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Hydroinformatics addresses cross-disciplinary issues ranging from technological and sociological to more general environmental concerns, including an ethical perspective. It covers the application of information technology in the widest sense to problems of the aquatic environment.This two-volume publication contains about 250 high quality papers contributed by authors from over 50 countries. The proceedings present many exciting new findings in the emerging subjects, as well as their applications, such as: data mining, data assimilation, artificial neural networks, fuzzy logic, genetic algorithms and genetic programming, chaos theory and support vector machines, geographic information systems and virtual imaging, decision support and management systems, Internet-based technologies.This book provides an excellent reference to researchers, graduate students, practitioners, and all those interested in the field of hydroinformatics.
Hydroinformatics addresses cross-disciplinary issues ranging from technological and sociological to more general environmental concerns, including an ethical perspective. It covers the application of information technology in the widest sense to problems of the aquatic environment.This two-volume publication contains about 250 high quality papers contributed by authors from over 50 countries. The proceedings present many exciting new findings in the emerging subjects, as well as their applications, such as: data mining, data assimilation, artificial neural networks, fuzzy logic, genetic algorithms and genetic programming, chaos theory and support vector machines, geographic information systems and virtual imaging, decision support and management systems, Internet-based technologies.This book provides an excellent reference to researchers, graduate students, practitioners, and all those interested in the field of hydroinformatics.
Streamflow forecasting is of great importance to water resources management and flood defense. On the other hand, a better understanding of the streamflow process is fundamental for improving the skill of streamflow forecasting. The methods for forecasting streamflows may fall into two general classes: process-driven methods and data-driven methods. Equivalently, methods for understanding streamflow processes may also be broken into two categories: physically-based methods and mathematically-based methods. This thesis focuses on using mathematically-based methods to analyze stochasticity and nonlinearity of streamflow processes based on univariate historic streamflow records, and presents data-driven models that are also mainly based on univariate streamflow time series. Six streamflow processes of five rivers in different geological regions are investigated for stochasticity and nonlinearity at several characteristic timescales.
Water quality and management are of great significance globally, as the demand for clean, potable water far exceeds the availability. Water science research brings together the natural and applied sciences, engineering, chemistry, law and policy, and economics, and the Treatise on Water Science seeks to unite these areas through contributions from a global team of author-experts. The 4-volume set examines topics in depth, with an emphasis on innovative research and technologies for those working in applied areas. Published in partnership with and endorsed by the International Water Association (IWA), demonstrating the authority of the content Editor-in-Chief Peter Wilderer, a Stockholm Water Prize recipient, has assembled a world-class team of volume editors and contributing authors Topics related to water resource management, water quality and supply, and handling of wastewater are treated in depth
This volume reviews the state-of-the-art in conventional coastal modelling as well as the increasingly popular integration of various artificial intelligence technologies into coastal modelling. It examines conventional hydrodynamic and water quality modelling techniques, finite difference and finite element methods, novel and genetic algorithms, knowledge-based systems, artificial neural networks, and fuzzy inference systems. The author discusses soft computing methods that contribute to accurate and reliable prediction of coastal processes and describes how combining these techniques and harnessing their benefits has the potential to make extremely powerful modelling tools.
Like all natural hazards, flooding is a complex and inherently uncertain phenomenon. Despite advances in developing flood forecasting models and techniques, the uncertainty in forecasts remains unavoidable. This uncertainty needs to be acknowledged, and uncertainty estimation in flood forecasting provides a rational basis for risk-based
One of the effects of global climate change is the increasing variability of extreme flood events and cyclones. Current measures to mitigate flood impacts, particularly in the urban environment, are based on previously-planned flood risk intervals and no longer provide sufficient protection. Being prepared for unexpected changes and extreme flood events asks for a paradigm shift in current strategies to avoid and manage flood disasters. In order to stem the increasing impact of urban floods, a major rethink of current planning and flood management policies and practice is required, taking into account different spatial and temporal scales. This book addresses a broad spectrum of relevant issues in the emerging field of urban flood management. It may act as a stimulus for further research and development in urban flood management while informing and engaging stakeholders in the promotion of integrated and cooperative approaches in water management. An interdisciplinary approach which will be of interest to all those who are active in water, risk and urban management.
Written and edited by leading worldwide authorities in the field, and comprising nearly 200 substantial articles, the Encyclopedia provides detailed, informed coverage of the subject.