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<Article>
<Journal>
				<PublisherName>University of Tehran</PublisherName>
				<JournalTitle>Journal of Natural Environment</JournalTitle>
				<Issn>2008-7764</Issn>
				<Volume>63</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2010</Year>
					<Month>12</Month>
					<Day>22</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Spatial estimation of groundwater quality factors using geostatistical methods (case study: Golpayegan plain)</ArticleTitle>
<VernacularTitle>Spatial estimation of groundwater quality factors using geostatistical methods (case study: Golpayegan plain)</VernacularTitle>
			<FirstPage>347</FirstPage>
			<LastPage>357</LastPage>
			<ELocationID EIdType="pii">29191</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mohammadreza</FirstName>
					<LastName>Hajihashemi Jazi</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Majid</FirstName>
					<LastName>Atashgahi</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Amirhossein</FirstName>
					<LastName>Hamidian</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>1970</Year>
					<Month>01</Month>
					<Day>01</Day>
				</PubDate>
			</History>
		<Abstract>Nowadays, much attention has been paid on using geostatistical methods for estimation of spatial parameters, either using the variables of these parameters (kriging) or auxiliary variables (cokriging), in water and soil sciences. The quality of ground water for agriculture is very important; however, it is expensive and time consuming to measure parameters such as SAR, Na, Ca, TH, TDS and EC. Therefore, it is essential to explore methods for estimation of these parameters based on those which can be easily measured. In this paper, information on individual samples taken from 84 wells of Golpayegan plain was investigated using, kriging and cokriging geostatistical methods. Variograms were produced using the normalized data. In order to select the appropriate model fitting the experimental variograms, lower values of RSS and stronger spatial structures were used. Outputs of the cokriging and kriging for estimation of SAR, Na, Ca, TH, TDS and EC using RMSE were evaluated. The results showed no preference for using cokriging over kriging method. However, because of lower RMSE value of cokriging, this method was used for the preparation of underground water zoning maps using GIS.</Abstract>
			<OtherAbstract Language="FA">Nowadays, much attention has been paid on using geostatistical methods for estimation of spatial parameters, either using the variables of these parameters (kriging) or auxiliary variables (cokriging), in water and soil sciences. The quality of ground water for agriculture is very important; however, it is expensive and time consuming to measure parameters such as SAR, Na, Ca, TH, TDS and EC. Therefore, it is essential to explore methods for estimation of these parameters based on those which can be easily measured. In this paper, information on individual samples taken from 84 wells of Golpayegan plain was investigated using, kriging and cokriging geostatistical methods. Variograms were produced using the normalized data. In order to select the appropriate model fitting the experimental variograms, lower values of RSS and stronger spatial structures were used. Outputs of the cokriging and kriging for estimation of SAR, Na, Ca, TH, TDS and EC using RMSE were evaluated. The results showed no preference for using cokriging over kriging method. However, because of lower RMSE value of cokriging, this method was used for the preparation of underground water zoning maps using GIS.</OtherAbstract>
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			<Object Type="keyword">
			<Param Name="value">Cokriging</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Golpayegan</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">groundwater quality factor</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Kriging</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">RMSE</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jne.ut.ac.ir/article_29191_50769eac2bd3dfdf4f98ce3a8d1c5fbe.pdf</ArchiveCopySource>
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