Effective Communication of Coastal Flood Warnings: Challenges and Recommendations
Bibliographic record
Abstract
With the increasing risk of coastal flooding facing coastal communities due to climate change, coastal flood warnings (CFWs) are expected to play a critical role in the protection of people and property to ensure communities’ sustainable development. However, as destructive coastal flooding hazards have caused considerable damage in recent years, the effectiveness of coastal flooding warnings could be questioned considering their objective of disaster risk reduction. Here, we deliver a review investigation of the current CFWs in the USA and Canada based on their setup and dissemination, and a case study of two representative coastal flooding events. Through this review, we found that collaboration between multi-level administration regarding CFW mechanisms has the potential to strengthen these mechanisms, improving their efficacy. We also found that CFWs presented in the media often lacked consideration of public acceptance and practicability in their reports, which may have affected the performance of these CFWs. Meanwhile, the technological limitations and uncertain public acceptance may also reduce the CFWs’ effectiveness in application. Accordingly, the media should further consider the understandability of CFW-related reports. Moreover, emergency information channels should be set in both traditional media and social media for accessible use by residents with different customs. Lastly, starting from the normalized prevention of coastal flood disaster, a consensus of crisis awareness should be built with which the social aspects of the defense against coastal flooding can be established for future environmental sustainability.
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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 | 0.001 |
| 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".