Cokriging Optimization of Monitoring Network Configuration Based on Fuzzy and Non-Fuzzy Variogram Evaluation
Identifieur interne : 007A88 ( Main/Exploration ); précédent : 007A87; suivant : 007A89Cokriging Optimization of Monitoring Network Configuration Based on Fuzzy and Non-Fuzzy Variogram Evaluation
Auteurs : G. Passarella [Italie] ; M. Vurro [Italie] ; V. D'Agostino [Italie] ; M. J. Barcelona [États-Unis]Source :
- Environmental Monitoring and Assessment [ 0167-6369 ] ; 2003-02-01.
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Abstract
Abstract: A number of optimization approaches regarding monitoring networkdesign and sampling optimization procedures have been reported inthe literature. Cokriging Estimation Variance (CEV) is a usefuloptimization tool to determine the influence of the spatial configuration of monitoring networks on parameter estimations. Itwas used in order to derive a reduced configuration of a nitrateconcentration monitoring well network. The reliability of the reduced monitoring configuration suffers from the uncertainties caused by the variographer's choices and several inherent assumptions. These uncertainties can be described considering thevariogram parameters as fuzzy numbers and the uncertainties by means of membership functions.Fuzzy and non-fuzzy approaches were used to evaluate differencesamong well network configurations. Both approaches permitted estimates of acceptable levels of information loss for nitrate concentrations in the monitoring network of the aquifer of the Plain of Modena, Northern Italy. The fuzzy approach was found torequire considerably more computational time and numbers of wellsat comparable level of information loss.
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DOI: 10.1023/A:1021662705554
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Cokriging Estimation Variance (CEV) is a usefuloptimization tool to determine the influence of the spatial configuration of monitoring networks on parameter estimations. Itwas used in order to derive a reduced configuration of a nitrateconcentration monitoring well network. The reliability of the reduced monitoring configuration suffers from the uncertainties caused by the variographer's choices and several inherent assumptions. These uncertainties can be described considering thevariogram parameters as fuzzy numbers and the uncertainties by means of membership functions.Fuzzy and non-fuzzy approaches were used to evaluate differencesamong well network configurations. Both approaches permitted estimates of acceptable levels of information loss for nitrate concentrations in the monitoring network of the aquifer of the Plain of Modena, Northern Italy. The fuzzy approach was found torequire considerably more computational time and numbers of wellsat comparable level of information loss.</div></front></TEI><affiliations><list><country><li>Italie</li><li>États-Unis</li></country><region><li>Michigan</li></region></list><tree><country name="Italie"><noRegion><name sortKey="Passarella, G" sort="Passarella, G" uniqKey="Passarella G" first="G." last="Passarella">G. Passarella</name></noRegion><name sortKey="D Agostino, V" sort="D Agostino, V" uniqKey="D Agostino V" first="V." last="D'Agostino">V. D'Agostino</name><name sortKey="Passarella, G" sort="Passarella, G" uniqKey="Passarella G" first="G." last="Passarella">G. Passarella</name><name sortKey="Vurro, M" sort="Vurro, M" uniqKey="Vurro M" first="M." last="Vurro">M. Vurro</name></country><country name="États-Unis"><region name="Michigan"><name sortKey="Barcelona, M J" sort="Barcelona, M J" uniqKey="Barcelona M" first="M. J." last="Barcelona">M. J. 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