Optimisation approach for pollution source identification in groundwater: an overview

Chadalavada, Sreenivasulu, Datta, Bithin, and Naidu, Ravi (2011) Optimisation approach for pollution source identification in groundwater: an overview. International of Environment and Waste Management, 8 (1-2). pp. 40-61.

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DOI: 10.1504/IJEWM.2011.040964

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Abstract

Groundwater pollution occurs from different anthropogenic sources like leakage from Underground Storage Tanks (USTs) and depositories, leakage from hazardous waste dump sites and soak pits. Remediation of these contaminated sites requires optimal decision-making system so that the remediation is done in a cost-effective and efficient manner. Identification of unknown pollution sources plays an important role in remediation and containment of contaminant plume in a hazardous site. This paper reviews different optimisation algorithms like classical, nonclassical such as Genetic Algorithm, Artificial Neural Network and Simulated Annealing and hybrid methods, which can be applied for optimal identification of unknown groundwater pollution sources.


Item ID:	21405
Item Type:	Article (Research - C1)
ISSN:	1478-9868
Keywords:	groundwater contamination; pollution sources; source identification; optimisation; monitoring networks; water pollution; genetic algorithms; artificial neural networks; ANNs; simulated annealing.
Date Deposited:	03 Apr 2012 23:35
FoR Codes:	09 ENGINEERING > 0905 Civil Engineering > 090509 Water Resources Engineering @ 50% 09 ENGINEERING > 0907 Environmental Engineering > 090799 Environmental Engineering not elsewhere classified @ 50%
SEO Codes:	96 ENVIRONMENT > 9609 Land and Water Management > 960999 Land and Water Management of Environments not elsewhere classified @ 100%
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