Bio-physical effects on infiltration, channel roughness and discharge: a comparative study involving ephemeral and perennial streams
Bibliographic record
Abstract
Infiltration and channel roughness, two major factors that govern stream discharge were studied between ephemeral streams (ES) and similar-sized perennial streams (PS) for two ephemeral flow conditions: with surface flow (wet season) and with ceased flow (dry season). The highest infiltration was observed at the low flow areas around the thalweg of ES in the dry season. Also, the infiltration in the high flow areas close to the channel margin was higher in ES than PS in the wet season but was similar in the dry season. Similar infiltration rates in ES and PS were rather unexpected and was attributed to the vegetation mat formed by air-dried litter because of the rapid decrease in sediment moisture. In high flow areas of both stream types in the wet season, negative and positive correlations were observed for infiltration with biomass and sediment organic content, respectively. Also, in a few cases sediment moisture showed a positive correlation with infiltration. ES were two to three times rougher than PS and standing crop biomass and/or litter content increased stream roughness and decreased with herb diversity. Impact of vegetation parameters on roughness was more prominent in PS, whereas mean particle size had equally strong importance on roughness for both streams other than perennials in the dry season. Modelled (via HEC-HMS) and observed discharges had a better agreement for PS. The field observations, analytical solutions as well as hydrological modelling revealed ES to have a lower unit discharge than PS.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".