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Application of Evidence Theory to Quantify Uncertainty in Contaminant Transport Modeling
Spatial variability and uncertainty in the hydrogeologic system make contaminant transport in the subsurface a complex phenomenon. Both random and non random uncertainties exist in contaminant transport modeling. An ideal approach is to use possibilistic distributions based on fuzzy sets for non random uncertainties and probabilistic distributions based on frequency of occurrence for random uncertainties. Thus, both probability and possibility distributions need to be incorporated. This paper presents a method using fuzzy-stochastic partial differential equations (FSPDEs) to simulate the uncertainties in contaminant fate and transport. In this paper, we use evidence theory, which can be related to both probability and possibility theory and is thus more suitable to quantify probabilistic and possibilistic uncertainties in contaminant transport modeling. Ranges of final results of FSPDEs, based on evidence theory, are presented in the form of upper and lower limits given by plausibility PlmaxT and belief function BelminT, respectively.
Application of Evidence Theory to Quantify Uncertainty in Contaminant Transport Modeling
Spatial variability and uncertainty in the hydrogeologic system make contaminant transport in the subsurface a complex phenomenon. Both random and non random uncertainties exist in contaminant transport modeling. An ideal approach is to use possibilistic distributions based on fuzzy sets for non random uncertainties and probabilistic distributions based on frequency of occurrence for random uncertainties. Thus, both probability and possibility distributions need to be incorporated. This paper presents a method using fuzzy-stochastic partial differential equations (FSPDEs) to simulate the uncertainties in contaminant fate and transport. In this paper, we use evidence theory, which can be related to both probability and possibility theory and is thus more suitable to quantify probabilistic and possibilistic uncertainties in contaminant transport modeling. Ranges of final results of FSPDEs, based on evidence theory, are presented in the form of upper and lower limits given by plausibility PlmaxT and belief function BelminT, respectively.
Application of Evidence Theory to Quantify Uncertainty in Contaminant Transport Modeling
Zhang, Kejiang (author) / Achari, Gopal (author) / Li, Hua (author)
GeoCongress 2008 ; 2008 ; New Orleans, Louisiana, United States
GeoCongress 2008 ; 782-789
2008-03-07
Conference paper
Electronic Resource
English
Application of Evidence Theory to Quantify Uncertainty in Contaminant Transport Modeling
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