Artificial Neural Networks in Hydrology (Hardcover)

Acknowledgements. List of Contributors. Introduction; R.S. Govindaraju, A. Ramachandra Rao. 1. Effective and Efficient Modeling for Streamflow Forecasting; H.V. Gupta, et al. 2. Streamflow Forecasting Based on Artificial Neural Networks; J.D. Salas, et al. 3. Real Time Forecasting Using Neural Networks; M.C. Deo, K. Thirumalaiah. 4. Modular Neural Networks for Watershed Runoff; B. Zhang, R.S. Govindaraju. 5. Radial-Basis Function Networks; R.S. Govindaraju, B. Zhang. 6. Artificial Neural Networks in Subsurface Characterization; D.M. Rizzo, D.E. Dougherty. 7. Optimal Groundwater Remediation Using Artificial Neural Networks; L.L. Rogers, et al. 8. Adaptive Neural Networks in Regulation of River Flows; J.M. Reddy, B.M. Wilamowski. 9. Identification of Pollution Sources Via Neural Networks; G.M. Brion, S. Lingireddy. 10. Spatial Organization and Characterization of Soil Physical Properties Using Self-Organizing Maps; S. Islam, R. Kothari. 11. Rainfall Estimation From Satellite Imagery; K.-L. Hsu, et al. 12. Streamflow Data Infilling Techniques Based on Concepts of Groups and Neural Networks; U.S. Panu, et al. 13. Spatial Analysis of Hydrologic and Environmental Data Based on Artificial Neural Networks; H.-S. Shin, J.D. Salas. 14. Application of Artificial Neural Networks to Forecasting of Surface Water Quality Variables: Issues, Applications and Challenges; H.R. Maier, G.C. Dandy. 15. Long Range Precipitation Prediction in California: A Look Inside the `Black Box' of a Trained Network; D. Silverman, J.A. Dracup.