Investigating Hydrochemical Groundwater Processes in an Inland   Agricultural Area with Limited Data: A Clustering Approach

doi:10.3390/w9090723

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	Investigating Hydrochemical Groundwater Processes in an Inland Agricultural Area with Limited Data: A Clustering Approach
	Wu, Xin ; Zheng, Yi ; Zhang, Juan ; Wu, Bin ; Wang, Sai ; Tian, Yong ; Li, Jinguo ; Meng, Xue
刊名	WATER
	2017
关键词	Gaussian mixture model fuzzy clustering hydrochemical processes groundwater Heihe River Basin regionalization HEIHE RIVER-BASIN MULTIVARIATE STATISTICAL-ANALYSIS SURFACE-WATER NORTHWEST CHINA DISCRIMINANT-ANALYSIS VARIABLE SELECTION SEMIARID REGIONS GEOCHEMICAL DATA MIXTURE-MODELS CHEMISTRY
DOI	10.3390/w9090723
英文摘要	Groundwater chemistry data are normally scarce in remote inland areas. Effective statistical approaches are highly desired to extract important information about hydrochemical processes from the limited data. This study applied a clustering approach based on the Gaussian Mixture Model (GMM) to a hydrochemical dataset of groundwater collected in the middle Heihe River Basin (HRB) of northwestern China. Independent hydrological data were introduced to examine whether the clustering results led to an appropriate interpretation on the hydrochemical processes. The main findings include the following. First, in the middle HRB, although groundwater chemistry reflects primarily a natural salinization process, there are evidence for significant anthropogenic influence such as irrigation and fertilization. Second, the regional hydrological cycle, particularly surface water-groundwater interaction, has a profound and spatially variable impact on groundwater chemistry. Third, the interaction between the regional agricultural development and the groundwater quality is complicated. Overall, this study demonstrates that the GMM clustering can effectively analyze hydrochemical datasets and that these clustering results can provide insights into hydrochemical processes, even with a limited number of observations. The clustering approach introduced in this study represents a cost-effective way to investigate groundwater chemistry in remote inland areas where groundwater monitoring is difficult and costly.; National Natural Science Foundation of China [41622111, 91647201, 41501024]; Shenzhen Science and Technology Innovation Commission [JCYJ20160530190411804]; Southern University of Science and Technology [G01296001]; SCI(E); ARTICLE; 9; 9
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/471030]
专题	工学院
推荐引用方式 GB/T 7714	Wu, Xin,Zheng, Yi,Zhang, Juan,et al. Investigating Hydrochemical Groundwater Processes in an Inland Agricultural Area with Limited Data: A Clustering Approach[J]. WATER,2017.
APA	Wu, Xin.,Zheng, Yi.,Zhang, Juan.,Wu, Bin.,Wang, Sai.,...&Meng, Xue.(2017).Investigating Hydrochemical Groundwater Processes in an Inland Agricultural Area with Limited Data: A Clustering Approach.WATER.
MLA	Wu, Xin,et al."Investigating Hydrochemical Groundwater Processes in an Inland Agricultural Area with Limited Data: A Clustering Approach".WATER (2017).