Groundwater Modelling: A Comparison Between Multiple Regression and Artificial Neural Network Approaches - Couverture souple

Sarkar, Rupak

 
9783659259487: Groundwater Modelling: A Comparison Between Multiple Regression and Artificial Neural Network Approaches
Couverture souple
ISBN 10 : 3659259489 ISBN 13 : 9783659259487
Editeur : LAP LAMBERT Academic Publishing, 2012

Synopsis

Groundwater is being exploited indiscriminately to meet our ever increasing demand of water in different parts of the world. In India, the Gangetic plane is amongst the most fertile land of the country. Over the past couple of decades, intensive growth in agriculture, industries, and human population have increased the water demand substantially. As a result severe problems of groundwater table declination have taken place causing threat to future availability of water. Keeping these in view, a study was undertaken in the Ramganga-Bahgul interbasin of Uttar Pradesh, India, to investigate the groundwater behaviour, analyse the causes behind water table declination, and estimate the stages of groundwater development. The collected field data were used to develop groundwater models using multiple regression and artificial neural network (ANN) approaches for the prediction of seasonal water table depths below ground level in the study area. The performance of both multiple regression and ANN models were compared and evaluated.

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Présentation de l'éditeur

Groundwater is being exploited indiscriminately to meet our ever increasing demand of water in different parts of the world. In India, the Gangetic plane is amongst the most fertile land of the country. Over the past couple of decades, intensive growth in agriculture, industries, and human population have increased the water demand substantially. As a result severe problems of groundwater table declination have taken place causing threat to future availability of water. Keeping these in view, a study was undertaken in the Ramganga-Bahgul interbasin of Uttar Pradesh, India, to investigate the groundwater behaviour, analyse the causes behind water table declination, and estimate the stages of groundwater development. The collected field data were used to develop groundwater models using multiple regression and artificial neural network (ANN) approaches for the prediction of seasonal water table depths below ground level in the study area. The performance of both multiple regression and ANN models were compared and evaluated.

Biographie de l'auteur

Dr. Rupak Sarkar (Ph.D. in Civil Engineering from Indian Institute of Technology Guwahati, India) is presently working as Assistant Professor at Faculty of Technology, Uttar Banga Krishi Viswavidyalaya, India. Dr. Sarkar is actively involved in hydrological research and he has published papers in national and international journals of high repute.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2012
Langue
anglais
ISBN 10 
3659259489
ISBN 13 
9783659259487
Reliure
Broché
Nombre de pages
156
Coordonnées du fabricant
non disponible
Personne responsable
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