ISSN: 2157-7617

Journal of Earth Science & Climatic Change
Open Access

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
  • Research Article   
  • J Earth Sci Clim Change 2015, Vol 6(5): 274
  • DOI: 10.4172/2157-7617.1000274

Application of Artificial Neural Network for Groundwater Level Simulation in Amritsar and Gurdaspur Districts of Punjab, India

Lohani AK1 and Krishan G1,2*
1National Institute of Hydrology, , Roorkee-247667, Uttarakhand, India
2IGB Groundwater Resilience Project, British Geological Survey, , United Kingdom
*Corresponding Author : Krishan G, IGB Groundwater Resilience Project, British Geological Survey, United Kingdom, Tel: +91-1332-272108, Email: drgopal.krishan@gmail.com

Received Date: Apr 21, 2015 / Accepted Date: Apr 28, 2015 / Published Date: May 08, 2015

Abstract

In this paper, the most stable and efficient neural network configuration for predicting groundwater level in Amritsar and Gurdaspur districts of Punjab, India is identified. For predicting the model efficiency and accuracy, different types of network architectures and training algorithms are investigated and compared. It has been found that accurate predictions can be achieved with a standard feed forward neural network trained with the Levenberg–Marquardt algorithm providing the best results. Good estimation of groundwater level can be achieved by dividing the boreholes/observation wells into different groups of data and designing distinct networks which is validated by the ANN technique and the degree of accuracy of the ANN model in groundwater level forecasting is within acceptable limits. The ANN method has been found to forecast groundwater level in Amritsar and Gurdaspur districts of Punjab, India.

Keywords: Artificial neural networks; Groundwater level forecasting; Amritsar; Gurdaspur; Punjab; Aquifer exploitation

Citation: Lohani AK, Krishan G (2015) Application of Artificial Neural Network for Groundwater Level Simulation in Amritsar and Gurdaspur Districts of Punjab, India. J Earth Sci Clim Change 6: 274. Doi: 10.4172/2157-7617.1000274

Copyright: ©2015 Lohani AK, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Top