干旱区生态环境知识资源中心(Arid): Groundwater quality assessment by multi-model comparison: a comprehensive study during dry and wet periods in semi-arid regions

Arid

DOI	10.1007/s11356-023-25937-2
	Groundwater quality assessment by multi-model comparison: a comprehensive study during dry and wet periods in semi-arid regions
	Wang, Zihan; Wang, Yong
通讯作者	Wang, Y
来源期刊	ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
ISSN	0944-1344
EISSN	1614-7499
出版年	2023
卷号	30 期号:18 页码:51571-51594
英文摘要	With the impact of human engineering activities, groundwater pollution has seriously threatened the health of human life. Accurate water quality assessment is the basis of controlling groundwater pollution and improving groundwater management, especially in specific regions. A typical semi-arid city in Fuxin Province of China is taken as an example. We use remote sensing and GIS to compile four environmental factors, such as rainfall, temperature, LULC, and NDVI, to analyze and screen the correlation of indicators. The differences among the four algorithms were compared by using hyperparameters and model interpretability, including random forest (RF), support vector machine support vector machine (SVM), decision tree (DT), and K-nearest neighbor (KNN). The groundwater quality of the city during the dry and wet periods was comprehensively evaluated. The results show that the RF model has higher integrated precision (MSE = 0.11, 0.035; RMSE = 0.19,0.188; R-2 = 0.829,0.811; ROC = 0.98, 0.98). The quality of shallow groundwater is poor in general, 29%, 38%, 33% of the groundwater quality in low-water period is III, IV, V water. Thirty-three percent and 67% of the groundwater quality in the high-water period were IV and V water. The proportion of poor water quality in high-water period was higher than that in low-water period, which was consistent with the actual investigation. This study provides a kind of machine learning method for the semi-arid area, which cannot only promote the sustainable development of groundwater in this area, but also provide reference for the management policy of related departments.
英文关键词	Groundwater quality Machine learning Dry season Wet season Correlation analysis Water resource management
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000936964300001
WOS关键词	DRINKING-WATER QUALITY ; LAND-USE ; INDEX ; CITY ; DISTRICTS ; SUPPORT ; SYSTEM ; LEVEL ; RIVER
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/396261
推荐引用方式 GB/T 7714	Wang, Zihan,Wang, Yong. Groundwater quality assessment by multi-model comparison: a comprehensive study during dry and wet periods in semi-arid regions[J],2023,30(18):51571-51594.
APA	Wang, Zihan,&Wang, Yong.(2023).Groundwater quality assessment by multi-model comparison: a comprehensive study during dry and wet periods in semi-arid regions.ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,30(18),51571-51594.
MLA	Wang, Zihan,et al."Groundwater quality assessment by multi-model comparison: a comprehensive study during dry and wet periods in semi-arid regions".ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 30.18(2023):51571-51594.