Estimation of historical groundwater contaminant distribution using the adjoint state method applied to geostatistical inverse modeling

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A markov random field model of contamination source identification in porous media flow (2006, methodology): “We refer to these parameters as ‘structure variables’ following the terminology by Michalak and Kitanidis [4].”
Simultaneous identification of a single pollution point-source location and contamination time under known flow field conditions (2007, methodology): “Only few authors hav dealt with the source identification problem in multidimen sional heterogeneous systems, as for instance Aral et al. [2 Michalak and Kitanidis [14], Neupauer and Wilson [21 and Neupauer and Lin [15].”
A robust geostatistical approach to contaminant source identification (2007, methodology): “Examples of stochastic approaches include the minimum relative entropy approach [Woodbury and Ulrych, 1996; Woodbury et al., 1998], the geostatistical inversion approach (GS) [Snodgrass and Kitanidis, 1997; Michalak and Kitanidis, 2004 ], and the backward probabilistic model [Neupauer and Wilson, 1”
A constrained robust least squares approach for contaminant release history identification (2006, methodology): “[8] From our literature review and the comparison-ofmethodology table provided by Michalak and Kitanidis [2004] , we see in most of the previous studies, the effect of model error was often evaluated through ad hoc sensitivity studies.”