Evidence map›Paper›PMID 42040663›Full record

ReviewCambridge prisms. Coastal futures2026

A review of early warning systems for storm-induced coastal flooding and erosion on wave-dominated open coasts.

Oscar Ferreira

Abstract readReview
In one paragraph

Review in Cambridge prisms. Coastal futures, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Oscar FerreiraFCT, CIMA, Universidade do Algarve, Portugal.ORCID https://orcid.org/0000-0001-9975-0036

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early warning systems for coastal erosion and flooding are currently primarily designed for local applications, offering high-resolution, site-specific predictions. Only a few early warning systems (EWS) are used at large regional or national scales. There is also a lack of standardised indicators and thresholds, which vary widely across systems and hinder cross-regional applicability. While current EWS perform well in binary hazard detection (Yes/No hazard; 80-95% accuracy), they struggle to accurately classify intermediate hazard levels. A lack of comprehensive field datasets has impeded rigorous validation for most systems, with many assessments relying on qualitative observations. Improving the reliability of the EWS requires improving their validation against field data obtained during storms and regular updating of the topobathymetric data to include the actual pre-storm morphology. Currently, most EWS rely on outdated or synthetic morphological inputs, which increases prediction uncertainty. The computational constraints of physics-based models may prevent warnings from being issued in time and have led to the adoption of surrogate approaches that depend on robust training datasets. Furthermore, most systems focus solely on hazard detection, paying limited attention to the risk to assets or populations. Future development must prioritise stakeholder engagement and the co-design of systems that incorporate both hazard and risk assessments, in order to improve their usefulness and facilitate decision-making by end users.

Indexed as

coastal hazardsrisk reductionstorm impactswarning levels

Identifiers

PMID42040663
PMCPMC13107362

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.