干旱区生态环境知识资源中心(Arid): Providing predictive models for quality parameters of groundwater resources in arid areas of central Iran: A case study of kashan plain

Arid

DOI	10.1016/j.heliyon.2024.e31493
	Providing predictive models for quality parameters of groundwater resources in arid areas of central Iran: A case study of kashan plain
	Zarajabad, Aysan Morovvati; Hadi, Mahdi; Nodehi, Ramin Nabizadeh; Moradi, Mahsa; Ghalhari, Mohammad Rezvani; Zeraatkar, Abbas; Mahvi, Amir Hossein
通讯作者	Mahvi, AH
来源期刊	HELIYON
EISSN	2405-8440
出版年	2024
卷号	10 期号:11
英文摘要	Groundwater pollution can occur due to both anthropogenic and natural causes, leading to a decline in water quality and posing a threat to human health and the environment. The pollution of ground water resources with chemical pollutants is often considered. To manage water resources sustainably, ensuring their quality and quantity is crucial. Yet, testing groundwater can be expensive and time-consuming. So, using modeling to predict the chemical parameters of groundwater resources is considered to be an efficient and economical method. In this study, we examined three models to predict groundwater quality in dry regions by using R programming language. The random forest (RF) outperformed the other models in developing predictive models for water quality. Also, the multiple linear regression (MLR) model demonstrated strong performance, particularly in predicting total hardness (TH) in Aran Va Bidgol groundwater resources. The decision tree (DT) model did well but had lower performance than the RF model in predicting quality parameters. This approach can be efficacious in the field of effective management and protection of groundwater resources and enables the assessment of risks related to water resources.
英文关键词	Chemical parameters Groundwater Modeling Water quality
类型	Article
语种	英语
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:001246474800001
WOS关键词	ARTIFICIAL NEURAL-NETWORK ; WATER ; RIVER ; CITY
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/404032
推荐引用方式 GB/T 7714	Zarajabad, Aysan Morovvati,Hadi, Mahdi,Nodehi, Ramin Nabizadeh,et al. Providing predictive models for quality parameters of groundwater resources in arid areas of central Iran: A case study of kashan plain[J],2024,10(11).
APA	Zarajabad, Aysan Morovvati.,Hadi, Mahdi.,Nodehi, Ramin Nabizadeh.,Moradi, Mahsa.,Ghalhari, Mohammad Rezvani.,...&Mahvi, Amir Hossein.(2024).Providing predictive models for quality parameters of groundwater resources in arid areas of central Iran: A case study of kashan plain.HELIYON,10(11).
MLA	Zarajabad, Aysan Morovvati,et al."Providing predictive models for quality parameters of groundwater resources in arid areas of central Iran: A case study of kashan plain".HELIYON 10.11(2024).