Adjoint‐derived location and travel time probabilities for a multidimensional groundwater system

By R. Neupauer, John L. Wilson. 2001

164 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Environmental Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/33b86b8e685c873bb3d1c08b7b5dbd0b801f3ac1

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In Civil and Structural Engineering

In Environmental Engineering

In Water Science and Technology

Citations in the corpus

State of the Art Report on Mathematical Methods for Groundwater Pollution Source Identification (2001, methodology): “In this and the follow-up paper, Neupauer and Wilson (1999; 2001) presented the adjoint method as a formal framework for obtaining the backward-in-time probabilities for multidimensional problems and more complex domain geometries.”
A robust geostatistical approach to contaminant source identification (2007, methodology): “…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, 1999, 2001, 2003].”
A method for enforcing parameter nonnegativity in Bayesian inverse problems with an application to contaminant source identification (2003, methodology): “…include geostatistical techniques [Snodgrass and Kitanidis, 1997; Michalak and Kitanidis, 2002, 2003], minimum relative entropy methods [Woodbury and Ulrych, 1996; Woodbury et al., 1998; Neupauer et al., 2000], and adjoint-derived source distribution probabilities [Neupauer and Wilson, 1999, 2001].”
Simultaneous identification of a single pollution point-source location and contamination time under known flow field conditions (2007, methodology): “and the backward pdf F q with an initial unit-mass input at a point x1 is a solution of the transport equation with a reversed flow field [16,17]”
Estimation of historical groundwater contaminant distribution using the adjoint state method applied to geostatistical inverse modeling (2004, methodology): “These methods include backward tracking [Bagtzoglou et al., 1991; Bagtzoglou and Dougherty, 1992] and adjoint-derived source distribution probabilities [Neupauer and Wilson, 1999, 2001, 2002].”