agricultural water requirements, optimize water budget management, and further the sustainable development of water resources, particularly on coarse textured soil due to their rapid drainage behavior. The objectives of the study were to evaluate the feasibility and robustness of groundwater recharge estimation using one-dimensional physically based modelling coupled with weather stations and to interpolate the point estimates of recharge to a regional scale.Since the modelling results from different study areas coincided well with other studies, this method is feasible and robust to produce reliable point estimates of recharge universally. Four methods of recharge interpolation were applied in the second study area and were cross-validated by means of true percent error between the simulated and predicted recharge.The best prediction (7.8% true percent error) was obtained by ordinary kriging. Therefore, the methods of using physically based vadose zone modelling and kriging to estimate both points and regional recharge on coarse textured soil are feasible and extendable.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".