Coastal erosion and sediment reworking caused by hurricane Irma – implications for storm impact on low‐lying tropical islands
Bibliographic record
Abstract
Abstract Hurricane Irma (September 2017) was one of the most devastating hurricanes in recent times. In January 2018, a post‐hurricane field survey was conducted on Anegada (British Virgin Islands) to report on the erosional and depositional evidence caused by Hurricane Irma's storm surge and waves. We document the type and extent of hurricane‐induced geomorphological changes, allowing for an improved risk assessment of hurricane‐related inundation on low‐lying islands and carbonate platforms. Anegada's north shore was most impacted by Hurricane Irma. The surge reached about 3.8 m above sea level and onshore flow depths ranged between 1.2 to 1.6 m. Storm wave action created 1 to 1.5 m high erosional scarps along the beaches, and the coastline locally retreated by 6 to 8 m. Onshore sand sheets reached up to 40 m inland, overlie a sharp erosive contact and have thicknesses of 7 to 35 cm along the north shore. In contrast, lobate overwash fans in the south are 2 to 10 cm thick and reach 10 to 30 m inland. Moreover, the hurricane reworked a pre‐existing coast‐parallel coral rubble ridge on the central north shore. The crest of the coral rubble ridge shifted up to 10 m inland due to the landward transport of cobbles and boulders (maximum size 0.5 m 3 ) that were part of the pre‐hurricane ridge. A re‐survey, 18 months after the event, assessed the degree of the natural coastal recovery. The sand along the northern shoreline of Anegada that was eroded during the hurricane and stored in the shallow water, acted as a nearshore source for beach reconstruction which set in only days after the event. Beach recovery peaked in February 2018, when beaches accreted within hours during a nor'easter‐like storm that transported large volumes of nearshore sand back onto the beach.
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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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".