Multiobjective Design of Dynamic Monitoring Networks for Detection of Groundwater Pollution

A methodology is developed based on the solution of optimization models for optimal design of groundwater quality monitoring networks. The optimal monitoring network is time varying as the monitoring wells are installed in stages, considering the transient pollutant transport process. The monitoring locations specified as solution to the optimization model change with time. This ensures additional economy in the installation of the network, compared to a single stage network design. The optimization model incorporates uncertainties in prediction or estimation of some of the aquifer parameters such as hydraulic conductivity and dispersivity. Advective, dispersive, and radioactive decay processes of transport in a two-dimensional groundwater system are considered. Randomly generated aquifer parameter values are used to simulate different realizations of resulting pollutant plumes incorporating uncertainties in predicting the transport process. The simulated pollutant plume realizations are subsequently util...

[1]  R. Freeze A stochastic‐conceptual analysis of one‐dimensional groundwater flow in nonuniform homogeneous media , 1975 .

[2]  J. Bredehoeft,et al.  Computer model of two-dimensional solute transport and dispersion in ground water , 1978 .

[3]  Ahmed E. Hassan,et al.  Heuristic space–time design of monitoring wells for contaminant plume characterization in stochastic flow fields , 2000 .

[4]  Patrick M. Reed,et al.  Striking the Balance: Long-Term Groundwater Monitoring Design for Conflicting Objectives , 2004 .

[5]  A. Charnes,et al.  Deterministic Equivalents for Optimizing and Satisficing under Chance Constraints , 1963 .

[6]  Wilson H. Tang,et al.  Optimal ground-water detection monitoring system design under uncertainty , 1999 .

[7]  Daniel J. Goode,et al.  Modification of a method-of-characteristics solute-transport model to incorporate decay and equilibrium-controlled sorption or ion exchange , 1989 .

[8]  L M Nunes,et al.  Optimal Space-time Coverage and Exploration Costs in Groundwater Monitoring Networks , 2004, Environmental monitoring and assessment.

[9]  Joel Massmann,et al.  Groundwater contamination from waste management sites: The interaction between risk‐based engineering design and regulatory policy: 1. Methodology , 1987 .

[10]  J. Eheart,et al.  Aquifer remediation design under uncertainty using a new chance constrained programming technique , 1993 .

[11]  Yuh-Ming Lee,et al.  Comparison of Algorithms for Nonlinear Integer Optimization: Application to Monitoring Network Design , 1996 .

[12]  B. Minsker,et al.  Cost‐effective long‐term groundwater monitoring design using a genetic algorithm and global mass interpolation , 2000 .

[13]  David E. Goldberg,et al.  Simplifying multiobjective optimization: An automated design methodology for the nondominated sorted genetic algorithm‐II , 2003 .

[14]  J. Bear Hydraulics of Groundwater , 1979 .

[15]  Miguel A. Mariño,et al.  Multivariate Geostatistical Design of Ground‐Water Monitoring Networks , 1994 .

[16]  Robert V. Hogg,et al.  Introduction to Mathematical Statistics. , 1966 .

[17]  Yeou-Koung Tung,et al.  Groundwater Management by Chance‐Constrained Model , 1986 .

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

[19]  B. Hobbs,et al.  Review of Ground‐Water Quality Monitoring Network Design , 1993 .

[20]  David E. Goldberg,et al.  Designing a competent simple genetic algorithm for search and optimization , 2000 .

[21]  Ricardo A. Olea,et al.  Lognormal kriging for the assessment of reliability in groundwater quality control observation networks , 1988 .

[22]  J. Eheart,et al.  Monitoring network design to provide initial detection of groundwater contamination , 1994 .

[23]  E. D. Brill,et al.  A method for locating wells in a groundwater monitoring network under conditions of uncertainty , 1988 .

[24]  J. Eheart,et al.  Using Genetic Algorithms to Solve a Multiobjective Groundwater Monitoring Problem , 1995 .

[25]  Brian J. Wagner,et al.  Sampling Design Methods For Groundwater Modeling Under Uncertainty , 1995 .

[26]  M. Vurro,et al.  Cokriging Optimization of Monitoring Network Configuration Based on Fuzzy and Non-Fuzzy Variogram Evaluation , 2003, Environmental monitoring and assessment.

[27]  D. McKinney,et al.  Network design for predicting groundwater contamination , 1992 .

[28]  George F. Pinder,et al.  Application of the Digital Computer for Aquifer Evaluation , 1968 .

[29]  Maria da Conceição Cunha,et al.  Groundwater Monitoring Network Optimization with Redundancy Reduction , 2004 .

[30]  H. Loáiciga An optimization approach for groundwater quality monitoring network design , 1989 .

[31]  Miguel A. Mariño,et al.  Regional-scale ground water quality monitoring via integer programming , 1995 .

[32]  S. Ranjithan,et al.  Using genetic algorithms to solve a multiple objective groundwater pollution containment problem , 1994 .

[33]  Bithin Datta,et al.  Chance-Constrained Optimal Monitoring Network Design for Pollutants in Ground Water , 1996 .

[34]  Jianfeng Wu,et al.  Cost-effective sampling network design for contaminant plume monitoring under general hydrogeological conditions. , 2005, Journal of contaminant hydrology.