Abstract

A methodology is developed based on an optimization model solution for optimal design of groundwater quality monitoring network. Redundancy in monitoring network results in economic and overall inefficiency of the network. Therefore, redundancy reduction is an important issue in the optimal design of a monitoring network. The developed methodology reduces monitoring redundancy. It incorporates the inverse distance weighting method for spatial interpolation of concentration data. The formulated logic-based mixed-integer linear optimization model is solved using the branch-and-bound algorithm. The proposed methodology is tested for a real world problem. Performance of the proposed methodology is evaluated for different scenarios using available historical concentration data. These performance evaluation results show that the proposed methodology performs satisfactorily when compared with other existing methodologies. These results demonstrate the potential applicability of the proposed methodology for groundwater contaminant monitoring network design, while incorporating reduction in redundancy of monitoring locations.

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