Surfzone State Estimation, with Applications to Quadcopter-Based Remote Sensing Data
Bibliographic record
Abstract
Abstract A one-dimensional variational data assimilation (1DVar) method is presented based on the depth- and time-averaged alongshore-uniform surfzone wave and current equations, for simultaneous estimation of three uncertain variables: bathymetry, incident wave boundary conditions, and bed roughness. The method is validated using twin tests and in situ field observations, and its results are shown to be comparable to those of an existing ensemble-based bathymetry inversion technique. Unlike existing techniques, the ability to simultaneously estimate boundary conditions and bed roughness along with bathymetry also means the 1DVar method can produce full state estimates without the requirement for additional supporting measurements (e.g., direct measurements of the incident waves). A proof-of-concept field application is shown using observations collected from an unmanned quadcopter sensor package that measures surfzone wave height from a fixed-beam lidar range finder, and time-averaged longshore current from particle image velocimetry of drifting surface foam.
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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 | 0.001 | 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 | 0.000 |
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".