Recent advances in groundwater pollution research using machine learning from 2000 to 2023: a bibliometric analysis DOI
Xuan Li, Guohua Liang, Bin He

и другие.

Environmental Research, Год журнала: 2024, Номер 267, С. 120683 - 120683

Опубликована: Дек. 20, 2024

Язык: Английский

Using unsupervised machine learning models to drive groundwater chemistry and associated health risks in Indo-Bangla Sundarban region DOI

Jannatun Nahar Jannat,

Abu Reza Md. Towfiqul Islam, Md. Yousuf Mia

и другие.

Chemosphere, Год журнала: 2024, Номер 351, С. 141217 - 141217

Опубликована: Янв. 20, 2024

Язык: Английский

Процитировано

21

Groundwater hydrochemistry, source identification and health assessment based on self-organizing map in an intensive mining area in Shanxi, China DOI
Yajie Shang, Changchang Fu, Wenjing Zhang

и другие.

Environmental Research, Год журнала: 2024, Номер 252, С. 118934 - 118934

Опубликована: Апрель 21, 2024

Язык: Английский

Процитировано

14

Prediction of sulfate concentrations in groundwater in areas with complex hydrogeological conditions based on machine learning DOI

Yushan Tian,

Quanli Liu,

Yao Ji

и другие.

The Science of The Total Environment, Год журнала: 2024, Номер 923, С. 171312 - 171312

Опубликована: Фев. 28, 2024

Язык: Английский

Процитировано

10

Spatial variability, source identification, and partitioning of groundwater constituents in a typical lakeside plain on Yungui Plateau DOI

Wenxu Hu,

Yong Xiao, Liwei Wang

и другие.

Process Safety and Environmental Protection, Год журнала: 2024, Номер unknown

Опубликована: Окт. 1, 2024

Язык: Английский

Процитировано

10

Distribution of Groundwater Hydrochemistry and Quality Assessment in Hutuo River Drinking Water Source Area of Shijiazhuang (North China Plain) DOI Open Access
Ziting Yuan,

Yantao Jian,

Zhi Chen

и другие.

Water, Год журнала: 2024, Номер 16(1), С. 175 - 175

Опубликована: Янв. 3, 2024

The Hutuo River Drinking Water Source Area is an important water source of Shijiazhuang (North China Plain). Knowing the characteristics groundwater chemistry/quality essential for protection and management resources. However, there are few studies focused on chemistry evolution over drinking area. In this study, total 160 samples were collected in November 2021, spatial distribution related controlling factors analyzed using hydrological multivariate analysis. entropy-weighted quality index (EWQI) was introduced to assess quality. results show that hydrogeochemical types Ca-HCO3 (78.1%), mixed Ca-Mg-Cl (20%), Ca-Cl (1.9%) Graphical binary diagrams indicate hydrochemistry mainly controlled by water–rock interaction (i.e., rock weathering, mineral dissolution, ion exchange). Five principal components separated from component analysis represent rock–water agricultural return, redox environment, geogenic sources, utilization fertilizer, weathering aluminum silicates, dissolution carbonates, respectively. More than 70% not recommended irrigation due presence high salt content groundwater. EWQI assessment demonstrates good. outcomes study significant understanding geochemical status Area, helping policymakers protect manage

Язык: Английский

Процитировано

7

Optimized groundwater quality evaluation using unsupervised machine learning, game theory and Monte-Carlo simulation DOI
Yuting Yan,

Yunhui Zhang,

Shiming Yang

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 371, С. 122902 - 122902

Опубликована: Ноя. 11, 2024

Язык: Английский

Процитировано

6

Under the Strong Influence of Human Activities: The Patterns and Controlling Factors of River Water Chemistry Changes—A Case Study of the Lower Yellow River DOI Open Access

Chaobin Ren,

Lu Liu

Water, Год журнала: 2024, Номер 16(13), С. 1886 - 1886

Опубликована: Июль 1, 2024

This study provides an in-depth analysis of the hydrochemical characteristics and their controlling factors in lower reaches Yellow River. Through water quality sampling over two hydrological periods within a year, combined with methods machine learning techniques, reveals joint impact natural human activities on spatiotemporal variations constituents. The findings indicate that River exhibits weak alkalinity (the pH is between 7 8), primary type being HCO3·SO4—Ca·Na·Mg. temporal variation constituents mainly influenced by rainfall, where nitrate levels are higher during flood season due to flushing effect whereas other show opposite pattern dilution rainfall. spatial River’s hydrochemistry primarily controlled combination Using Gibbs diagram analysis, it identified rock weathering main source ionic constituents, while agricultural fertilization, industrial emissions, domestic wastewater discharge have significant impacts Compared rivers worldwide, concentration relatively high, especially sulfate, which closely related geological basin intense middle reaches. Principal component for dry dissolution activities, followed wastewater; season, wastewater. research provide theoretical support resource management protection

Язык: Английский

Процитировано

5

Ecological and health risk assessment of heavy metals in agricultural soils from northern China DOI
Jiangyun Liu,

Qiwen Zheng,

Shuwei Pei

и другие.

Environmental Monitoring and Assessment, Год журнала: 2023, Номер 196(1)

Опубликована: Дек. 29, 2023

Язык: Английский

Процитировано

12

Identifying the hydrochemical features, driving factors, and associated human health risks of high-fluoride groundwater in a typical Yellow River floodplain, North China DOI
Jing Chen, Wang Shou, Shuxuan Zhang

и другие.

Environmental Geochemistry and Health, Год журнала: 2023, Номер 45(11), С. 8709 - 8733

Опубликована: Сен. 14, 2023

Язык: Английский

Процитировано

10

Photo-assisted arsenic removal by MgFeAl-layered double hydroxide: Understanding the activation of Al3+ by Fe3+ incorporation DOI
Qian Li, Guihao Liu, Zhaohui Wu

и другие.

Chemical Engineering Journal, Год журнала: 2024, Номер 496, С. 154029 - 154029

Опубликована: Июль 15, 2024

Язык: Английский

Процитировано

4