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Assessing the spatial uncertainty of mapping trace elements in cultivated fields
Many of the cultivated soils in Galicia (NW Spain) consist of grassland areas and, subsequently, cattle density is also considerable. As a result, dispersion of heavy metals into the rural environment associated with manure and slurry applications has been reported. Mapping the spatial distribution...
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Published in: | Communications in soil science and plant analysis 2005, Vol.36 (1-3), p.253-274 |
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description | Many of the cultivated soils in Galicia (NW Spain) consist of grassland areas and, subsequently, cattle density is also considerable. As a result, dispersion of heavy metals into the rural environment associated with manure and slurry applications has been reported. Mapping the spatial distribution of heavy metals in soils is important for soil management; currently, geostatistical methods are used to generate maps of fertilizer and heavy metal contents and also to assess the uncertainty of the predicted concentrations of these elements. The main objective of this study was to assess the spatial variability of trace elements in a small catchment (10.7 ha), where slurry application was intense. Moreover, the use of geostatistical tools for the description and modeling of metal distribution is illustrated. Fifty-five soil samples were digested by nitric acid in a microwave (U.S.E PA-SW-846 3051) method to assess Mn, Zn, Cu, Ni, Pb, and Cd contents by ICP/AES. The pattern of spatial distribution of total metal contents was analyzed by means of different geostatistical techniques and by the inverse distance method. When a pattern of spatial dependence was found, kriging was used to construct contour maps after semivariogram analysis. High statistical variability was observed for the metals studied. Mean Cu content was 28.5 mg kg(-1) and that of Zn was 64.7 mg kg(-1), the differences between maximum and minimum being 62.3 mg kg(-1) and 122.1 mg kg(-1) for Cu and Zn, respectively. Also, some hot spots with high levels of Cd (>13 mg kg(-1)) with respect to background values were recorded. The spatial distributions of total Zn and Cu contents were characterized using spherical semivariograms with no nugget effect. Ordinary kriging estimates were compared with results obtained by indicator kriging. Sequential simulation was also applied to analyze the spatial distribution of the metals studied. This study reveals that these methods are useful to determine spatial distribution and uncertainty of trace metal contents in cultivated fields and thus to characterize the heavy metal status at the scale studied. In contrast, EDTA- and CaCl2-extractable Zn and Cu contents did not show spatial structure at all; hence, nongeostatistical techniques were used to attempt to interpolate these metal fractions. |
doi_str_mv | 10.1081/CSS-200043078 |
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As a result, dispersion of heavy metals into the rural environment associated with manure and slurry applications has been reported. Mapping the spatial distribution of heavy metals in soils is important for soil management; currently, geostatistical methods are used to generate maps of fertilizer and heavy metal contents and also to assess the uncertainty of the predicted concentrations of these elements. The main objective of this study was to assess the spatial variability of trace elements in a small catchment (10.7 ha), where slurry application was intense. Moreover, the use of geostatistical tools for the description and modeling of metal distribution is illustrated. Fifty-five soil samples were digested by nitric acid in a microwave (U.S.E PA-SW-846 3051) method to assess Mn, Zn, Cu, Ni, Pb, and Cd contents by ICP/AES. The pattern of spatial distribution of total metal contents was analyzed by means of different geostatistical techniques and by the inverse distance method. When a pattern of spatial dependence was found, kriging was used to construct contour maps after semivariogram analysis. High statistical variability was observed for the metals studied. Mean Cu content was 28.5 mg kg(-1) and that of Zn was 64.7 mg kg(-1), the differences between maximum and minimum being 62.3 mg kg(-1) and 122.1 mg kg(-1) for Cu and Zn, respectively. Also, some hot spots with high levels of Cd (>13 mg kg(-1)) with respect to background values were recorded. The spatial distributions of total Zn and Cu contents were characterized using spherical semivariograms with no nugget effect. Ordinary kriging estimates were compared with results obtained by indicator kriging. Sequential simulation was also applied to analyze the spatial distribution of the metals studied. This study reveals that these methods are useful to determine spatial distribution and uncertainty of trace metal contents in cultivated fields and thus to characterize the heavy metal status at the scale studied. In contrast, EDTA- and CaCl2-extractable Zn and Cu contents did not show spatial structure at all; hence, nongeostatistical techniques were used to attempt to interpolate these metal fractions.</description><identifier>ISSN: 0010-3624</identifier><identifier>EISSN: 1532-2416</identifier><identifier>DOI: 10.1081/CSS-200043078</identifier><identifier>CODEN: CSOSA2</identifier><language>eng</language><publisher>Philadelphia, PA: Taylor & Francis Group</publisher><subject>agricultural soils ; Agronomy. Soil science and plant productions ; Biological and medical sciences ; cattle manure ; copper ; Fundamental and applied biological sciences. Psychology ; geostatistics ; land application ; Soil and water pollution ; Soil science ; soil surveys ; spatial distribution ; spatial variation ; statistical uncertainty ; trace elements ; zinc</subject><ispartof>Communications in soil science and plant analysis, 2005, Vol.36 (1-3), p.253-274</ispartof><rights>Copyright Taylor & Francis Group, LLC 2005</rights><rights>2005 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c340t-b31cd27e7a54ef7e605b36147e578dca89503f52159664fad59001a3c4272fc73</citedby><cites>FETCH-LOGICAL-c340t-b31cd27e7a54ef7e605b36147e578dca89503f52159664fad59001a3c4272fc73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>309,310,314,780,784,789,790,4024,4050,4051,23930,23931,25140,27923,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16724415$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Caridad-Cancela, R</creatorcontrib><creatorcontrib>Vidal Vazquez, E</creatorcontrib><creatorcontrib>Vieira, S.R</creatorcontrib><creatorcontrib>Abreu, C.A</creatorcontrib><creatorcontrib>Paz Gonzalez, A</creatorcontrib><title>Assessing the spatial uncertainty of mapping trace elements in cultivated fields</title><title>Communications in soil science and plant analysis</title><description>Many of the cultivated soils in Galicia (NW Spain) consist of grassland areas and, subsequently, cattle density is also considerable. As a result, dispersion of heavy metals into the rural environment associated with manure and slurry applications has been reported. Mapping the spatial distribution of heavy metals in soils is important for soil management; currently, geostatistical methods are used to generate maps of fertilizer and heavy metal contents and also to assess the uncertainty of the predicted concentrations of these elements. The main objective of this study was to assess the spatial variability of trace elements in a small catchment (10.7 ha), where slurry application was intense. Moreover, the use of geostatistical tools for the description and modeling of metal distribution is illustrated. Fifty-five soil samples were digested by nitric acid in a microwave (U.S.E PA-SW-846 3051) method to assess Mn, Zn, Cu, Ni, Pb, and Cd contents by ICP/AES. The pattern of spatial distribution of total metal contents was analyzed by means of different geostatistical techniques and by the inverse distance method. When a pattern of spatial dependence was found, kriging was used to construct contour maps after semivariogram analysis. High statistical variability was observed for the metals studied. Mean Cu content was 28.5 mg kg(-1) and that of Zn was 64.7 mg kg(-1), the differences between maximum and minimum being 62.3 mg kg(-1) and 122.1 mg kg(-1) for Cu and Zn, respectively. Also, some hot spots with high levels of Cd (>13 mg kg(-1)) with respect to background values were recorded. The spatial distributions of total Zn and Cu contents were characterized using spherical semivariograms with no nugget effect. Ordinary kriging estimates were compared with results obtained by indicator kriging. Sequential simulation was also applied to analyze the spatial distribution of the metals studied. This study reveals that these methods are useful to determine spatial distribution and uncertainty of trace metal contents in cultivated fields and thus to characterize the heavy metal status at the scale studied. In contrast, EDTA- and CaCl2-extractable Zn and Cu contents did not show spatial structure at all; hence, nongeostatistical techniques were used to attempt to interpolate these metal fractions.</description><subject>agricultural soils</subject><subject>Agronomy. Soil science and plant productions</subject><subject>Biological and medical sciences</subject><subject>cattle manure</subject><subject>copper</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>geostatistics</subject><subject>land application</subject><subject>Soil and water pollution</subject><subject>Soil science</subject><subject>soil surveys</subject><subject>spatial distribution</subject><subject>spatial variation</subject><subject>statistical uncertainty</subject><subject>trace elements</subject><subject>zinc</subject><issn>0010-3624</issn><issn>1532-2416</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><recordid>eNp1kMtOwzAQRS0EEqWwZI03LAPjR-xkWVW8pEogla6jqWMXozSJbBfUvycQHitWo5HOvTM6hJwzuGJQsOv5cplxAJACdHFAJiwXPOOSqUMyAWCQCcXlMTmJ8XVYSw18Qp5mMdoYfbuh6cXS2GPy2NBda2xI6Nu0p52jW-z7LySgsdQ2dmvbFKlvqdk1yb9hsjV13jZ1PCVHDptoz77nlKxub57n99ni8e5hPltkRkhI2VowU3NtNebSOm0V5GuhmNQ210VtsChzEC7nLC-Vkg7rvBx-RmEk19wZLaYkG3tN6GIM1lV98FsM-4pB9amjGnRUvzoG_nLke4wGGxewNT7-hZTmUg7GpqQYOd-6LmzxvQtNXSXcN134CYn_TlyMUYddhZswkKslByYAylJwocQHqzx7Sg</recordid><startdate>2005</startdate><enddate>2005</enddate><creator>Caridad-Cancela, R</creator><creator>Vidal Vazquez, E</creator><creator>Vieira, S.R</creator><creator>Abreu, C.A</creator><creator>Paz Gonzalez, A</creator><general>Taylor & Francis Group</general><general>Taylor & Francis</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>2005</creationdate><title>Assessing the spatial uncertainty of mapping trace elements in cultivated fields</title><author>Caridad-Cancela, R ; Vidal Vazquez, E ; Vieira, S.R ; Abreu, C.A ; Paz Gonzalez, A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c340t-b31cd27e7a54ef7e605b36147e578dca89503f52159664fad59001a3c4272fc73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>agricultural soils</topic><topic>Agronomy. Soil science and plant productions</topic><topic>Biological and medical sciences</topic><topic>cattle manure</topic><topic>copper</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>geostatistics</topic><topic>land application</topic><topic>Soil and water pollution</topic><topic>Soil science</topic><topic>soil surveys</topic><topic>spatial distribution</topic><topic>spatial variation</topic><topic>statistical uncertainty</topic><topic>trace elements</topic><topic>zinc</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Caridad-Cancela, R</creatorcontrib><creatorcontrib>Vidal Vazquez, E</creatorcontrib><creatorcontrib>Vieira, S.R</creatorcontrib><creatorcontrib>Abreu, C.A</creatorcontrib><creatorcontrib>Paz Gonzalez, A</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><jtitle>Communications in soil science and plant analysis</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Caridad-Cancela, R</au><au>Vidal Vazquez, E</au><au>Vieira, S.R</au><au>Abreu, C.A</au><au>Paz Gonzalez, A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing the spatial uncertainty of mapping trace elements in cultivated fields</atitle><jtitle>Communications in soil science and plant analysis</jtitle><date>2005</date><risdate>2005</risdate><volume>36</volume><issue>1-3</issue><spage>253</spage><epage>274</epage><pages>253-274</pages><issn>0010-3624</issn><eissn>1532-2416</eissn><coden>CSOSA2</coden><abstract>Many of the cultivated soils in Galicia (NW Spain) consist of grassland areas and, subsequently, cattle density is also considerable. As a result, dispersion of heavy metals into the rural environment associated with manure and slurry applications has been reported. Mapping the spatial distribution of heavy metals in soils is important for soil management; currently, geostatistical methods are used to generate maps of fertilizer and heavy metal contents and also to assess the uncertainty of the predicted concentrations of these elements. The main objective of this study was to assess the spatial variability of trace elements in a small catchment (10.7 ha), where slurry application was intense. Moreover, the use of geostatistical tools for the description and modeling of metal distribution is illustrated. Fifty-five soil samples were digested by nitric acid in a microwave (U.S.E PA-SW-846 3051) method to assess Mn, Zn, Cu, Ni, Pb, and Cd contents by ICP/AES. The pattern of spatial distribution of total metal contents was analyzed by means of different geostatistical techniques and by the inverse distance method. When a pattern of spatial dependence was found, kriging was used to construct contour maps after semivariogram analysis. High statistical variability was observed for the metals studied. Mean Cu content was 28.5 mg kg(-1) and that of Zn was 64.7 mg kg(-1), the differences between maximum and minimum being 62.3 mg kg(-1) and 122.1 mg kg(-1) for Cu and Zn, respectively. Also, some hot spots with high levels of Cd (>13 mg kg(-1)) with respect to background values were recorded. The spatial distributions of total Zn and Cu contents were characterized using spherical semivariograms with no nugget effect. Ordinary kriging estimates were compared with results obtained by indicator kriging. Sequential simulation was also applied to analyze the spatial distribution of the metals studied. This study reveals that these methods are useful to determine spatial distribution and uncertainty of trace metal contents in cultivated fields and thus to characterize the heavy metal status at the scale studied. In contrast, EDTA- and CaCl2-extractable Zn and Cu contents did not show spatial structure at all; hence, nongeostatistical techniques were used to attempt to interpolate these metal fractions.</abstract><cop>Philadelphia, PA</cop><pub>Taylor & Francis Group</pub><doi>10.1081/CSS-200043078</doi><tpages>22</tpages></addata></record> |
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subjects | agricultural soils Agronomy. Soil science and plant productions Biological and medical sciences cattle manure copper Fundamental and applied biological sciences. Psychology geostatistics land application Soil and water pollution Soil science soil surveys spatial distribution spatial variation statistical uncertainty trace elements zinc |
title | Assessing the spatial uncertainty of mapping trace elements in cultivated fields |
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