Environmental and hydrological systems modelling / A. W. Jayawardena.

Includes bibliographical references and index.

1 Introduction --
2 Historical Development of Hydrological Modelling --
3 Population Dynamics --
4 Reaction Kinetics --
5 Water Quality Systems --
6 Longitudinal Dispersion --
7 Time Series Analysis and Forecasting --
8 Artificial Neural Networks --
9 Radial Basis Function (RBF) Neural Networks --
10 Fractals and chaos --
11 Dynamical Systems Approach of Modelling --
12 Support Vector Machines --
13 Fuzzy Logic Systems --
14 Genetic Algorithms (GAs) and Genetic Programming (GP).

Mathematical modelling has become an indispensable tool for engineers, scientists, planners, decision makers, and many other professionals who need to make predictions of future scenarios as well as real impending events. As modelling approaches and the model to be used are problem-specific, no single model or approach can be used to solve all problems, and there are constraints in each situation. Modellers therefore need to have a range of choices when confronted with constraints such as lack of sufficient data, resources, expertise, and time. Environmental and Hydrological Systems Modelling provides the tools for students and professionals embarking on a modelling project. The book presents different approaches to modelling the water environment over a range of spatial and temporal scales. Applications are shown with a series of case studies, taken mainly from the Asia-Pacific Region. Coverage includes:Linear systems Conceptual models Data driven models Process-based models Risk-management models Model parameter estimation Model calibration, validation and testing.