Recovering the release history of a groundwater contaminant using a non-linear least-squares method.

A non-linear least-squares (NLS) method is used without regularization to recover the release history of a groundwater contaminant plume from its current measured spatial distribution. The flow system is assumed to be one-dimensional, with the plume originating from a known single site. The solution is found to be very sensitive to noise and to the extent to which the plume is dissipated. Although the NLS method is extremely sensitive to measurement errors for the gradual release scenario, it can resolve the release histories for catastrophic release scenarios reasonably well, even in the presence of moderate measurement errors. A number of synthetic numerical examples are analysed. We find that for catastrophic contaminant releases the NLS method may be an alternative to the Tikhonov regularization approach.

[1]  Allan D. Woodbury,et al.  Three-dimensional plume source reconstruction using minimum relative entropy inversion , 1998 .

[2]  J. Hadamard,et al.  Lectures on Cauchy's Problem in Linear Partial Differential Equations , 1924 .

[3]  Brian J. Wagner,et al.  Simultaneous parameter estimation and contaminant source characterization for coupled groundwater flow and contaminant transport modelling , 1992 .

[4]  N. Draper,et al.  Applied Regression Analysis , 1966 .

[5]  W. Durner Transfer Functions and Solute Movement through Soil , 1992 .

[6]  William H. Press,et al.  Numerical recipes in C. The art of scientific computing , 1987 .

[7]  T. Ulrych,et al.  Minimum Relative Entropy Inversion: Theory and Application to Recovering the Release History of a Groundwater Contaminant , 1996 .

[8]  T. Skaggs,et al.  Comment on “Minimum relative entropy inversion: Theory and application to recovering the release history of a groundwater contaminant” by Allan D. Woodbury and Tadeusz J. Ulrych , 1998 .

[9]  J. Ross Macdonald Solution of an ‘‘impossible’’ diffusion‐inversion problem , 1995 .

[10]  William P. Ball,et al.  Application of inverse methods to contaminant source identification from aquitard diffusion profiles at Dover AFB, Delaware , 1999 .

[11]  R. Kerry Rowe,et al.  Ground water models: scientific and regulatory applications , 1990 .

[12]  T. Ulrych,et al.  Reply [to “Comment on ‘Minimum relative entropy inversion: Theory and application to recovering the release history of a groundwater contaminant’ by Allan D. Woodbury and Tadeusz J. Ulrych”] , 1998 .

[13]  Stephen Wolfram,et al.  Mathematica: a system for doing mathematics by computer (2nd ed.) , 1991 .

[14]  P. Kitanidis,et al.  A geostatistical approach to contaminant source identification , 1997 .

[15]  T. Skaggs,et al.  Recovering the release history of a groundwater contaminant , 1994 .

[16]  T. Skaggs,et al.  Limitations in recovering the history of a groundwater contaminant plume , 1998 .

[17]  川口 光年,et al.  R.D.Richtmyer: Difference Methods for Initial-Value Problems. Interscience Pub. Inc. New York, 1957, xii+238頁, 15×23cm, \2,600. , 1958 .

[18]  T. Skaggs,et al.  Recovering the History of a Groundwater Contaminant Plume: Method of Quasi‐Reversibility , 1995 .

[19]  R. D. Richtmyer,et al.  Difference methods for initial-value problems , 1959 .

[20]  A. N. Tikhonov,et al.  Solutions of ill-posed problems , 1977 .

[21]  S. Gorelick,et al.  Identifying sources of groundwater pollution: An optimization approach , 1983 .

[22]  William H. Press,et al.  The Art of Scientific Computing Second Edition , 1998 .

[23]  A. Bagtzoglou,et al.  Application of particle methods to reliable identification of groundwater pollution sources , 1992 .