Neural Networks for Hydrological Modeling

Author: Robert Abrahart
Publisher: CRC Press
ISBN: 9789058096197
Format: PDF
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A new approach to the fast-developing world of neural hydrological modelling, this book is essential reading for academics and researchers in the fields of water sciences, civil engineering, hydrology and physical geography. Each chapter has been written by one or more eminent experts working in various fields of hydrological modelling. The book covers an introduction to the concepts and technology involved, numerous case-studies with practical applications and methods, and finishes with suggestions for future research directions. Wide in scope, this book offers both significant new theoretical challenges and an examination of real-world problem-solving in all areas of hydrological modelling interest.

Artificial Neural Networks in Hydrology

Author: R.S. Govindaraju
Publisher: Springer Science & Business Media
ISBN: 9401593418
Format: PDF, ePub, Mobi
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R. S. GOVINDARAJU and ARAMACHANDRA RAO School of Civil Engineering Purdue University West Lafayette, IN. , USA Background and Motivation The basic notion of artificial neural networks (ANNs), as we understand them today, was perhaps first formalized by McCulloch and Pitts (1943) in their model of an artificial neuron. Research in this field remained somewhat dormant in the early years, perhaps because of the limited capabilities of this method and because there was no clear indication of its potential uses. However, interest in this area picked up momentum in a dramatic fashion with the works of Hopfield (1982) and Rumelhart et al. (1986). Not only did these studies place artificial neural networks on a firmer mathematical footing, but also opened the dOOf to a host of potential applications for this computational tool. Consequently, neural network computing has progressed rapidly along all fronts: theoretical development of different learning algorithms, computing capabilities, and applications to diverse areas from neurophysiology to the stock market. . Initial studies on artificial neural networks were prompted by adesire to have computers mimic human learning. As a result, the jargon associated with the technical literature on this subject is replete with expressions such as excitation and inhibition of neurons, strength of synaptic connections, learning rates, training, and network experience. ANNs have also been referred to as neurocomputers by people who want to preserve this analogy.

Hydrologic Modeling

Author: Vijay P Singh
Publisher: Springer
ISBN: 9811058016
Format: PDF, Docs
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This book contains seven parts. The first part deals with some aspects of rainfall analysis, including rainfall probability distribution, local rainfall interception, and analysis for reservoir release. Part 2 is on evapotranspiration and discusses development of neural network models, errors, and sensitivity. Part 3 focuses on various aspects of urban runoff, including hydrologic impacts, storm water management, and drainage systems. Part 4 deals with soil erosion and sediment, covering mineralogical composition, geostatistical analysis, land use impacts, and land use mapping. Part 5 treats remote sensing and geographic information system (GIS) applications to different hydrologic problems. Watershed runoff and floods are discussed in Part 6, encompassing hydraulic, experimental, and theoretical aspects. Water modeling constitutes the concluding Part 7. Soil and Water Assessment Tool (SWAT), Xinanjiang, and Soil Conservation Service-Curve Number (SCS-CN) models are discussed. The book is of interest to researchers and practitioners in the field of water resources, hydrology, environmental resources, agricultural engineering, watershed management, earth sciences, as well as those engaged in natural resources planning and management. Graduate students and those wishing to conduct further research in water and environment and their development and management find the book to be of value.

Advances in Data based Approaches for Hydrologic Modeling and Forecasting

Author: Bellie Sivakumar
Publisher: World Scientific
ISBN: 9814307971
Format: PDF, ePub, Docs
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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.

Handbook of Engineering Hydrology

Author: Saeid Eslamian
Publisher: CRC Press
ISBN: 1466552476
Format: PDF, ePub, Docs
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While most books examine only the classical aspects of hydrology, this three-volume set covers multiple aspects of hydrology. It examines new approaches, addresses growing concerns about hydrological and ecological connectivity, and considers the worldwide impact of climate change. It also provides updated material on hydrological science and engineering, discussing recent developments as well as classic approaches. Published in three books, Fundamentals and Applications; Modeling, Climate Change, and Variability; and Environmental Hydrology and Water Management, the entire set consists of 87 chapters, and contains 29 chapters in each book. The chapters in this book contain information on: Climate change and hydrological hazards, hydrological modeling, and urban water systems, as well as climate change impacts on hydrology and water resources, climate change uncertainty, vulnerability, and adaption Rainfall estimation and changes, hydrological changes of mangrove ecosystems, impact of the development of vegetation on flow conditions and flood hazards, urbanization impacts on runoff regime, and discretization in urban watersheds Artificial neural network-based modeling of hydrologic processes, flow and sediment transport modeling in rivers, hybrid hydrological modeling, hydrologic modeling: stochastic processes, and time series analysis of hydrologic data Dam risk and uncertainty, drought indices for drought risk assessment in a changing climate, hydrologic prediction and uncertainty quantification, uncertainty and risk of the PMP and PMF Geostatistics applications in hydrology, GIS applications in a changing climate, GIS-based upland erosion mapping, regional flood frequency analysis, regionalization of hydrological extreme events, remote sensing data and information for hydrological monitoring and modeling Application of copulas in hydrology, bankfull frequency of rivers, statistical parameters used for assessing hydrological regime, significance of statistical tests and persistence in hydrologic processes Students, practitioners, policy makers, consultants and researchers can benefit from the use of this text.

Practical Hydroinformatics

Author: Robert J. Abrahart
Publisher: Springer Science & Business Media
ISBN: 3540798811
Format: PDF
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Hydroinformatics is an emerging subject that is expected to gather speed, momentum and critical mass throughout the forthcoming decades of the 21st century. This book provides a broad account of numerous advances in that field - a rapidly developing discipline covering the application of information and communication technologies, modelling and computational intelligence in aquatic environments. A systematic survey, classified according to the methods used (neural networks, fuzzy logic and evolutionary optimization, in particular) is offered, together with illustrated practical applications for solving various water-related issues. ...

Hydrological Modelling and the Water Cycle

Author: Soroosh Sorooshian
Publisher: Springer Science & Business Media
ISBN: 3540778438
Format: PDF, Kindle
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This volume is a collection of a selected number of articles based on presentations at the 2005 L’Aquila (Italy) Summer School on the topic of “Hydrologic Modeling and Water Cycle: Coupling of the Atmosphere and Hydrological Models”. The p- mary focus of this volume is on hydrologic modeling and their data requirements, especially precipitation. As the eld of hydrologic modeling is experiencing rapid development and transition to application of distributed models, many challenges including overcoming the requirements of compatible observations of inputs and outputs must be addressed. A number of papers address the recent advances in the State-of-the-art distributed precipitation estimation from satellites. A number of articles address the issues related to the data merging and use of geo-statistical techniques for addressing data limitations at spatial resolutions to capture the h- erogeneity of physical processes. The participants at the School came from diverse backgrounds and the level of - terest and active involvement in the discussions clearly demonstrated the importance the scienti c community places on challenges related to the coupling of atmospheric and hydrologic models. Along with my colleagues Dr. Erika Coppola and Dr. Kuolin Hsu, co-directors of the School, we greatly appreciate the invited lectures and all the participants. The members of the local organizing committee, Drs Barbara Tomassetti; Marco Verdecchia and Guido Visconti were instrumental in the success of the school and their contributions, both scienti cally and organizationally are much appreciated.

Hydrological Data Driven Modelling

Author: Renji Remesan
Publisher: Springer
ISBN: 3319092359
Format: PDF, Kindle
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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.

Environmental and Hydrological Systems Modelling

Author: A W Jayawardena
Publisher: CRC Press
ISBN: 041546532X
Format: PDF, ePub
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Mathematical modelling has become an indispensable tool for engineers, scientists, planners, decision makers and many other professionals to make predictions of future scenarios as well as real impending events. As the modelling approach and the model to be used are problem specific, no single model or approach can be used to solve all problems, and there are constraints in each situation. Modellers therefore need to have a choice when confronted with constraints such as lack of sufficient data, resources, expertise and time. Environmental and Hydrological Systems Modelling provides the tools needed by presenting different approaches to modelling the water environment over a range of spatial and temporal scales. Their applications are shown with a series of case studies, taken mainly from the Asia-Pacific Region. Coverage includes: Population dynamics Reaction kinetics Water quality systems Longitudinal dispersion Time series analysis and forecasting Artificial neural networks Fractals and chaos Dynamical systems Support vector machines Fuzzy logic systems Genetic algorithms and genetic programming This book will be of great value to advanced students, professionals, academics and researchers working in the water environment.

Hydrological Modelling in Arid and Semi Arid Areas

Author: Howard Wheater
Publisher: Cambridge University Press
ISBN: 1139468081
Format: PDF, Kindle
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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.