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 criteria. This book presents the development and applications of various methods based on probablity and fuzzy set theories for modelling uncertainty in flood forecasting systems. In particular, it presents a methodology for uncertainty assessment using disaggregation of time series inputs in the framework of both the Monte Carlo method and the Fuzzy Extention Principle. It reports an improvement in the First Order Second Moment method, using second degree reconstruction, and derives qualitative scales for the interpretation of qualitative uncertainty. Application is to flood forecasting models for the Klodzko catchment in POland and the Loire River in France. Prospects for the hybrid techniques of uncertainty modelling and probability-possibility transformations are also explored and reported.

Catchment Hydrological Modelling: The Science and Art covers various methods (and equations) for modeling all components of a CHM. Readers are presented with multiple methods and approaches to modeling the same component, allowing them to distinguish the differences between methods. The books also provides a clear understanding of what makes some commonly used hydrological models similar or different and what their strengths and weaknesses may be. This comprehensive guide contains questions and answers in each chapter, along with concepts and detailed equations that are fundamental to understanding CHM. This book is useful to students and professionals in the fields of catchment and hydrology, as well as environmental and civil engineers.

A hydroinformatics system represents an electronic knowledge encapsulator that models part of the real world and can be used for the simulation and analysis of physical, chemical and biological processes in water systems, in order to achieve a better management of the aquatic environment. Thus, modelling is at the heart of hydroinformatics. The theory of nonlinear dynamics and chaos, and the extent to which recent improvements in the understanding of inherently nonlinear natural processes present challenges to the use of mathematical models in the analysis of water and environmental systems, are elaborated in this work. In particular, it demonstrates that the deterministic chaos present in many nonlinear systems can impose fundamental limitations on our ability to predict behaviour, even when well-defined mathematical models exist. On the other hand, methodologies and tools from the theory of nonlinear dynamics and chaos can provide means for a better accuracy of short-term predictions as demonstrated through the practical applications in this work.