Advances In Streamflow Forecasting
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Advances In Streamflow Forecasting
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Author : Priyanka Sharma
language : en
Publisher: Elsevier
Release Date : 2021-06-20
Advances In Streamflow Forecasting written by Priyanka Sharma and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-20 with Science categories.
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
Recursive Streamflow Forecasting
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Author : Jozsef Szilagyi
language : en
Publisher: CRC Press
Release Date : 2017-06-29
Recursive Streamflow Forecasting written by Jozsef Szilagyi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-29 with Technology & Engineering categories.
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 Hydrologic Forecasts And Water Resources Management
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Author : Fi-John Chang
language : en
Publisher: MDPI
Release Date : 2021-01-20
Advances In Hydrologic Forecasts And Water Resources Management written by Fi-John Chang and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-20 with Technology & Engineering categories.
The impacts of climate change on water resource management, as well as increasingly severe natural disasters over the last decades, have caught global attention. Reliable and accurate hydrological forecasts are essential for efficient water resource management and the mitigation of natural disasters. While the notorious nonlinear hydrological processes make accurate forecasts a very challenging task, it requires advanced techniques to build accurate forecast models and reliable management systems. One of the newest techniques for modeling complex systems is artificial intelligence (AI). AI can replicate the way humans learn and has great capability to efficiently extract crucial information from large amounts of data to solve complex problems. The fourteen research papers published in this Special Issue contribute significantly to the uncertainty assessment of operational hydrologic forecasting under changing environmental conditions and the promotion of water resources management by using the latest advanced techniques, such as AI techniques. The fourteen contributions across four major research areas: (1) machine learning approaches to hydrologic forecasting; (2) uncertainty analysis and assessment on hydrological modeling under changing environments; (3) AI techniques for optimizing multi-objective reservoir operation; (4) adaption strategies of extreme hydrological events for hazard mitigation. The papers published in this issue will not only advance water sciences but also help policymakers to achieve more sustainable and effective water resource management.
Advances In Data Based Approaches For Hydrologic Modeling And Forecasting
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Author :
language : en
Publisher:
Release Date :
Advances In Data Based Approaches For Hydrologic Modeling And Forecasting written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Advances In Data Based Approaches For Hydrologic Modeling And Forecasting
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Author : Bellie Sivakumar
language : en
Publisher: World Scientific
Release Date : 2010
Advances In Data Based Approaches For Hydrologic Modeling And Forecasting written by Bellie Sivakumar and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Science categories.
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.
Stochasticity Nonlinearity And Forecasting Of Streamflow Processes
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Author : Wen Wang
language : en
Publisher: IOS Press
Release Date : 2006
Stochasticity Nonlinearity And Forecasting Of Streamflow Processes written by Wen Wang and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computers categories.
Streamflow forecasting is of great importance to water resources management and flood defense. On the other hand, a better understanding of the streamflow process is fundamental for improving the skill of streamflow forecasting. The methods for forecasting streamflows may fall into two general classes: process-driven methods and data-driven methods. Equivalently, methods for understanding streamflow processes may also be broken into two categories: physically-based methods and mathematically-based methods. This thesis focuses on using mathematically-based methods to analyze stochasticity and nonlinearity of streamflow processes based on univariate historic streamflow records, and presents data-driven models that are also mainly based on univariate streamflow time series. Six streamflow processes of five rivers in different geological regions are investigated for stochasticity and nonlinearity at several characteristic timescales.
Recursive Streamflow Forecasting
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Author : Jozsef Szilagyi
language : en
Publisher: CRC Press
Release Date : 2017-06-29
Recursive Streamflow Forecasting written by Jozsef Szilagyi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-29 with categories.
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 in advance when, where, and at what level a river will crest, appropriate protection works can be organized, reducing casualties and property damage. Through its real-life case examples and problem listings, the book teaches hydrology and civil engineering students and water-resources practitioners the physical forecasting model and allows them to apply it directly in real-life problems of streamflow simulation and forecasting. Designed as a textbook for courses on hydroinformatics and water management, it includes exercises and a CD-ROM with MATLAB codes for the simulation of streamflows and the creation of real-time hydrological forecasts.
Toward A New Advanced Hydrologic Prediction Service Ahps
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2006-06-28
Toward A New Advanced Hydrologic Prediction Service Ahps written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06-28 with Science categories.
The National Weather Service (NWS) is responsible for providing flood forecasts and warnings in the United States. The agency established the Advanced Hydrologic Prediction Services (AHPS) program in 1997 to advance technology for hydrologic services, specifically to provide accurate forecasts that support timely warnings for all users of hydrologic predictions. AHPS strives to provide information at the right time to facilitate adequate responses to mitigate damages to life, livelihoods, and property. AHPS is slated to be fully implemented nationwide in 2013. With seven years still remaining in its development and implementation timeline, a review of the program now is critical to providing NWS with information it needs to maximize the effectiveness of the AHPS program. This report assesses AHPS in respect to hydrologic science and technology research, river routing and mechanics, "systems" engineering aspects, and implementation. Overall, this report finds AHPS to be an ambitious program that promises to provide services and products that are timely and necessary. The report calls for AHPS to develop a detailed and comprehensive, multi-year implementation plan and for the program's goals and budget to be brought into closer alignment.
Flood Forecasting Using Machine Learning Methods
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Author : Fi-John Chang
language : en
Publisher: MDPI
Release Date : 2019-02-28
Flood Forecasting Using Machine Learning Methods written by Fi-John Chang and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-28 with Technology & Engineering categories.
Nowadays, the degree and scale of flood hazards has been massively increasing as a result of the changing climate, and large-scale floods jeopardize lives and properties, causing great economic losses, in the inundation-prone areas of the world. Early flood warning systems are promising countermeasures against flood hazards and losses. A collaborative assessment according to multiple disciplines, comprising hydrology, remote sensing, and meteorology, of the magnitude and impacts of flood hazards on inundation areas significantly contributes to model the integrity and precision of flood forecasting. Methodologically oriented countermeasures against flood hazards may involve the forecasting of reservoir inflows, river flows, tropical cyclone tracks, and flooding at different lead times and/or scales. Analyses of impacts, risks, uncertainty, resilience, and scenarios coupled with policy-oriented suggestions will give information for flood hazard mitigation. Emerging advances in computing technologies coupled with big-data mining have boosted data-driven applications, among which Machine Learning technology, with its flexibility and scalability in pattern extraction, has modernized not only scientific thinking but also predictive applications. This book explores recent Machine Learning advances on flood forecast and management in a timely manner and presents interdisciplinary approaches to modelling the complexity of flood hazards-related issues, with contributions to integrative solutions from a local, regional or global perspective.
River Flow Modelling And Forecasting
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Author : D.A. Kraijenhoff
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
River Flow Modelling And Forecasting written by D.A. Kraijenhoff and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
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.