Evidence map›Paper›PMID 36554287›Full record

ArticleInternational journal of environmental research and public health2022

Urban Flood Risk Assessment Based on Dynamic Population Distribution and Fuzzy Comprehensive Evaluation.

Hao Chen, Zongxue Xu, Yang Liu, Yixuan Huang, Fang Yang

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
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

2 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 3 institutions in 1 country.

Hao ChenCollege of Water Sciences, Beijing Normal University, Beijing 100875, China.
Zongxue XuCollege of Water Sciences, Beijing Normal University, Beijing 100875, China.
Yang LiuCollege of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100875, China.
Yixuan HuangCollege of Water Sciences, Beijing Normal University, Beijing 100875, China.
Fang YangThe Pear River Hydraulic Research Institute, Pearl River Water Resources Commission, Guangzhou 510000, China.
Beijing Normal University · CNChina University of Mining and Technology · CNPearl River Hydraulic Research Institute · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Floods are one of the most common natural disasters that can cause considerable economic damage and loss of life in many regions of the world. Urban flood risk assessment is important for urban flood control, disaster reduction, and risk management. In this study, a novel approach for assessing urban flood risk was proposed based on the dynamic population distribution, improved entropy weight method, fuzzy comprehensive evaluation method, and the principle of maximum membership, and the spatial distribution of flood risk in four different sessions or daily time segments (TS1-TS4) in the northern part of the Shenzhen River Basin (China) was assessed using geographic information system technology. Results indicated that risk levels varied with population movement. The areas of highest risk were largest in TS1 and TS3, accounting for 7.03% and 7.07% of the total area, respectively. The areas of higher risk were largest in TS2 and TS4, accounting for 4.54% and 4.64% of the total area, respectively. The findings of this study could provide a theoretical basis for assessing urban flood risk management measures in Shenzhen (and even throughout China), and a scientific basis for development of disaster prevention and reduction strategies by flood control departments.

Indexed as

DisastersFloodsChinaDemographyRisk AssessmentRisk Managementdynamic populationfuzzy comprehensive evaluationimproved entropy weightprinciple of maximum membershipurban flood risk assessment

Identifiers

PMID36554287
PMCPMC9778856
OpenAlexW4310803288

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.