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.
1. Why Use Neural Networks? Pauline E.Kneale, Linda M. See & Robert J.Abrahart 2. Neural Network Modelling: Basic Tools and Broader Issues Robert J.Abrahart 3. Single Network Modelling Solutions Christian W.Dawson & Robert L.Wilby 4. Hybrid Neural Network Modelling Solutions Asaad Y.Shamseldin 5. The Application of Time Delay Neural Networks to River Level Forecasting Linda M.See & Pauline E.Kneale 6. The Application of Cascade Correlation Neural Networks to River Flow Forecasting Claire E.Imrie 7. The Use of Partial Recurrent Neural Networks for Autoregressive Modelling of Dynamic Hydrological Systems Henk F.P.van den Boogaard 8. RLF1/ Flood Forecasting via the Internet Simon A.Corne & Stan Openshaw 9. Rainfall-Runoff Modelling Anthony W.Minns & Michael J.Hall 10. A Neural Network Approach to Rainfall Forecasting in Urban Environments James E.Ball & Kin Choi Luk 11. Water Quality and Ecological Management in Freshwaters Pauline E.Kneale 12. Neural Network Modelling of Sediment Supply and Transfer Susan M.White 13. Nowcasting products from Meteorological Satellite Imagery George S.Pankiewicz 14. Mapping Land Cover from Remotely Sensed Imagery for Input to Hydrological Models Giles M.Foody 15. Towards a Hydrological Research Agenda Robert J.Abrahart, Pauline E.Kneale & Linda M.See Index