Characterization of Groundwater Pollution Sources with Unknown Release Time History

Characterizations of unknown groundwater pollution sources in terms of source location, source flux release history and sources activity initiation times, from sparse observation concentration measurements are a challenging task. Optimization-based methods are often applied to solve groundwater pollution source characterization problem. These methods are effective only when the starting times of activity of the sources are precisely known, or the possible time window within which the sources activity actually start is known with a fair degree of certainty. However, in real life scenarios, the starting time of the activity of the sources is either unknown or can lie anywhere within a time window of years or decades. Absence of any prior information about the span of time window, within which the sources become active, makes existing source identification methodologies inefficient. As an alternative, an optimization-based source identification model is proposed, to simultaneously estimate source flux release history and sources activity initiation times. The method considers source flux release history and sources activity initiation times as explicit decision variables, optimally estimated by the decision model. Performance of the developed methodology is evaluated for an illustrative study area having multiple sources with different source activity initiation times, missing observation data and transient flow conditions. These evaluation results demonstrate the potential applicability of the proposed methodology and its capability to correctly estimate the unknown source flux releasing history and sources activity initiation times.

[1]  Reza Kerachian,et al.  Characterizing an unknown pollution source in groundwater resources systems using PSVM and PNN , 2010, Expert Syst. Appl..

[2]  C. Zheng,et al.  A Modular Three-Dimensional Multispecies Transport Model for Simulation of Advection, Dispersion, and Chemical Reactions of Contaminants in Groundwater Systems , 1997 .

[3]  Bithin Datta,et al.  Optimal Identification of Ground-Water Pollution Sources and Parameter Estimation , 2001 .

[4]  Bithin Datta,et al.  Development of an expert-system embedding pattern-recognition techniques for pollution-source identification. Report for 30 September 1987-29 November 1989 , 1989 .

[5]  K. Rushton.  Seepage and groundwater flow , 1979 .

[6]  Arlen W. Harbaugh,et al.  MODFLOW-2000, The U.S. Geological Survey Modular Ground-Water Model - User Guide to Modularization Concepts and the Ground-Water Flow Process , 2000 .

[7]  Bithin Datta,et al.  Optimal Monitoring Network and Ground-Water–Pollution Source Identification , 1997 .

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

[9]  D. Ouazar,et al.  Ground Water Contaminant Source and Transport Parameter Identification by Correlation Coefficient Optimization , 1998 .

[10]  Bithin Datta,et al.  Artificial neural network modeling for identification of unknown pollution sources in groundwater with partially missing concentration observation data , 2007 .

[11]  Amvrossios C. Bagtzoglou,et al.  On the Nonlocality of Reversible-Time Particle Tracking Methods , 2003 .

[12]  G. Mahinthakumar,et al.  Hybrid Genetic Algorithm—Local Search Methods for Solving Groundwater Source Identification Inverse Problems , 2005 .

[13]  J. Skopp,et al.  Physical and Chemical Hydrogeology, 2nd edition , 1999 .

[14]  Amvrossios C. Bagtzoglou,et al.  Marching‐jury backward beam equation and quasi‐reversibility methods for hydrologic inversion: Application to contaminant plume spatial distribution recovery , 2003 .

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

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

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

[18]  Ashu Jain,et al.  Identification of Unknown Groundwater Pollution Sources Using Artificial Neural Networks , 2004 .

[19]  Bithin Datta,et al.  Identification of unknown groundwater pollution sources using classical optimization with linked simulation , 2011 .

[20]  Om Prakash,et al.  Efficient Identification of Unknown Groundwater Pollution Sources Using Linked Simulation-Optimization Incorporating Monitoring Location Impact Factor and Frequency Factor , 2013, Water Resources Management.

[21]  Om Prakash,et al.  Sequential optimal monitoring network design and iterative spatial estimation of pollutant concentration for identification of unknown groundwater pollution source locations , 2013, Environmental Monitoring and Assessment.

[22]  Bithin Datta,et al.  Groundwater Pollution Source Identification and Simultaneous Parameter Estimation Using Pattern Matching by Artificial Neural Network , 2004 .

[23]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

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

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

[26]  Amvrossios C. Bagtzoglou,et al.  Pollution source identification in heterogeneous porous media , 2001 .

[27]  B. Datta,et al.  Identification of groundwater pollution sources using GA-based linked simulation optimization model , 2006 .

[28]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[29]  Bithin Datta,et al.  Simultaneous identification of unknown groundwater pollution sources and estimation of aquifer parameters , 2009 .

[30]  Bithin Datta,et al.  Optimal Dynamic Monitoring Network Design and Identification of Unknown Groundwater Pollution Sources , 2009 .

[31]  A. Bagtzoglou,et al.  State of the Art Report on Mathematical Methods for Groundwater Pollution Source Identification , 2001 .

[32]  Bithin Datta,et al.  Identification of Contaminant Source Characteristics and Monitoring Network Design in Groundwater Aquifers: An Overview , 2013 .

[33]  Bithin Datta,et al.  Optimisation approach for pollution source identification in groundwater: an overview , 2011 .

[34]  M Tamer Ayvaz,et al.  A linked simulation-optimization model for solving the unknown groundwater pollution source identification problems. , 2010, Journal of contaminant hydrology.

[35]  P. Domenico,et al.  Physical and chemical hydrogeology , 1990 .

[36]  Amvrossios C. Bagtzoglou,et al.  Near real-time atmospheric contamination source identification by an optimization-based inverse method , 2005 .

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

[38]  W. Yeh.  Review of Parameter Identification Procedures in Groundwater Hydrology: The Inverse Problem , 1986 .

[39]  Bithin Datta,et al.  Identification of Pollution Sources in Transient Groundwater Systems , 2000 .

[40]  Amvrossios C. Bagtzoglou,et al.  Mathematical Methods for Hydrologic Inversion: The Case of Pollution Source Identification , 2005 .

[41]  R. Ababou,et al.  Anti-diffusion and source identification with the ‘RAW’ scheme: A particle-based censored random walk , 2010 .

[42]  Mustafa M. Aral,et al.  Identification of Contaminant Source Location and Release History in Aquifers , 2001 .

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

[44]  Manish Jha,et al.  Simulated annealing based simulation-optimization approach for identification of unknown contaminant sources in groundwater aquifers , 2011 .