
Neural Networks for Hydrological Modeling
A A Balkema Publishers
1st Edition
Will be published approx. on 15. May 2004
Book
Hardback
230 pages
978-90-5809-619-7 (ISBN)
Description
A new approach to the fast-developing world of neural hydrological modelling, this book is essential reading for academics and researchers in the fields of water sciences, civil engineering, hydrology and physical geography. Each chapter has been written by one or more eminent experts working in various fields of hydrological modelling. The book covers an introduction to the concepts and technology involved, numerous case-studies with practical applications and methods, and finishes with suggestions for future research directions. Wide in scope, this book offers both significant new theoretical challenges and an examination of real-world problem-solving in all areas of hydrological modelling interest.
More details
Language
English
Place of publication
Rotterdam
Netherlands
Target group
Hydrologists, civil engineers, water scientists, physical geographers
Dimensions
Height: 246 mm
Width: 174 mm
Weight
720 gr
ISBN-13
978-90-5809-619-7 (9789058096197)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Robert Abrahart | P.E. Kneale | Linda M. See
Neural Networks for Hydrological Modeling
E-Book
05/2004
1st Edition
CRC Press
€73.99
Available for download

Robert Abrahart | P.E. Kneale | Linda M. See
Neural Networks for Hydrological Modeling
E-Book
05/2004
1st Edition
CRC Press
€73.99
Available for download
Persons
Abrahart, Robert; Kneale, P.E.; See, Linda M.
Editor
University of Nottingham, UK
University of Leeds, UK
University of Leeds, England
Content
1. Why Use Neural Networks? 2. Neural Network Modelling: Basic Tools and Broader Issues 3. Single Network Modelling Solutions 4. Hybrid Neural Network Modelling Solutions 5. The Application of Time Delay Neural Netowrks to River Level Forecasting 6. The Application of Cascade Correlation Neural Networks to River Flow Forecasting 7. The Use of Partial Recurrent Neural Networks for Autoregressive Modelling of Dynamic Hydrological Systems 8. RLF1/ Flood Foecasting via the Internet 9. Railfall-Runoff Modelling 10. A Neural Network Approach to Rainfall Forecasting in Urban Environments 11. Water Quality and Ecological Management in Freshwaters 12. Neural Network Modelling of Sediment Supply and Transfer 13. Nowcasting products from Meteorological Satellite Imagery 14. Mapping Land Cover from Remotely Sensed Imagery for Input to Hydrological Models 15. Towards a Hydrological Research Agenda Index