This textbook is a practical guide to real-time streamflow forecasting that provides a rigorous description of a coupled stochastic and physically based flow routing method and its practical applications. This method is used in current times of record-breaking floods to forecast flood levels by various hydrological forecasting services. By knowing

Advances in Streamflow Forecasting: From Traditional to Modern Approaches covers the three major data-driven approaches of streamflow forecasting including traditional approach of statistical and stochastic time-series modelling with their recent developments, stand-alone data-driven approach such as artificial intelligence techniques, and modern hybridized approach where data-driven models are combined with preprocessing methods to improve the forecast accuracy of streamflows and to reduce the forecast uncertainties. This book starts by providing the background information, overview, and advances made in streamflow forecasting. The overview portrays the progress made in the field of streamflow forecasting over the decades. Thereafter, chapters describe theoretical methodology of the different data-driven tools and techniques used for streamflow forecasting along with case studies from different parts of the world. Each chapter provides a flowchart explaining step-by-step methodology followed in applying the data-driven approach in streamflow forecasting. This book addresses challenges in forecasting streamflows by abridging the gaps between theory and practice through amalgamation of theoretical descriptions of the data-driven techniques and systematic demonstration of procedures used in applying the techniques. Language of this book is kept simple to make the readers understand easily about different techniques and make them capable enough to straightforward replicate the approach in other areas of their interest. This book will be vital for hydrologists when optimizing the water resources system, and to mitigate the impact of destructive natural disasters such as floods and droughts by implementing long-term planning (structural and nonstructural measures), and short-term emergency warning. Moreover, this book will guide the readers in choosing an appropriate technique for streamflow forecasting depending upon the given set of conditions. - Contributions from renowned researchers/experts of the subject from all over the world to provide the most authoritative outlook on streamflow forecasting - Provides an excellent overview and advances made in streamflow forecasting over the past more than five decades and covers both traditional and modern data-driven approaches in streamflow forecasting - Includes case studies along with detailed flowcharts demonstrating a systematic application of different data-driven models in streamflow forecasting, which helps understand the step-by-step procedures

Fourth international conference on FRIEND, Cape Town, March 2002.

In recent years, the continued technological advances have led to the spread of low-cost sensors and devices supporting crowdsourcing as a way to obtain observations of hydrological variables in a more distributed way than the classic static physical sensors. The main advantage of using these type of sensors is that they can be used not only by technicians but also by regular citizens. However, due to their relatively low reliability and varying accuracy in time and space, crowdsourced observations have not been widely integrated in hydrological and/or hydraulic models for flood forecasting applications. Instead, they have generally been used to validate model results against observations, in post-event analyses. This research aims to investigate the benefits of assimilating the crowdsourced observations, coming from a distributed network of heterogeneous physical and social (static and dynamic) sensors, within hydrological and hydraulic models, in order to improve flood forecasting. The results of this study demonstrate that crowdsourced observations can significantly improve flood prediction if properly integrated in hydrological and hydraulic models. This study provides technological support to citizen observatories of water, in which citizens not only can play an active role in information capturing, evaluation and communication, leading to improved model forecasts and better flood management.

Advances in computer technology, in the technology of communication and in mathematical modelling of processes in the hydrological cycle have recently improved our potential to protect ourselves against damage through floods and droughts and to control quantities and qualities in our water systems. This development was demonstrated in a 1983 post-experience course at Wageningen University where an international group of experts reviewed successful modelling techniques and described the design and operation of a number of forecasting and control systems in drainage basins and river reaches of various sizes and under various geographical and climat ological conditions. A special effort was made to bridge the gap between theory and practice; case studies showed that each forecasting system was designed to meet a set of specific requirements and they illustrated that the forecasting system can only be expected to operate reliably if, on the one hand, it is based on sound theoretical concepts and methods and if, on the other hand, it is robust so that, also under adverse conditions, it will continue to collect and process the necessary input data and produce correct and timely signals. We were pleased to meet with encouragement for preserving the course material and making it available to a wider public. This was effected by the team of authorf who elaborated, updated and harmonized the materia in two stages; first into an issue of our university department and finally into the manuscript of this book.

Arid and semi-arid regions are defined as areas where water is at its most scarce. The hydrological regime in these areas is extreme and highly variable, and they face great pressures to deliver and manage freshwater resources. However, there is no guidance on the decision support tools that are needed to underpin flood and water resource management in arid areas. UNESCO initiated the Global network for Water and Development Information for arid lands (GWADI), and arranged a workshop of the world's leading experts to discuss these issues. This book presents chapters from contributors to the workshop, and includes case studies from the world's major arid regions to demonstrate model applications, and web links to tutorials and state-of-the-art modelling software. This volume is a valuable reference for researchers and engineers working on the water resources of arid and semi-arid regions.

This volume contains 27 papers, written by time series analysts, dealing with statistical theory, methodology and applications. The emphasis is on the recent developments in the analysis of linear, onlinear (non-Gaussian), stationary and nonstationary time series. The topics include cointegration, estimation and asymptotic theory, Kalman filtering, nonparametric statistical inference, long memory models, nonlinear models, spectral analysis of stationary and nonstationary processes. Quite a number of papers are devoted to modelling and analysis of real time series, and the econometricians, mathematical statisticians, communications engineers and scientists who use time series techniques and Fourier analysis should find the papers in this volume useful.