River Flow Modelling Using Artificial Neural Network

Jitendra Sinha

ISBN 10: 3659474835 / ISBN 13: 9783659474835

Published by LAP LAMBERT Academic Publishing Okt 2013, 2013

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -Water is vital for life and the initial step in its management is to quantify the runoff produced in the catchment area due to rainfall. For stream flow measurement gauging of catchment is done. Because of the high cost involved in the setting up and maintenance of gauging stations, it is not possible to set up and maintain the stations over many locations for a long period of time. Thus, although many large catchments are gauged, a lot of small catchments still remain ungauged. The problem demands for modelling of stream flow. The traditional techniques of modelling not only require lengthy and reliable rainfall-runoff records, but also a procedure for updating the model parameters from time to time. Under such condition stream flow modelling is performed with reasonable accuracy by data driven artificial intelligence technique such as Artificial Neural Network. This book provides a comprehensive approach to stream flow modelling of Upper Kharun Catchment in Chhatttisgarh, India; involving two different methodologies of Artificial Neural Network. The book will be highly useful to the research scholars, academicians, hydrologists and water resources engineers.Books on Demand GmbH, Überseering 33, 22297 Hamburg 168 pp. Englisch.

Seller Inventory # 9783659474835

Bibliographic Details

• Title: River Flow Modelling Using Artificial Neural Network
• Publisher: LAP LAMBERT Academic Publishing Okt 2013
• Publication Date: 2013
• Language: English
• ISBN 10: 3659474835
• ISBN 13: 9783659474835
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 11D millimeters 220 millimeters width by 150 millimeters height by 11 millimeters depth
• Weight: 268 grams

About this title

Synopsis

Water is vital for life and the initial step in its management is to quantify the runoff produced in the catchment area due to rainfall. For stream flow measurement gauging of catchment is done. Because of the high cost involved in the setting up and maintenance of gauging stations, it is not possible to set up and maintain the stations over many locations for a long period of time. Thus, although many large catchments are gauged, a lot of small catchments still remain ungauged. The problem demands for modelling of stream flow. The traditional techniques of modelling not only require lengthy and reliable rainfall-runoff records, but also a procedure for updating the model parameters from time to time. Under such condition stream flow modelling is performed with reasonable accuracy by data driven artificial intelligence technique such as Artificial Neural Network. This book provides a comprehensive approach to stream flow modelling of Upper Kharun Catchment in Chhatttisgarh, India; involving two different methodologies of Artificial Neural Network. The book will be highly useful to the research scholars, academicians, hydrologists and water resources engineers.

About the Author

Jitendra SinhaB.Tech. Agril. Engg.(Gold Medalist) JNKVV, JabalpurM.Tech. SWC Engg.,(First Class) GBPUA&T, PantnagarPhD. Soil & Water Engg.(Gold Medalist), IGKV, RaipurDr Jitendra Sinha, Scientist, SWE, Indira Gandhi Krishi Vishwavidyalaya, Raipur, India; bears 14 years of professional experience and has published more than 20 scientific papers.