Runoff–infiltration partitioning using an upscaled Green–Ampt solution
Bibliographic record
Abstract
Abstract A new set of formulae for calculating regionally averaged infiltration rates into heterogeneous soils is presented. The solutions are based upon an upscaled approximation of the explicit Green‐Ampt (GA) infiltration solution, and require specification of the spatial distribution of saturated hydraulic conductivity and/or initial soil water deficit in the sub‐basin. The resultant areal averaged infiltration formulae, which ignore the impacts of run on or spatial correlation, are easily integrated into existing distributed surface water schemes, and can also be used to calculate saturated soil surface area. The impacts of preferential flow may be investigated through the use of a bimodal conductivity distribution. The solutions are tested against Monte Carlo simulations and assessed for accuracy. Interesting results are obtained regarding the impacts of upscaling on GA infiltration, most notably that the cumulative infiltration is most impacted by low‐conductivity soils and that calibration of the standard (point‐scale) GA equation to basin‐scale hydrographs will lead to an underestimation of average system hydraulic conductivity. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".