Practical Hydroinformatics

Computational Intelligence and Technological Developments in Water Applications

  • Robert J. Abrahart
  • Linda M. See
  • Dimitri P. Solomatine

Part of the Water Science and Technology Library book series (WSTL, volume 68)

Table of contents

  1. Front Matter
    Pages I-XV
  2. Hydroinformatics: Integrating Data and Models

    1. Front Matter
      Pages 1-1
    2. D. Solomatine, L.M. See, R.J. Abrahart
      Pages 17-30
  3. Artificial Neural Network Models

  4. Models Based on Fuzzy Logic

    1. Front Matter
      Pages 163-163
    2. A. Bardossy
      Pages 177-187
    3. C.K. Makropoulos, D. Butler, C. Maksimovic
      Pages 215-228
  5. Global and Evolutionary Optimization

  6. Emerging Technologies

  7. Model Integration

About this book


Hydroinformatics is an emerging subject that is expected to gather speed, momentum and critical mass throughout the forthcoming decades of the 21st century. This book provides a broad account of numerous advances in that field - a rapidly developing discipline covering the application of information and communication technologies, modelling and computational intelligence in aquatic environments. A systematic survey, classified according to the methods used (neural networks, fuzzy logic and evolutionary optimization, in particular) is offered, together with illustrated practical applications for solving various water-related issues. These include, but are not limited to, flood estimation, rainfall-runoff modelling, rehabilitation of urban water networks, estimation of ocean temperature profiles, etc. Particular attention is also given to certain aspects of the most recent technological progress in hydroinformatics including the development of protocols for model integration and of computer architectures for modern modelling systems. Invited contributions were obtained from leading international experts - including academics, hydrological practitioners and industrial professionals - such that this edited volume constitutes an authoritative source of reference material and is essential reading for active workers in this field.


Fuzzy Groundwater algorithms computational intelligence decision support system digital elevation model hydroinformatics hydrology intelligence learning machine learning optimization soft computing uncertainty water resources

Editors and affiliations

  • Robert J. Abrahart
    • 1
  • Linda M. See
    • 2
  • Dimitri P. Solomatine
    • 3
    • 4
  1. 1.Dept. GeographyUniversity NottinghamUniversity ParkUnited Kingdom NT7 2QW
  2. 2.School of Geography Fac. Earth and EnvironmentUniversity of LeedsLeedsUnited Kingdom LS2 9JT
  3. 3.UNESCO - IHEInstitute for Water EducationThe Netherlands
  4. 4.Water Resources SectionDelft University of TechnologyThe Netherlands

Bibliographic information