Evidence map›Paper›PMID 41125715›Full record

ArticleScientific reports2025

Spatial-temporal variations of river water quality under human-induced land use changes in large river basins.

Xiaojing Zhang, Bing Yu, Zhuohang Xin, Ming Cong, Chi Zhang

Abstract read
In one paragraph

Article in Scientific reports, 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

5 authors.

Xiaojing ZhangSchool of Infrastructure Engineering, Dalian University of Technology, Dalian, 116024, China.
Bing YuSchool of Infrastructure Engineering, Dalian University of Technology, Dalian, 116024, China. yubing@dlut.edu.cn.
Zhuohang XinSchool of Infrastructure Engineering, Dalian University of Technology, Dalian, 116024, China.
Ming CongSchool of Infrastructure Engineering, Dalian University of Technology, Dalian, 116024, China.
Chi ZhangSchool of Infrastructure Engineering, Dalian University of Technology, Dalian, 116024, China.

Funding

the National Key Research and Development Program of China 2023YFC3208402the National Natural Science Foundation of China 52422904
6 · The paper itself

Abstract

Land use patterns and anthropogenic activities exert diverse impacts on river water quality and ecosystem health across spatial and temporal scales. Under ongoing pressures from human activities and climate change, it is urgently needed to understand the pollution mechanisms and associated ecological risks in surface waters through cross-basin assessments that incorporate a broad set of water quality parameters. This study investigated the spatial-temporal variations of 22 water quality parameters, including physico-biochemical indicators, nutrients, and heavy metals, at 39 sampling sites across the Daliao River (DLR), Shuangtaizi River (STR), and Naoli River (NLR). Field observations were conducted in September 2019, December 2020, and June 2020, covering the wet, dry, and agricultural seasons to assess the influencing mechanisms of natural factors and human activities on river water quality and human health. Principal Component Analysis revealed a notable seasonal variation in water quality components for DLR and STR, which indicated substantially high concentrations of TN, NO

Indexed as

Environmental MonitoringRiversWater Pollutants, ChemicalWater QualityAgricultureChinaClimate ChangeEcosystemHuman ActivitiesHumansMetals, HeavySeasonsSpatio-Temporal AnalysisMetals, HeavyWater Pollutants, ChemicalHuman healthLand use patternsSeasonal variationWater quality

Identifiers

PMID41125715
PMCPMC12546616

What OpenQuestion holds

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LicenceCC BY
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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.