<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>University of Guilan</PublisherName>
				<JournalTitle>Caspian Journal of Environmental Sciences</JournalTitle>
				<Issn>1735-3033</Issn>
				<Volume>13</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>12</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Application of multivariate statistics and geostatistical techniques to identify the spatial variability of heavy metals in groundwater resources</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>333</FirstPage>
			<LastPage>347</LastPage>
			<ELocationID EIdType="pii">1546</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>F.</FirstName>
					<LastName>Khanduzi</LastName>
<Affiliation>University of Zanjan</Affiliation>

</Author>
<Author>
					<FirstName>A.</FirstName>
					<LastName>Parizanganeh</LastName>
<Affiliation>University of Zanjan</Affiliation>

</Author>
<Author>
					<FirstName>A.</FirstName>
					<LastName>Zamani</LastName>
<Affiliation>University of Zanjan</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>03</Month>
					<Day>01</Day>
				</PubDate>
			</History>
		<Abstract>The performance of geostatistical and spatial interpolation techniques for estimation of spatial variability of heavy metals and water quality mapping of groundwater resources in Ramiyan district (Golestan province- Iran) were investigated. 24 spring/well water samples were collected and the concentration of heavy metals (Ni, Co, Pb, Cd and Cu) was determined using Differential Pulse Polarography. Multivariate and geostatistical methods have been applied to differentiate the influences of natural processes and human activities as to the pollution of heavy metals in groundwater across the study area. The results of the Cluster Analysis and Factor Analysis show that Ni and Co are grouped in the factor F1, whereas, Pb and Cd in F2 and Zn and Cu in F3. The probability of presence of elevated levels for the three factors was predicted by utilizing the most appropriate Variogram Model, whilst the performance of methods, was evaluated by using Mean Absolute Error, Mean Bias Error and Root Mean Square Error. The spatial structure results show that the variograms and cross-validation of the six variables can be modeled with three methods, namely,the Radial Basis Fraction, Inverse Distance Weight and Ordinary Kriging. Moreover, results illustrated that Radial Basis Fraction method was the best as it had the highest precision and lowest error. The Geographic Information System can fully display spatial patterns of heavy metal concentrations, in groundwater resources of the study area.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Groundwater resources</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Heavy metals contamination</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Geostatistical</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Multivariate statistics</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Interpolation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Spatial mapping</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://cjes.guilan.ac.ir/article_1546_7bd616fdd42367cd8e1a722547775c24.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
