Groundwater Modelling | A Comparison Between Multiple Regression and Artificial Neural Network Approaches

Rupak Sarkar

ISBN 10: 3659259489 / ISBN 13: 9783659259487

Published by LAP LAMBERT Academic Publishing, 2012

About this Item

Groundwater Modelling | A Comparison Between Multiple Regression and Artificial Neural Network Approaches | Rupak Sarkar | Taschenbuch | 156 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659259487 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 106236668

Bibliographic Details

• Title: Groundwater Modelling | A Comparison Between Multiple Regression and Artificial Neural Network Approaches
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2012
• Language: English
• ISBN 10: 3659259489
• ISBN 13: 9783659259487
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 10D millimeters 220 millimeters width by 150 millimeters height by 10 millimeters depth
• Weight: 250 grams
• Seller catalogs:
  • Bücher

About this title

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.

About the Author

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.