Environmental and Hydrological Systems Modelling (Paperback) book cover

Environmental and Hydrological Systems Modelling

By A W Jayawardena

© 2014 – CRC Press

536 pages | 141 B/W Illus.

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Paperback: 9780415465328
pub: 2014-01-21
eBook (VitalSource) : 9781466584228
pub: 2014-01-23
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About the Book

Mathematical modelling has become an indispensable tool for engineers, scientists, planners, decision makers and many other professionals to make predictions of future scenarios as well as real impending events. As the modelling approach 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 choice when confronted with constraints such as lack of sufficient data, resources, expertise and time.

Environmental and Hydrological Systems Modelling provides the tools needed by presenting different approaches to modelling the water environment over a range of spatial and temporal scales. Their applications are shown with a series of case studies, taken mainly from the Asia-Pacific Region. Coverage includes:

  • Population dynamics
  • Reaction kinetics
  • Water quality systems
  • Longitudinal dispersion
  • Time series analysis and forecasting
  • Artificial neural networks
  • Fractals and chaos
  • Dynamical systems
  • Support vector machines
  • Fuzzy logic systems
  • Genetic algorithms and genetic programming

This book will be of great value to advanced students, professionals, academics and researchers working in the water environment.

Table of Contents

Introduction. Historical Development of the Systems Theory Approach to Modelling. Population Dynamics. Reaction Kinetics. Water Quality Systems. Longitudinal Dispersion. Stochastic Models – Time Series Analysis and Modeling. Artificial Neural Networks. Radial Basis Function Networks. Fuzzy Logic Systems and Their Variations. Dynamical Systems Approach - Phase Space Re-Construction. Genetic Algorithms and Genetic Programming. Wavelet Decomposition. Process Based (Distributed) Models. Model Parameter Optimization. Closure.

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