Evidence map›Paper›PMID 40414900›Full record

ArticleNature communications2025

Exploring how economic level drives urban flood risk.

Jie Fan, Baoyin Liu, Tianjie Lei, Yong Sun, Yunjia Ma, Rui Guo, Dong Chen, Kan Zhou, Sisi Li, Xiang Gao

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Jie Fan *Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China. fanj@igsnrr.ac.cn.ORCID http://orcid.org/0000-0001-6070-1675
Baoyin Liu *Institutes of Science and Development, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0003-3370-7646
Tianjie LeiInstitute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing, China.
Yong SunSchool of Public Administration, Guangzhou University, Guangzhou, China.
Yunjia MaSchool of Geography and Tourism, Qufu Normal University, Rizhao, China.
Rui GuoInstitutes of Science and Development, Chinese Academy of Sciences, Beijing, China.
Dong ChenInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Kan ZhouInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0002-8241-2521
Sisi LiInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Xiang GaoInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 42230510National Natural Science Foundation of China (National Science Foundation of China) 72394403
6 · The paper itself

Abstract

In recent years, measures proposed to address urban flooding caused by extreme rainfall often demand substantial investment, restricting their broad implementation. This study quantitatively assessed the inundation situations of 138 capital cities under both normal and extreme rainfall conditions. Using machine learning techniques, we found that grey infrastructure-closely commensurate with a city's economic development-dominates flood reduction during normal rainfall events. However, during extreme precipitation, as rainfall intensity rises, the marginal effectiveness of grey infrastructure declines markedly. In contrast, green infrastructure and topography-less commensurate with economic development-play increasingly critical roles in mitigating urban flooding. These findings suggest that economic development has a limited impact on urban flooding during extreme rainfall events. Rationally utilizing topography and enhancing green spaces provides a cost-effective nature-based solution, which is particularly important for urban planning in low- and middle-income countries undergoing rapid urbanization.

Identifiers

PMID40414900
PMCPMC12104414

What OpenQuestion holds

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Registered trials

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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.