Applied Modeling of Hydrologic Time Series
Author | : Jose D. Salas |
Publisher | : Water Resources Publication |
Total Pages | : 502 |
Release | : 1980 |
Genre | : Science |
ISBN | : 9780918334374 |
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Author | : Jose D. Salas |
Publisher | : Water Resources Publication |
Total Pages | : 502 |
Release | : 1980 |
Genre | : Science |
ISBN | : 9780918334374 |
Author | : Deepesh Machiwal |
Publisher | : Springer Science & Business Media |
Total Pages | : 316 |
Release | : 2012-03-05 |
Genre | : Science |
ISBN | : 9400718616 |
There is a dearth of relevant books dealing with both theory and application of time series analysis techniques, particularly in the field of water resources engineering. Therefore, many hydrologists and hydrogeologists face difficulties in adopting time series analysis as one of the tools for their research. This book fills this gap by providing a proper blend of theoretical and practical aspects of time sereies analysis. It deals with a comprehensive overview of time series characteristics in hydrology/water resources engineering, various tools and techniques for analyzing time series data, theoretical details of 31 available statistical tests along with detailed procedures for applying them to real-world time series data, theory and methodology of stochastic modelling, and current status of time series analysis in hydrological sciences. In adition, it demonstrates the application of most time series tests through a case study as well as presents a comparative performance evaluation of various time series tests, together with four invited case studies from India and abroad. This book will not only serve as a textbook for the students and teachers in water resources engineering but will also serve as the most comprehensive reference to educate researchers/scientists about the theory and practice of time series analysis in hydrological sciences. This book will be very useful to the students, researchers, teachers and professionals involved in water resources, hydrology, ecology, climate change, earth science, and environmental studies.
Author | : Deepesh Machiwal |
Publisher | : Springer |
Total Pages | : 280 |
Release | : 2011-12-23 |
Genre | : Science |
ISBN | : 9789400718609 |
There is a dearth of relevant books dealing with both theory and application of time series analysis techniques, particularly in the field of water resources engineering. Therefore, many hydrologists and hydrogeologists face difficulties in adopting time series analysis as one of the tools for their research. This book fills this gap by providing a proper blend of theoretical and practical aspects of time sereies analysis. It deals with a comprehensive overview of time series characteristics in hydrology/water resources engineering, various tools and techniques for analyzing time series data, theoretical details of 31 available statistical tests along with detailed procedures for applying them to real-world time series data, theory and methodology of stochastic modelling, and current status of time series analysis in hydrological sciences. In adition, it demonstrates the application of most time series tests through a case study as well as presents a comparative performance evaluation of various time series tests, together with four invited case studies from India and abroad. This book will not only serve as a textbook for the students and teachers in water resources engineering but will also serve as the most comprehensive reference to educate researchers/scientists about the theory and practice of time series analysis in hydrological sciences. This book will be very useful to the students, researchers, teachers and professionals involved in water resources, hydrology, ecology, climate change, earth science, and environmental studies.
Author | : K.W. Hipel |
Publisher | : Elsevier |
Total Pages | : 1053 |
Release | : 1994-04-07 |
Genre | : Technology & Engineering |
ISBN | : 0080870368 |
This is a comprehensive presentation of the theory and practice of time series modelling of environmental systems. A variety of time series models are explained and illustrated, including ARMA (autoregressive-moving average), nonstationary, long memory, three families of seasonal, multiple input-single output, intervention and multivariate ARMA models. Other topics in environmetrics covered in this book include time series analysis in decision making, estimating missing observations, simulation, the Hurst phenomenon, forecasting experiments and causality. Professionals working in fields overlapping with environmetrics - such as water resources engineers, environmental scientists, hydrologists, geophysicists, geographers, earth scientists and planners - will find this book a valuable resource. Equally, environmetrics, systems scientists, economists, mechanical engineers, chemical engineers, and management scientists will find the time series methods presented in this book useful.
Author | : N. T Kottegoda |
Publisher | : Springer |
Total Pages | : 384 |
Release | : 1980-06-18 |
Genre | : Mathematics |
ISBN | : 1349034673 |
Author | : Ramesh S. V. Teegavarapu |
Publisher | : |
Total Pages | : 1022 |
Release | : 2019 |
Genre | : Groundwater flow |
ISBN | : 9780784415177 |
This book provides a compilation of statistical analysis methods used to analyze and assess critical variables in the hydrological cycle.
Author | : A.R. Rao |
Publisher | : Springer Science & Business Media |
Total Pages | : 251 |
Release | : 2008-01-08 |
Genre | : Science |
ISBN | : 1402064543 |
The Hilbert-Huang Transform (HHT) is a recently developed technique used to analyze nonstationary data. This book uses methods based on the Hilbert-Huang Transform to analyze hydrological and environmental time series. These results are compared to the results from the traditional methods such as those based on Fourier transform and other classical statistical tests.
Author | : Keith W. Hipel |
Publisher | : Springer Science & Business Media |
Total Pages | : 469 |
Release | : 2013-04-17 |
Genre | : Science |
ISBN | : 9401730830 |
International experts from around the globe present a rich variety of intriguing developments in time series analysis in hydrology and environmental engineering. Climatic change is of great concern to everyone and significant contributions to this challenging research topic are put forward by internationally renowned authors. A range of interesting applications in hydrological forecasting are given for case studies in reservoir operation in North America, Asia and South America. Additionally, progress in entropy research is described and entropy concepts are applied to various water resource systems problems. Neural networks are employed for forecasting runoff and water demand. Moreover, graphical, nonparametric and parametric trend analyses methods are compared and applied to water quality time series. Other topics covered in this landmark volume include spatial analyses, spectral analyses and different methods for stream-flow modelling. Audience The book constitutes an invaluable resource for researchers, teachers, students and practitioners who wish to be at the forefront of time series analysis in the environmental sciences.
Author | : Renji Remesan |
Publisher | : Springer |
Total Pages | : 261 |
Release | : 2014-11-03 |
Genre | : Science |
ISBN | : 3319092359 |
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.