Hydrological Processes Modelling And Data Analysis

This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space.

Hydrology: An Advanced Introduction to Hydrological Processes and Modelling introduces the reader to hydrological processes and methods of estimation of the various quantities involved. Topics covered range from elements of meteorology to precipitation, evaporation and transpiration, interception, and flood routing. Extreme events, design flood, and small catchment runoff are also discussed. This book is comprised of 12 chapters and begins with an overview of hydrology and the hydrologic cycle, along with the world's water resources and their utilization and management. Subsequent chapters deal with atmospheric thermodynamics and atmospheric circulation; analysis and measurement of precipitation, evaporation, transpiration, and interception; infiltration of groundwater; and reservoir and stream routing. Storage for flood control and regulation for abatement of water shortage are also considered, along with stratification and siltation of reservoirs, catchment yield, and sediment yield and transport. The final chapter highlights the importance of information analysis and decision making in hydrological work. This monograph is written for senior and postgraduate students and should also be of value to practitioners of physics, mathematics, and civil engineering.

This book comprehensively accounts the advances in data-based approaches for hydrologic modeling and forecasting. Eight major and most popular approaches are selected, with a chapter for each stochastic methods, parameter estimation techniques, scaling and fractal methods, remote sensing, artificial neural networks, evolutionary computing, wavelets, and nonlinear dynamics and chaos methods. These approaches are chosen to address a wide range of hydrologic system characteristics, processes, and the associated problems. Each of these eight approaches includes a comprehensive review of the fundamental concepts, their applications in hydrology, and a discussion on potential future directions.

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Understand the fundamentals, methods, and processes of modern hydrology This comprehensive engineering textbook offers a thorough overview of all aspects of hydrology and shows how to apply hydrologic principles for effective management of water resources. It presents detailed explanations of scientific principles along with real-world applications and technologies. Engineering Hydrology: An Introduction to Processes, Analysis, and Modeling follows a logical progression that builds on foundational concepts with modern hydrologic methods. Every hydrologic process is clearly explained along with current techniques for modeling and analyzing data. You will get practice problems throughout that help reinforce important concepts. Coverage includes: •The hydrologic cycle •Water balance •Components of the hydrologic cycle •Evapotranspiration •Infiltration and soil moisture •Surface water •Groundwater •Water quality •Hydrologic measurements •Streamflow measurement •Remote sensing and geographic information systems •Hydrologic analysis and modeling •Unit hydrograph models •River flow modeling •Design storm and design flood estimation •Environmental flows •Impact of climate change on water management

This book provides a compilation of statistical analysis methods used to analyze and assess critical variables in the hydrological cycle.

Hydrological extremes have become a major concern because of their devastating consequences and their increased risk as a result of climate change and the growing concentration of people and infrastructure in high-risk zones. The analysis of hydrological extremes is challenging due to their rarity and small sample size, and the interconnections between different types of extremes and becomes further complicated by the untrustworthy representation of meso-scale processes involved in extreme events by coarse spatial and temporal scale models as well as biased or missing observations due to technical difficulties during extreme conditions. The complexity of analyzing hydrological extremes calls for robust statistical methods for the treatment of such events. This Special Issue is motivated by the need to apply and develop innovative stochastic and statistical approaches to analyze hydrological extremes under current and future climate conditions. The papers of this Special Issue focus on six topics associated with hydrological extremes: Historical changes in hydrological extremes; Projected changes in hydrological extremes; Downscaling of hydrological extremes; Early warning and forecasting systems for drought and flood; Interconnections of hydrological extremes; Applicability of satellite data for hydrological studies.