Artificial neural networks approximation of density dependent saltwater intrusion process in coastal aquifers
Bhattacharjya, Rajib Kumar, Datta, Bithin, and Satish, Mysore (2007) Artificial neural networks approximation of density dependent saltwater intrusion process in coastal aquifers. Journal of Hydrologic Engineering, 12 (3). pp. 273-282.
PDF (Published Version)
Restricted to Repository staff only
The flow and transport processes in a coastal aquifer are highly nonlinear, where both the flow and transport processes become density dependent. Therefore, numerical simulation of the saltwater intrusion process in such an aquifer is complex and time consuming. An approximate simulation of those complex flow and transport processes may be very useful, if sufficiently accurate, especially where repetitive simulations of these processes are necessary. A simulation methodology using a trained artificial neural network (ANN)is developed to approximate the three-dimensional density dependent flow and transport processes in a coastal aquifer. The data required for initially training the ANN model is generated by using a numerical simulation model (FEMWATER). The simulated data consisting of corresponding sets of input and output patterns are used to train a multilayer perceptron using the back-propagation algorithm. The trained ANN predicts the concentration at specified observation locations at different times. The performance of the ANN as a simulator of the density dependent saltwater intrusion process in a coastal aquifer is evaluated using an illustrative study area. These evaluation results show that the ANN technique can be successfully used for approximating the three-dimensional flow and transport processes in coastal aquifers.
|Item Type:||Article (Refereed Research - C1)|
|Keywords:||neural networks; salt water intrusion; aquifers; coastal environment; simulation.|
|Date Deposited:||14 Apr 2010 01:15|
|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 > 960506 Ecosystem Assessment and Management of Fresh, Ground and Surface Water Environments @ 25%