A conceptual model of preferential flow systems in forested hillslopes: evidence of self‐organization
Bibliographic record
Abstract
Abstract Preferential flow paths are known to be important conduits of subsurface stormflow in forest hillslopes. Earlier research on preferential flow paths focused on vertical transport; however, lateral transport is also evident in steep forested slopes underlain by bedrock or till. Macropores consisting of decayed and live roots, subsurface erosion, surface bedrock fractures, and animal burrows form the basis of a ‘backbone’ for lateral preferential flow in such sites. Evidence from field studies in Japan indicates that although individual macropore segments are generally <0·5 m in length, they have a tendency to self‐organize into larger preferential flow systems as sites become wetter. Staining tests show clear evidence of interconnected macropore flow segments, including: flow within decayed root channels and subsurface erosion cavities; flow in small depressions of the bedrock substrate; fracture flow in weathered bedrock; exchange between macropores and mesopores; and flow at the organic horizon–mineral soil interface and in buried pockets of organic material and loose soil. Here we develop a three‐dimensional model for preferential flow systems based on distributed attributes of macropores and potential connecting nodes (e.g. zones of loose soil and buried organic matter). We postulate that the spatially variable and non‐linear preferential flow response observed at our Japan field site, as well as at other sites, is attributed to discrete segments of macropores connecting at various nodes within the regolith. Each node is activated by local soil water conditions and is influenced strongly by soil depth, permeability, pore size, organic matter distribution, surface and substrate topography, and possibly momentum dissipation. This study represents the first attempt to characterize the spatially distributed nature of preferential flow paths at the hillslope scale and presents strong evidence that these networks exhibit complex system behaviour. Copyright © 2001 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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".