Evidence map›Paper›PMID 39297165›Full record

ArticleiScience2024

Urban meteorological drought comprehensive index based on a composite fuzzy matter element-moment estimation weighting model.

Xiangyang Zhang, Zening Wu, Huiliang Wang, Chentao He, Fengyi Zhang, Yihong Zhou

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2024. 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

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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

6 authors.

Xiangyang ZhangSchool of Water Conservancy and Transportation, Zhengzhou University, Henan 450001, China.
Zening WuSchool of Water Conservancy and Transportation, Zhengzhou University, Henan 450001, China.
Huiliang WangSchool of Water Conservancy and Transportation, Zhengzhou University, Henan 450001, China.
Chentao HeSchool of Water Conservancy and Transportation, Zhengzhou University, Henan 450001, China.
Fengyi ZhangSchool of Water Conservancy and Transportation, Zhengzhou University, Henan 450001, China.
Yihong ZhouSchool of Water Conservancy and Transportation, Zhengzhou University, Henan 450001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to rapid urbanization and climate change, cities face hidden drought risks. A single drought index may inadequately reflect urban meteorological drought. The indicator weight combination method does not fully consider index correlation and weight. This study constructed an urban meteorological drought evaluation index system and developed the Composite Fuzzy Matter Element Meteorological drought Comprehensive Index (CFEMCI) by combining the moment estimation weighting model. Analyzing Zhengzhou City from 2000 to 2019, CFEMCI effectively captured meteorological drought events, with a probability of detection (POD) > 0.78, critical success index (CSI) > 0.70, false alarm rate (FAR) < 0.13 and failure ratio (FR) < 0.22. Most meteorological droughts were classified as Grade I (no drought), with 26% being light and moderate (Grades II-III). Droughts mainly occurred in spring, and the summer drought showed a more significantly aggravating trend. This index provides reliable urban drought monitoring and supports disaster prevention and mitigation efforts.

Indexed as

Atmospheric scienceGeographyGlobal changeMeteorology

Identifiers

PMID39297165
PMCPMC11408020

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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.