Advances in Streamflow Forecasting

Advances in Streamflow Forecasting PDF

Author: Priyanka Sharma

Publisher: Elsevier

Published: 2021-06-20

Total Pages: 404

ISBN-13: 0128209240

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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

Advances in Hydrologic Forecasts and Water Resources Management

Advances in Hydrologic Forecasts and Water Resources Management PDF

Author: Fi-John Chang

Publisher: MDPI

Published: 2021-01-20

Total Pages: 274

ISBN-13: 3039368044

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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.

Hydrologic Sciences

Hydrologic Sciences PDF

Author: National Research Council

Publisher: National Academies Press

Published: 1998-11-11

Total Pages: 148

ISBN-13: 0309174074

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Hydrologic science, an important, interdisciplinary science dealing with the occurrence, distribution, and properties of water on Earth, is key to understanding and resolving many contemporary, large-scale environmental issues. The Water Science and Technology Board used the opportunity of its 1997 Abel Wolman Distinguished Lecture to assess the vitality of the hydrologic sciences by the hydrologic community. The format included focus by lecturer Thomas Dunne on the intellectual vitality of the hydrologic sciences, followed by a symposium featuring several invited papers and discussions. Hydrologic Sciences is a compilation of the Wolman Lecture and the papers, preceded by a summarizing overview. The volume stresses a number of needs for furtherance of hydrologic science, including development of a coherent body of transferable theory and an intellectual center for the science, communication across multiple geo- and environmental science disciplines, appropriate measurements and observations, and provision of central guidance for the field.

Recursive Streamflow Forecasting

Recursive Streamflow Forecasting PDF

Author: Jozsef Szilagyi

Publisher: CRC Press

Published: 2017-06-29

Total Pages: 212

ISBN-13: 0203841441

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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

Flood Forecasting Using Machine Learning Methods

Flood Forecasting Using Machine Learning Methods PDF

Author: Fi-John Chang

Publisher: MDPI

Published: 2019-02-28

Total Pages: 376

ISBN-13: 3038975486

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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.

Stochasticity, Nonlinearity and Forecasting of Streamflow Processes

Stochasticity, Nonlinearity and Forecasting of Streamflow Processes PDF

Author: Wen Wang

Publisher: IOS Press

Published: 2006

Total Pages: 220

ISBN-13: 9781586036218

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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.

Advances in Data-based Approaches for Hydrologic Modeling and Forecasting

Advances in Data-based Approaches for Hydrologic Modeling and Forecasting PDF

Author: Bellie Sivakumar

Publisher: World Scientific

Published: 2010

Total Pages: 542

ISBN-13: 9814307971

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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.

Assessing the National Streamflow Information Program

Assessing the National Streamflow Information Program PDF

Author: National Research Council

Publisher: National Academies Press

Published: 2004-08-19

Total Pages: 176

ISBN-13: 0309166241

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From warning the public of impending floods to settling legal arguments over water rights, the measurement of streamflow ("streamgaging") plays a vital role in our society. Having good information about how much water is moving through our streams helps provide citizens with drinking water during droughts, control water pollution, and protect wildlife along our stream corridors. The U.S. Geological Survey's (USGS) streamgaging program provides such information to a wide variety of users interested in human safety, recreation, water quality, habitat, industry, agriculture, and other topics. For regional and national scale streamflow information needs, the USGS has created a National Streamflow Information Program (NSIP). In addition to streamgaging, the USGS envisions intensive data collection during floods and droughts, national assessments of streamflow characteristics, enhanced information delivery, and methods development and research. The overall goals of the program are to: meet legal and treaty obligations on interstate and international waters, support flow forecasting; measure river basin outflows, monitor sentinel watersheds for long-term trends in natural flows, and measure flows for water quality needs. But are these the right topics to collect data on? Or is the USGS on the wrong track? In general, the book is supportive of the design and content of NSIP, including its goals and methodology for choosing stream gages for inclusion in the program. It sees the ultimate goal of NSIP as developing the ability to use existing data-gathering sites to generate streamflow information with quantitative confidence limits at any location in the nation. It is just as important to have good measurements during droughts as during floods, and it therefore recommends supporting Natural Resource Conservation Service forecast sites in addition to those of the National Weather Service.

Next Generation Earth System Prediction

Next Generation Earth System Prediction PDF

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2016-08-22

Total Pages: 351

ISBN-13: 0309388805

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As the nation's economic activities, security concerns, and stewardship of natural resources become increasingly complex and globally interrelated, they become ever more sensitive to adverse impacts from weather, climate, and other natural phenomena. For several decades, forecasts with lead times of a few days for weather and other environmental phenomena have yielded valuable information to improve decision-making across all sectors of society. Developing the capability to forecast environmental conditions and disruptive events several weeks and months in advance could dramatically increase the value and benefit of environmental predictions, saving lives, protecting property, increasing economic vitality, protecting the environment, and informing policy choices. Over the past decade, the ability to forecast weather and climate conditions on subseasonal to seasonal (S2S) timescales, i.e., two to fifty-two weeks in advance, has improved substantially. Although significant progress has been made, much work remains to make S2S predictions skillful enough, as well as optimally tailored and communicated, to enable widespread use. Next Generation Earth System Predictions presents a ten-year U.S. research agenda that increases the nation's S2S research and modeling capability, advances S2S forecasting, and aids in decision making at medium and extended lead times.