Evidence map›Paper›PMID 30002358›Full record

ReviewSensors (Basel, Switzerland)2018

Real-Time Early Warning System Design for Pluvial Flash Floods-A Review.

Melisa Acosta-Coll, Francisco Ballester-Merelo, Marcos Martinez-Peiró, Emiro De la Hoz-Franco

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
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

4 authors.

Melisa Acosta-CollDepartment of Electronic Engineering, Universitat Politècnica de València, 46022 València, Spain. macosta10@cuc.edu.co.ORCID 0000-0002-5433-0414
Francisco Ballester-MereloDepartment of Electronic Engineering, Universitat Politècnica de València, 46022 València, Spain. fballest@eln.upv.es.
Marcos Martinez-PeiróDepartment of Electronic Engineering, Universitat Politècnica de València, 46022 València, Spain. mpeiro@eln.upv.es.
Emiro De la Hoz-FrancoDepartment of Computer Sciences and Electronic, Universidad de la Costa, Barranquilla 080020, Colombia. edelahoz@cuc.edu.co.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pluvial flash floods in urban areas are becoming increasingly frequent due to climate change and human actions, negatively impacting the life, work, production and infrastructure of a population. Pluvial flooding occurs when intense rainfall overflows the limits of urban drainage and water accumulation causes hazardous flash floods. Although flash floods are hard to predict given their rapid formation, Early Warning Systems (EWS) are used to minimize casualties. We performed a systematic review to define the basic structure of an EWS for rain flash floods. The structure of the review is as follows: first, Section 2 describes the most important factors that affect the intensity of pluvial flash floods during rainfall events. Section 3 defines the key elements and actors involved in an effective EWS. Section 4 reviews different EWS architectures for pluvial flash floods implemented worldwide. It was identified that the reviewed projects did not follow guidelines to design early warning systems, neglecting important aspects that must be taken into account in their implementation. Therefore, this manuscript proposes a basic structure for an effective EWS for pluvial flash floods that guarantees the forecasting process and alerts dissemination during rainfall events.

Indexed as

early warning systemflash floodsflood risk assessmentpluvial floodingreal-timeurban drainage

Identifiers

PMID30002358
PMCPMC6068664

What OpenQuestion holds

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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.