This book comprehensively accounts the advances in data-based approaches for hydrologic modeling and forecasting. Eight major and most popular approaches are selected, with a chapter for each - stochastic methods, parameter estimation techniques, scaling and fractal methods, remote sensing, artificial neural networks, evolutionary computing, wavelets, and nonlinear dynamics and chaos methods. These approaches are chosen to address a wide range of hydrologic system characteristics, processes, and the associated problems. Each of these eight approaches includes a comprehensive review of the fundamental concepts, their applications in hydrology, and a discussion on potential future directions.
Setting the Stage (B Sivakumar); Stochastic Methods (B Rajagopalan et al.); Parameter Estimation (J A Vrugt et al.); Scaling and Fractals (D Veneziano et al.); Remote Sensing (E Nikolopoulos et al.); Artificial Neural Networks (R J Abrahart et al.); Genetic Algorithms (M Franchini & S Alvisi); Wavelets (D Labat); Fuzzy Logic (A Bardossy); Nonlinear Dynamics and Chaos (B Sivakumar & R Berndtsson); Summary and Future (B Sivakumar & R Berndtsson).