35 leading multi-disciplinary scientists with international reputations provide reviews of topical areas of research on uncertainty and reliability related aspects of water resource systems. The volume will be valuable for graduate students, scientists, consultants, administrators, and practising hydrologists and water managers.

In Risk, Reliability, Uncertainty and Robustness of Water Resources Systems, thirty-five leading scientists provide state-of-the-art reviews of topical areas of research on water resources systems, including aspects of extreme hydrological events: floods and droughts, water quantity and quality, dams, reservoirs and hydraulic structures, evaluating sustainability and climate change impacts. As well as discussing essential challenges and research directions, the book will assist in applying theoretical methods to the solution of practical problems in water resources.

Although many theoretical developments have been achieved in recent years, the progress both in understanding and application of risk and reliability analysis in water resources and environmental engineering remains slow. One of the reasons seems to be the lack of training of engineers with phenomena of statistical nature, including optimum cost and benefit decisions under uncertainty. This book presents, in a unified and comprehensive framework, the various aspects of risk and reliability in bothwater quantity and quality problems. The topics covered include uncertainty analysis of water quantity and quality data, stochastic simulation of hydrosystems, decision theory under uncertaintyand case studies. Methods for risk analysis of extremes in hydrology, groundwater clean-up, river and coastal pollution as well as total risk management are presented.

Confronting Climate Uncertainty in Water Resources Planning and Project Design describes an approach to facing two fundamental and unavoidable issues brought about by climate change uncertainty in water resources planning and project design. The first is a risk assessment problem. The second relates to risk management. This book provides background on the risks relevant in water systems planning, the different approaches to scenario definition in water system planning, and an introduction to the decision-scaling methodology upon which the decision tree is based. The decision tree is described as a scientifically defensible, repeatable, direct and clear method for demonstrating the robustness of a project to climate change. While applicable to all water resources projects, it allocates effort to projects in a way that is consistent with their potential sensitivity to climate risk. The process was designed to be hierarchical, with different stages or phases of analysis triggered based on the findings of the previous phase. An application example is provided followed by a descriptions of some of the tools available for decision making under uncertainty and methods available for climate risk management. The tool was designed for the World Bank but can be applicable in other scenarios where similar challenges arise.

With the expansion of new technologies, materials, and the design of complex systems, the expectations of society upon engineers are becoming larger than ever. Engineers make critical decisions with potentially high adverse consequences. The current political, societal, and financial climate requires engineers to formally consider the factors of uncertainty (e.g., floods, earthquakes, winds, environmental risks) in their decisions at all levels. Uncertainty Modeling and Analysis in Civil Engineering provides a thorough report on the immediate state of uncertainty modeling and analytical methods for civil engineering systems, presenting a toolbox for solving problems in real-world situations. Topics include Neural networks Genetic algorithms Numerical modeling Fuzzy sets and operations Reliability and risk analysis Systems control Uncertainty in probability estimates This compendium is a considerable reference for civil engineers as well as for engineers in other disciplines, computer scientists, general scientists, and students.