Assessment of spatial distribution of fallout radionuclides through geostatistics concept.
Identifieur interne : 000190 ( Ncbi/Merge ); précédent : 000189; suivant : 000191Assessment of spatial distribution of fallout radionuclides through geostatistics concept.
Auteurs : L. Mabit [Autriche] ; C. BernardSource :
- Journal of environmental radioactivity [ 0265-931X ] ; 2007.
English descriptors
- KwdEn :
- MESH :
- chemical , analysis : Cesium Radioisotopes, Radioactive Fallout, Soil Pollutants, Radioactive.
- geographic : Quebec.
- statistics & numerical data : Radiation Monitoring.
- Models, Statistical.
Abstract
After introducing geostatistics concept and its utility in environmental science and especially in Fallout Radionuclide (FRN) spatialisation, a case study for cesium-137 ((137)Cs) redistribution at the field scale using geostatistics is presented. On a Canadian agricultural field, geostatistics coupled with a Geographic Information System (GIS) was used to test three different techniques of interpolation [Ordinary Kriging (OK), Inverse Distance Weighting power one (IDW1) and two (IDW2)] to create a (137)Cs map and to establish a radioisotope budget. Following the optimization of variographic parameters, an experimental semivariogram was developed to determine the spatial dependence of (137)Cs. It was adjusted to a spherical isotropic model with a range of 30 m and a very small nugget effect. This (137)Cs semivariogram showed a good autocorrelation (R(2)=0.91) and was well structured ('nugget-to-sill' ratio of 4%). It also revealed that the sampling strategy was adequate to reveal the spatial correlation of (137)Cs. The spatial redistribution of (137)Cs was estimated by Ordinary Kriging and IDW to produce contour maps. A radioisotope budget was established for the 2.16 ha agricultural field under investigation. It was estimated that around 2 x 10(7)Bq of (137)Cs were missing (around 30% of the total initial fallout) and were exported by physical processes (runoff and erosion processes) from the area under investigation. The cross-validation analysis showed that in the case of spatially structured data, OK is a better interpolation method than IDW1 or IDW2 for the assessment of potential radioactive contamination and/or pollution.
DOI: 10.1016/j.jenvrad.2007.05.008
PubMed: 17673340
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Mabit</name><affiliation wicri:level="1"><nlm:affiliation>Soil Science Unit, FAO/IAEA Agriculture and Biotechnology Laboratory, International Atomic Energy Laboratories Seibersdorf, A-2444 Seibersdorf, Austria. L.mabit@iaea.org</nlm:affiliation><country xml:lang="fr">Autriche</country><wicri:regionArea>Soil Science Unit, FAO/IAEA Agriculture and Biotechnology Laboratory, International Atomic Energy Laboratories Seibersdorf, A-2444 Seibersdorf</wicri:regionArea><wicri:noRegion>A-2444 Seibersdorf</wicri:noRegion></affiliation></author><author><name sortKey="Bernard, C" sort="Bernard, C" uniqKey="Bernard C" first="C" last="Bernard">C. Bernard</name></author></analytic><series><title level="j">Journal of environmental radioactivity</title><idno type="ISSN">0265-931X</idno><imprint><date when="2007" type="published">2007</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Cesium Radioisotopes (analysis)</term><term>Models, Statistical</term><term>Quebec</term><term>Radiation Monitoring (statistics & numerical data)</term><term>Radioactive Fallout (analysis)</term><term>Soil Pollutants, Radioactive (analysis)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>Cesium Radioisotopes</term><term>Radioactive Fallout</term><term>Soil Pollutants, Radioactive</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>Quebec</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Radiation Monitoring</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Models, Statistical</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">After introducing geostatistics concept and its utility in environmental science and especially in Fallout Radionuclide (FRN) spatialisation, a case study for cesium-137 ((137)Cs) redistribution at the field scale using geostatistics is presented. On a Canadian agricultural field, geostatistics coupled with a Geographic Information System (GIS) was used to test three different techniques of interpolation [Ordinary Kriging (OK), Inverse Distance Weighting power one (IDW1) and two (IDW2)] to create a (137)Cs map and to establish a radioisotope budget. Following the optimization of variographic parameters, an experimental semivariogram was developed to determine the spatial dependence of (137)Cs. It was adjusted to a spherical isotropic model with a range of 30 m and a very small nugget effect. This (137)Cs semivariogram showed a good autocorrelation (R(2)=0.91) and was well structured ('nugget-to-sill' ratio of 4%). It also revealed that the sampling strategy was adequate to reveal the spatial correlation of (137)Cs. The spatial redistribution of (137)Cs was estimated by Ordinary Kriging and IDW to produce contour maps. A radioisotope budget was established for the 2.16 ha agricultural field under investigation. It was estimated that around 2 x 10(7)Bq of (137)Cs were missing (around 30% of the total initial fallout) and were exported by physical processes (runoff and erosion processes) from the area under investigation. The cross-validation analysis showed that in the case of spatially structured data, OK is a better interpolation method than IDW1 or IDW2 for the assessment of potential radioactive contamination and/or pollution.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">17673340</PMID><DateCreated><Year>2007</Year><Month>09</Month><Day>24</Day></DateCreated><DateCompleted><Year>2008</Year><Month>01</Month><Day>31</Day></DateCompleted><DateRevised><Year>2007</Year><Month>09</Month><Day>24</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Print">0265-931X</ISSN><JournalIssue CitedMedium="Print"><Volume>97</Volume><Issue>2-3</Issue><PubDate><Year>2007</Year></PubDate></JournalIssue><Title>Journal of environmental radioactivity</Title><ISOAbbreviation>J Environ Radioact</ISOAbbreviation></Journal><ArticleTitle>Assessment of spatial distribution of fallout radionuclides through geostatistics concept.</ArticleTitle><Pagination><MedlinePgn>206-19</MedlinePgn></Pagination><Abstract><AbstractText>After introducing geostatistics concept and its utility in environmental science and especially in Fallout Radionuclide (FRN) spatialisation, a case study for cesium-137 ((137)Cs) redistribution at the field scale using geostatistics is presented. On a Canadian agricultural field, geostatistics coupled with a Geographic Information System (GIS) was used to test three different techniques of interpolation [Ordinary Kriging (OK), Inverse Distance Weighting power one (IDW1) and two (IDW2)] to create a (137)Cs map and to establish a radioisotope budget. Following the optimization of variographic parameters, an experimental semivariogram was developed to determine the spatial dependence of (137)Cs. It was adjusted to a spherical isotropic model with a range of 30 m and a very small nugget effect. This (137)Cs semivariogram showed a good autocorrelation (R(2)=0.91) and was well structured ('nugget-to-sill' ratio of 4%). It also revealed that the sampling strategy was adequate to reveal the spatial correlation of (137)Cs. The spatial redistribution of (137)Cs was estimated by Ordinary Kriging and IDW to produce contour maps. A radioisotope budget was established for the 2.16 ha agricultural field under investigation. It was estimated that around 2 x 10(7)Bq of (137)Cs were missing (around 30% of the total initial fallout) and were exported by physical processes (runoff and erosion processes) from the area under investigation. The cross-validation analysis showed that in the case of spatially structured data, OK is a better interpolation method than IDW1 or IDW2 for the assessment of potential radioactive contamination and/or pollution.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Mabit</LastName><ForeName>L</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Soil Science Unit, FAO/IAEA Agriculture and Biotechnology Laboratory, International Atomic Energy Laboratories Seibersdorf, A-2444 Seibersdorf, Austria. 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Bernard</name></noCountry><country name="Autriche"><noRegion><name sortKey="Mabit, L" sort="Mabit, L" uniqKey="Mabit L" first="L" last="Mabit">L. Mabit</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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