A new model to analyse the impact of woody riparian vegetation on the geotechnical stability of riverbanks
Bibliographic record
Abstract
Abstract We present a geotechnical stability analysis for the planar failure of riverbanks, which incorporates the effects of root reinforcement and surcharge for mature stands of woody riparian vegetation. The analysis relies on a new method of representing the root distribution in the soil, which evaluates the effects of the vegetation's position on the bank. The model is used in a series of sensitivity analyses performed for a wide range of bank morphological (bank slope and height) and sedimentological (bank cohesion and friction angle) conditions, enabling discrimination of the types of bank environment for which vegetation has an effect on bank stability. The results indicate that woody vegetation elements have a maximal impact on bank stability when they are located at the ends of the incipient failure plane (i.e. at the bank toe or at the intersection of the failure plane with the floodplain) and that vegetation has a greater effect on net bank stability when it is growing on low, shallow, banks comprised of weakly cohesive sediments. However, the magnitude of these effects is limited, with vegetation typically inducing changes (relative to non‐vegetated banks) in simulated factors of safety of less than 5%. If correct, this suggests that the well documented effects of vegetation on channel morphology must be related to alternative process mechanisms (such as the interaction of vegetation with river flows) rather than the mechanical effects of vegetation on bank failure, except in special cases where the equivalent non‐vegetated bank has a highly marginal stability status. Copyright © 2007 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".