No abstract

No abstract

The identification of unknown pollution sources is a prerequisite for designing of a remediation strategy. In most of the real world situations, it is difficult to identify the pollution sources without a scientifically designed efficient monitoring network. The locations of the contaminant concentration measurement sites would determine the efficiency of the unknown source identification process to a large extent. Therefore coupled and iterative sequential source identification and dynamic monitoring network design framework is developed. The coupled approach provides a framework for necessary sequential exchange of information between monitoring network and source identification methodology. The preliminary identification of unknown sources, based on limited concentration data from existing arbitrarily located wells provides the initial rough estimate of the source fluxes. These identified source fluxes are then utilized for designing an optimal monitoring network for the first stage. Both the monitoring network and source identification process is repeated by sequential identification of sources and design of monitoring network which provides the feedback information. In the optimal source identification model, the Jacobian matrix which is the determinant for the search direction in the nonlinear optimization model links the groundwater flow-transport simulator and the optimization method. For the optimal monitoring network design, the integer programming based optimal design model requires as input, simulated sets of concentration data. In the proposed methodology, the concentration measurement data from the designed and 2032 B. Datta et al.implemented monitoring network are used as feedback information for sequential identification of unknown pollution sources. The potential applicability of the developed methodology is demonstrated for an illustrative study area.

No abstract

No abstract

Groundwater remediation and management systems generally encompass multiple often conflicting objectives. This paper proposes a multi-objective groundwater remediation and management methodology based on pump-and-treat technology to determine optimal strategies for cleaning up the affected portion of a contaminated aquifer and at the same time removal of sufficient quantity of clean water from the unaffected portion of the same aquifer for supply to end users for drinking purposes. Two objective functions are incorporated into the proposed optimization model: (i) minimization of the total remediation cost, and (ii) maximization of clean water extraction rate. Pumping rates and well locations are the decision variables of the optimization model with imposed constraints on hydraulic heads and contaminant concentrations at several specified locations. This work employs a new and very efficient technique for interfacing C with FORTRAN programs to couple NSGA−II coded in C with FORTRAN programs MODFLOW and MT3DMS and use in this methodology to obtain a tradeoff between remediation cost and clean water extraction rate. The Pareto front thus obtained consists of several optimal solutions to the problem and is used to analyze the variation of remediation cost with the extraction rate of uncontaminated water. Sensitivity analyses on some important input parameters have been carried out to account for the effects of variability of these parameters on the model result. Main contributions of this paper are: (i) use of a novel technique of linking C programs with FORTRAN programs, and (ii) revelation and exploitation of insightful features of multi-objective optimization algorithms applicable to pump-and-treat groundwater remediation problems. Results are satisfactory and show great promise for wide applicability in the field of groundwater remediation.

No abstract

No abstract