Subsurface flow velocities in a hillslope with lateral preferential flow
Bibliographic record
Abstract
Our understanding of hillslope subsurface flow relies on assumptions about how storm characteristics affect the hillslope runoff response. Experiments in hillslopes dominated by preferential flow features often show that runoff is dynamic and is affected by antecedent conditions, rainfall conditions, and position of the slope. We applied tracers to a hillslope under natural and steady state flow boundary conditions to determine the relationship between lateral tracer velocities and various hillslope lengths and storm indicators. Tracer velocities were similar to the fastest velocities measured in other similar experiments. The velocities were dependent on the boundary conditions and slope length, and the subsurface flow velocity was most closely related to the 1‐h rainfall intensity. Unlike some studies, there was little correlation between our measured flow velocities and storm volume or antecedent conditions. We attributed this to the hillslope characteristics and the relatively consistent wet antecedent conditions during the experiments. This experiment showed that the connectivity of the hillslope preferential flow network is an important factor governing the average subsurface flow velocity.
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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 | 0.001 | 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 | 0.001 |
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; 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".