Implementation of geotechnical and vegetation modules inTELEMAC to simulatethe dynamics of vegetated alluvial floodplains
Bibliographic record
Abstract
Amongst the most widely used computational fluid\ndynamics models, some include a sediment transport module that\nenables the examination of river channel dynamics. However,\nmost ignore two families of processes influencing lateral erosion\nrates, and thus channel evolution mechanisms: lateral transport\nof sediment through mass wasting along river banks and valley\nwalls, and soil reinforcement created by plant roots. A few\nmodelling packages consider geotechnical processes, albeit with\nimportant limitations. Indeed, most solutions are solely\ncompatible with single-threaded channels, impose a given\ncomputational mesh structure (e.g. body-fitted coordinate\nsystem), derive lateral migration rates from hydraulic properties,\nadjust bank morphology solely based on the angle of repose of\nthe bank material, rely on non-physical assumptions to describe\ncertain processes (e.g. channel cut offs in meandering rivers), and\nexclude floodplain processes. This paper describes the\ndevelopment and testing of two modules that were recently added\nto the mathematical suite of solvers TELEMAC-MASCARET to\naddress the aforementioned limitations. The first module\n(GEOTECH) includes an algorithm that scans the computational\ndomain in an attempt to detect potentially unstable slope profiles\nacross the domain or intersecting with water-soil boundaries.\nThe module relies on a fully configurable, universal genetic\nalgorithm with tournament selection to delineate the shape of the\nsurface along which a slump block detaches itself from a river\nbank or slope by translational or rotational mechanism. Both the\nhydrostatic pressure caused by the flow and the elevation of the\nwater table are used in the Bishop’s method to quantify slope\nstability. Another algorithm computes the surface of the coarse\nfraction of the block material which is deposited at the toe of the\nslope. The second module (RIPVEG) simulates the evolution of\nfloodplain vegetation, whose properties affect the geotechnical\nstability of slopes present in the computational domain by\nimposing a surcharge and increasing soil cohesion near the soil\nsurface. Plants develop in height, weight and rooting depth at a\nrate that depends on the species and plant age. The two modules,\ncombined with the flow and sediment transport models included\nin TELEMAC, provide a holistic solution to study the dynamics\nof a broad range of alluvial river types. The model is currently\nbeing tested, calibrated and validated using datasets from\nmeandering rivers.\n
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".