Applications Of Machine Learning In Hydroclimatology

Author : Roshan Karan Srivastav
Publisher : Springer
ISBN 13 : 9783031644023
Total Pages : 0 pages
Book Rating : 4.26/5 ( download)

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Download or read book Applications of Machine Learning in Hydroclimatology written by Roshan Karan Srivastav and published by Springer. This book was released on 2024-10-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications of Machine Learning in Hydroclimatology is a comprehensive exploration of the transformative potential of machine learning for addressing critical challenges in water resources management. The book explores how artificial intelligence can unravel the complexities of hydrological systems, providing researchers and practitioners with cutting-edge tools to model, predict, and manage these systems with greater precision and effectiveness. It thoroughly examines the modeling of hydrometeorological extremes, such as floods and droughts, which are becoming increasingly difficult to predict due to climate change. By leveraging AI-driven methods to forecast these extremes, the book offers innovative approaches that enhance predictive accuracy. It emphasizes the importance of analyzing non-stationarity and uncertainty in a rapidly evolving climate landscape, illustrating how statistical and frequency analyses can improve hydrological forecasts. Moreover, the book explores the impact of climate change on flood risks, drought occurrences, and reservoir operations, providing insights into how these phenomena affect water resource management. To provide practical solutions, the book includes case studies that showcase effective mitigation measures for water-related challenges. These examples highlight the use of machine learning techniques such as deep learning, reinforcement learning, and statistical downscaling in real-world scenarios. They demonstrate how artificial intelligence can optimize decision-making and resource management while improving our understanding of complex hydrological phenomena. By utilizing machine learning architectures tailored to hydrology, the book presents physics-guided models, data-driven techniques, and hybrid approaches that can be used to address water management issues. Ultimately, Applications of Machine Learning in Hydroclimatology empowers researchers, practitioners, and policymakers to harness machine learning for sustainable water management. It bridges the gap between advanced AI technologies and hydrological science, offering innovative solutions to tackle today's most pressing challenges in water resources.

Author : Chaopeng Shen
Publisher : Frontiers Media SA
ISBN 13 : 2889669823
Total Pages : 163 pages
Book Rating : 4.20/5 ( download)

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Download or read book Broadening the Use of Machine Learning in Hydrology written by Chaopeng Shen and published by Frontiers Media SA. This book was released on 2021-07-08 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Ajin R.S
Publisher : Elsevier
ISBN 13 : 9780443189630
Total Pages : 0 pages
Book Rating : 4.33/5 ( download)

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Download or read book Machine Learning for the Management of Water Resources and Hydro-Climatological Disasters written by Ajin R.S and published by Elsevier. This book was released on 2023-10-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning for the Management of Water Resources and Hydro-climatological Disasters is divided into three sections: surface water resources management, groundwater resources management, and hydro-climatological disaster management. The rapid increase in the population, unscientific development practices, overexploitation, waste discharge from households and industries, and other factors are endangering surface and groundwater resources. The main threats to water resources are contamination, depletion of water levels and quality, sea water intrusion, growth of algal blooms, etc. The first two sections of this book address the majority of these problems. The major hydro-climatological disasters which pose a threat to communities include flooding (riverine floods, flash floods, coastal floods, glacial lake outburst floods, etc.), drought or water scarcity, rainfall induced landslides, snow avalanches, sea level rise and coastal erosion. The demarcation of hazard or susceptible zones, inundation zones, and assessment of damage are equally important in the effective management of disasters. The third section of this book covers most of these disasters and its management.This book enables researchers and students to get an insight on the machine learning (ML) and deep learning (DL) methods, and its applications. A comprehensive description and application of ML and DL methods to all the major aspects of water resources management and hydro-climatological disasters makes this book more relevant to the research community. The book should be of great interest to geologists, geomorphologists, hydrologists, geographers, researchers, students as well as disaster management professionals focusing on the management of water resources and hydro-climatological disasters.

Author : Sandeep Samantaray
Publisher : CRC Press
ISBN 13 : 1000386732
Total Pages : 310 pages
Book Rating : 4.38/5 ( download)

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Download or read book Watershed Management and Applications of AI written by Sandeep Samantaray and published by CRC Press. This book was released on 2021-05-16 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Land use and water resources are two major environmental issues which necessitate conservation, management, and maintenance practices through the use of various engineering techniques. Water scientists and environmental engineers must address the various aspects of flood control, soil conservation, rainfall-runoff processes, and groundwater hydrology. Watershed Management and Applications of AI provides the necessary principles of hydrology to provide practical strategies useful for the planning, design, and management of watersheds. The book also synthesizes novel new approaches, such as hydrological applications of machine learning using neural networks to predict runoff and using artificial intelligence for the prediction of groundwater fluctuations. Features: Presents hydrologic analysis and design along with soil conservation practices through proper watershed management techniques Provides analysis of land erosion and sediment transport in watersheds from small to large scale Includes estimations for runoff using different methodologies with systematic approaches for each Discusses water harvesting and development of water yield catchments This book will be a valuable resource for students in hydrology courses, environmental consultants, water resource engineers, and researchers in related water science and engineering fields.

Author : Gerald A. Corzo Perez
Publisher : John Wiley & Sons
ISBN 13 : 1119639344
Total Pages : 483 pages
Book Rating : 4.43/5 ( download)

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Download or read book Advanced Hydroinformatics written by Gerald A. Corzo Perez and published by John Wiley & Sons. This book was released on 2023-12-12 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Hydroinformatics Advanced Hydroinformatics Machine Learning and Optimization for Water Resources The rapid development of machine learning brings new possibilities for hydroinformatics research and practice with its ability to handle big data sets, identify patterns and anomalies in data, and provide more accurate forecasts. Advanced Hydroinformatics: Machine Learning and Optimization for Water Resources presents both original research and practical examples that demonstrate how machine learning can advance data analytics, accuracy of modeling and forecasting, and knowledge discovery for better water management. Volume Highlights Include: Overview of the application of artificial intelligence and machine learning techniques in hydroinformatics Advances in modeling hydrological systems Different data analysis methods and models for forecasting water resources New areas of knowledge discovery and optimization based on using machine learning techniques Case studies from North America, South America, the Caribbean, Europe, and Asia The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.

Author : Taesam Lee
Publisher :
ISBN 13 : 9783030647780
Total Pages : 0 pages
Book Rating : 4.81/5 ( download)

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Download or read book Deep Learning for Hydrometeorology and Environmental Science written by Taesam Lee and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN), especially for estimating parameters, with back-propagation as well as examples with real datasets of hydrometeorology (e.g. streamflow and temperature) and environmental science (e.g. water quality). Deep learning is known as part of machine learning methodology based on the artificial neural network. Increasing data availability and computing power enhance applications of deep learning to hydrometeorological and environmental fields. However, books that specifically focus on applications to these fields are limited. Most of deep learning books demonstrate theoretical backgrounds and mathematics. However, examples with real data and step-by-step explanations to understand the algorithms in hydrometeorology and environmental science are very rare. This book focuses on the explanation of deep learning techniques and their applications to hydrometeorological and environmental studies with real hydrological and environmental data. This book covers the major deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN) as well as the conventional artificial neural network model.

Author : Renji Remesan
Publisher : Springer
ISBN 13 : 3319092359
Total Pages : 250 pages
Book Rating : 4.55/5 ( download)

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Download or read book Hydrological Data Driven Modelling written by Renji Remesan and published by Springer. This book was released on 2014-11-03 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Valliappa Lakshmanan
Publisher : Springer
ISBN 13 : 3319172204
Total Pages : 252 pages
Book Rating : 4.00/5 ( download)

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Download or read book Machine Learning and Data Mining Approaches to Climate Science written by Valliappa Lakshmanan and published by Springer. This book was released on 2015-06-30 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents innovative work in Climate Informatics, a new field that reflects the application of data mining methods to climate science, and shows where this new and fast growing field is headed. Given its interdisciplinary nature, Climate Informatics offers insights, tools and methods that are increasingly needed in order to understand the climate system, an aspect which in turn has become crucial because of the threat of climate change. There has been a veritable explosion in the amount of data produced by satellites, environmental sensors and climate models that monitor, measure and forecast the earth system. In order to meaningfully pursue knowledge discovery on the basis of such voluminous and diverse datasets, it is necessary to apply machine learning methods, and Climate Informatics lies at the intersection of machine learning and climate science. This book grew out of the fourth workshop on Climate Informatics held in Boulder, Colorado in Sep. 2014.

Author : Arun Lal Srivastav
Publisher : Elsevier
ISBN 13 : 0323997155
Total Pages : 500 pages
Book Rating : 4.57/5 ( download)

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Download or read book Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence written by Arun Lal Srivastav and published by Elsevier. This book was released on 2022-11-11 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence covers computer-aided artificial intelligence and machine learning technologies as related to the impacts of climate change and its potential to prevent/remediate the effects. As such, different types of algorithms, mathematical relations and software models may help us to understand our current reality, predict future weather events and create new products and services to minimize human impact, chances of improving and saving lives and creating a healthier world. This book covers different types of tools for the prediction of climate change and alternative systems which can reduce the levels of threats observed by climate change scientists. Moreover, the book will help to achieve at least one of 17 sustainable development goals i.e., climate action. Includes case studies on the application of AI and machine learning for monitoring climate change effects and management Features applications of software and algorithms for modeling and forecasting climate change Shows how real-time monitoring of specific factors (temperature, level of greenhouse gases, rain fall patterns, etc.) are responsible for climate change and possible mitigation efforts to achieve environmental sustainability

Author : Julie A. Winkler
Publisher : Frontiers Media SA
ISBN 13 : 2832505457
Total Pages : 243 pages
Book Rating : 4.58/5 ( download)

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Download or read book Hydroclimatology of the Great Lakes Region of North America written by Julie A. Winkler and published by Frontiers Media SA. This book was released on 2022-11-14 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: