Improved Parameter Estimation Techniques for Soil Storage Capacity
Bibliographic record
Abstract
The capacity of surface soil layers to store infiltrated water is a critical factor when simulating runoff response in some natural or developing watersheds.Often, the underlying assumption that is made in hydrologic analyses is that the unsaturated zone is deep enough for unsaturated infiltration to occur throughout the event.However, in some areas this assumption is not valid, particularly for larger storm events.When the soil storage capacity in the unsaturated zone is exceeded, infiltration capacity is reduced or eliminated since capacity can only be regenerated by groundwater flow out of the surficial aquifer or by evapotranspiration (ET).These rates of groundwater flow or ET are often substantially smaller than infiltration rates.Current methods for estimating soil storage capacities are typically based on curve numbers, which use general soil and land use characteristics and most often do not make use of important published soil survey data.This chapter presents a physically based method for estimating the soil storage capacity for specific soil types using data that are readily available in GIS format Gregory, M. and B. Cunningham.2004."Improved Parameter Estimation Techniques for Soil Storage Capacity."
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".