Global optimal design of ground water monitoring network using embedded kriging
Dhar, Anirban, and Datta, Bithin (2009) Global optimal design of ground water monitoring network using embedded kriging. Ground Water, 47 (6). pp. 806-815.
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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.
|Item Type:||Article (Refereed Research - C1)|
|FoR Codes:||09 ENGINEERING > 0907 Environmental Engineering > 090702 Environmental Engineering Modelling @ 50%|
09 ENGINEERING > 0905 Civil Engineering > 090509 Water Resources Engineering @ 50%
|SEO Codes:||96 ENVIRONMENT > 9606 Environmental and Natural Resource Evaluation > 960604 Environmental Management Systems @ 50%|
96 ENVIRONMENT > 9609 Land and Water Management > 960999 Land and Water Management of Environments not elsewhere classified @ 25%
96 ENVIRONMENT > 9605 Ecosystem Assessment and Management > 960509 Ecosystem Assessment and Management of Mountain and High Country Environments @ 25%
|Deposited On:||13 Apr 2010 13:37|
|Last Modified:||24 May 2013 01:08|
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