Comment on "Artificial neural network model as a potential alternative for groundwater salinity forecasting" by Pallavi Banerjee et al. [J. Hydrol. 398 (2011) 212–220]
Journal Contribution ResearchOnline@JCUAbstract
[Extract] Management of coastal aquifers for maintaining the water quality within permissible limits is an important groundwater management problem. Modeling saltwater intrusion is particularly challenging because of the density dependence of the saltwater intrusion process necessitating the simultaneous solution of flow and transport equations. Banerjee et al. has developed an artificial neural network (ANN) based model to optimize the aquifer exploitation to maintain the water quality within permissible limits. ANN model is developed for a real coastal aquifer in the Lakshadweep group of islands in India. The application of the methodology to the real life case study very well establishes the practical utility of the heuristic modeling tools like the ANN. The discussers would like to comment on the broader literature available on groundwater salinity predictions and management for coastal areas and about the ANN model development.
Journal
Journal of Hydrology
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420-421
ISBN/ISSN
0022-1694
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Pages Count
2
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Publisher
Elsevier
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DOI
10.1016/j.jhydrol.2011.12.012