Global optimal design of ground water monitoring network using embedded kriging.
We present a methodology for global optimal design of ground water quality monitoring networks using a linear mixed-integer formulation. The proposed methodology incorporates ordinary kriging (OK) within the decision model formulation for spatial estimation of contaminant concentration values. Different monitoring network design models incorporating concentration estimation error, variance estimation error, mass estimation error, error in locating plume centroid, and spatial coverage of the designed network are developed. A big-M technique is used for reformulating the monitoring network design model to a linear decision model while incorporating different objectives and OK equations. Global optimality of the solutions obtained for the monitoring network design can be ensured due to the linear mixed-integer programming formulations proposed. Performances of the proposed models are evaluated for both field and hypothetical illustrative systems. Evaluation results indicate that the proposed methodology performs satisfactorily. These performance evaluation results demonstrate the potential applicability of the proposed methodology for optimal ground water contaminant monitoring network design.
Dhar
Anirban
A
School of Engineering, James Cook University, Townsville, QLD 4811, Australia.
Datta
Bithin
B
D004784:Environmental Monitoring / Q000379:methods*; D060587:Groundwater; D062070:Hydrology / Q000379:methods*; D008962:Models, Theoretical; D062206:Spatial Analysis; D014241:Trichloroethylene / Q000032:analysis; D014861:Washington; D014874:Water Pollutants, Chemical / Q000032:analysis; D014876:Water Pollution
D014874:Water Pollutants, Chemical; D014241:Trichloroethylene