干旱区生态环境知识资源中心(Arid): Statistical Modeling for Spatial Groundwater Potential Map Based on GIS Technique

Arid

DOI	10.3390/su13073788
	Statistical Modeling for Spatial Groundwater Potential Map Based on GIS Technique
	Azma, Aliasghar; Narreie, Esmaeil; Shojaaddini, Abouzar; Kianfar, Nima; Kiyanfar, Ramin; Alizadeh, Seyed Mehdi Seyed; Davarpanah, Afshin
通讯作者	Kianfar, N (corresponding author), KN Toosi Univ Technol, Fac Geodesy & Geomat Engn, Tehran 158754416, Iran.
来源期刊	SUSTAINABILITY
EISSN	2071-1050
出版年	2021
卷号	13 期号:7
英文摘要	In arid and semi-arid lands like Iran water is scarce, and not all the wastewater can be treated. Hence, groundwater remains the primary and the principal source of water supply for human consumption. Therefore, this study attempted to spatially assess the groundwater potential in an aquifer in a semi-arid region of Iran using geographic information systems (GIS)-based statistical modeling. To this end, 75 agricultural wells across the Marvdasht Plain were sampled, and the water samples' electrical conductivity (EC) was measured. To model the groundwater quality, multiple linear regression (MLR) and principal component regression (PCR) coupled with elven environmental parameters (soil-topographical parameters) were employed. The results showed that that soil EC (SEC) with Beta = 0.78 was selected as the most influential factor affecting groundwater EC (GEC). CaCO3 of soil samples and length-steepness (LS factor) were the second and third effective parameters. SEC with r = 0.89 and CaCO3 with r = 0.79 and LS factor with r = 0.69 were also characterized for PC1. According to performance criteria, the MLR model with R-2 = 0.94, root mean square error (RMSE) = 450 mu Scm(-1) and mean error (ME) = 125 mu Scm(-1) provided better results in predicting the GEC. The GEC map indicated that 16% of the Marvdasht groundwater was not suitable for agriculture. It was concluded that GIS, combined with statistical methods, could predict groundwater quality in the semi-arid regions.
英文关键词	carbonate aquifer digital elevation model modeling multivariate linear regression principal component regression groundwater quality assessment
类型	Article
语种	英语
开放获取类型	gold, Green Published
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000638912100001
WOS类目	Green & Sustainable Science & Technology ; Environmental Sciences ; Environmental Studies
WOS研究方向	Science & Technology - Other Topics ; Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/351830
作者单位	[Azma, Aliasghar] Beijing Univ Technol, Coll Architecture & Civil Engn, Beijing 100124, Peoples R China; [Narreie, Esmaeil] Grad Univ Adv Technol, Fac Civil & Surveying Engn, Dept Surveying Engn, Kerman 7631133131, Iran; [Shojaaddini, Abouzar] Tarbiat Modares Univ, Coll Agr, Soil Sci Dept, Tehran 14115336, Iran; [Kianfar, Nima] KN Toosi Univ Technol, Fac Geodesy & Geomat Engn, Tehran 158754416, Iran; [Kiyanfar, Ramin] Payame Noor Univ, Dept Art & Architecture, Shiraz 193954697, Iran; [Alizadeh, Seyed Mehdi Seyed] Australian Coll Kuwait, Petr Engn Dept, West Mishref 13015, Kuwait; [Davarpanah, Afshin] Aberystwyth Univ, Dept Math, Aberystwyth SY23 3FL, Dyfed, Wales
推荐引用方式 GB/T 7714	Azma, Aliasghar,Narreie, Esmaeil,Shojaaddini, Abouzar,et al. Statistical Modeling for Spatial Groundwater Potential Map Based on GIS Technique[J],2021,13(7).
APA	Azma, Aliasghar.,Narreie, Esmaeil.,Shojaaddini, Abouzar.,Kianfar, Nima.,Kiyanfar, Ramin.,...&Davarpanah, Afshin.(2021).Statistical Modeling for Spatial Groundwater Potential Map Based on GIS Technique.SUSTAINABILITY,13(7).
MLA	Azma, Aliasghar,et al."Statistical Modeling for Spatial Groundwater Potential Map Based on GIS Technique".SUSTAINABILITY 13.7(2021).