title: Fuzzy-stochastic characterization of site uncertainty and variability in groundwater flow and contaminant transport through a heterogeneous aquifer.
abstract: Site variabilities and uncertainties in data and information lead to significant spread in results of groundwater flow and contaminant transport models. A framework for hybrid propagation of random uncertainties represented by probability theory; nonrandom uncertainties represented by fuzzy set theory; and site variabilities represented by geostatistics was developed in this research. A case study was provided to explain the computational algorithm. The methodology presented here can be applied to complex environments where there are site variabilities as well as uncertainties of different kinds. The algorithm is suited when uncertainties in some variables may be best represented as fuzzy numbers whereas in others as probability distributions and both form part of the same governing equation.
authors.affiliation: Department of Civil Engineering, University of Calgary, Calgary, AB, Canada T2N 1N4.
authors.forename: Kejiang
authors.initials: K
authors.lastname: Zhang
authors.forename: Hua
authors.initials: H
authors.lastname: Li
authors.forename: Gopal
authors.initials: G
authors.lastname: Achari
mesh_terms: D004784:Environmental Monitoring / Q000379:methods / Q000706:statistics & numerical data; D005618:Fresh Water / Q000032:analysis*; D017143:Fuzzy Logic; D008962:Models, Theoretical; D015588:Observer Variation; D013269:Stochastic Processes; D035501:Uncertainty; D014872:Water Movements; D014874:Water Pollutants, Chemical / Q000032:analysis*
chemical_list: D014874:Water Pollutants, Chemical