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Information Theory And Artificial Intelligence To Manage Uncertainty In Hydrodynamic And Hydrological Models
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Book Synopsis Information Theory and Artificial Intelligence to Manage Uncertainty in Hydrodynamic and Hydrological Models by : Abebe Andualem Jemberie
Download or read book Information Theory and Artificial Intelligence to Manage Uncertainty in Hydrodynamic and Hydrological Models written by Abebe Andualem Jemberie and published by CRC Press. This book was released on 2014-04-21 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: The complementary nature of physically-based and data-driven models in their demand for physical insight and historical data, leads to the notion that the predictions of a physically-based model can be improved and the associated uncertainty can be systematically reduced through the conjunctive use of a data-driven model of the residuals. The objective of this thesis is to minimise the inevitable mismatch between physically-based models and the actual processes as described by the mismatch between predictions and observations. The complementary modelling approach is applied to various hydrodynamic and hydrological models.
Book Synopsis Frontiers in Flood Research by : Ioulia Tchiguirinskaia
Download or read book Frontiers in Flood Research written by Ioulia Tchiguirinskaia and published by . This book was released on 2006 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Urban Hydroinformatics by : Roland K. Price
Download or read book Urban Hydroinformatics written by Roland K. Price and published by IWA Publishing. This book was released on 2011 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introduction to hydroinformatics applied to urban water management. It shows how to make the best use of information and communication technologies for manipulating information to manage water in the urban environment. The book covers the acquisition and analysis of data from urban water systems to instantiate mathematical models or calculations, which describe identified physical processes. The models are operated within prescribed management procedures to inform decision makers, who are responsible to recognized stakeholders. The application is to the major components of the urban water environment, namely water supply, treatment and distribution, wastewater and stormwater collection, treatment and impact on receiving waters, and groundwater and urban flooding. Urban Hydroinformatics pays particular attention to modeling, decision support through procedures, economics and management, and implementation in both developed and developing countries. The book is written with post-graduates, researchers and practicing engineers who are involved in urban water management and want to improve the scope and reliability of their systems.
Book Synopsis Fundamental Constants by : Boris M. Menin
Download or read book Fundamental Constants written by Boris M. Menin and published by Cambridge Scholars Publishing. This book was released on 2019-02-27 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is devoted to one of the important areas of theoretical and experimental physics—the calculation of the accuracy of measurements of fundamental physical constants. To achieve this goal, numerous methods and criteria have been proposed. However, all of them are focused on identifying a posteriori uncertainty caused by the idealization of the model and its subsequent computerization in comparison with the physical system. This book focuses on formulating an a priori interaction between the level of a detailed description of a material object (the number of registered quantities) and the lowest uncertainty in measuring a physical constant. It contains the materials necessary for the optimal design of models describing a physical phenomenon. It will appeal to scientists and engineers, as well as university students.
Book Synopsis Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling by : NAGENDRA. KAYASTHA
Download or read book Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling written by NAGENDRA. KAYASTHA and published by CRC Press. This book was released on 2018-09-27 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. A solution could be the in use of several specialized models organized in the so-called committees. Refining the committee approach is one of the important topics of this study, and it is demonstrated that it allows for increased predictive capability of models. Another topic addressed is the prediction of hydrologic models' uncertainty. The traditionally used Monte Carlo method is based on the past data and cannot be directly used for estimation of model uncertainty for the future model runs during its operation. In this thesis the so-called MLUE (Machine Learning for Uncertainty Estimation) approach is further explored and extended; in it the machine learning techniques (e.g. neural networks) are used to encapsulate the results of Monte Carlo experiments in a predictive model that is able to estimate uncertainty for the future states of the modelled system. Furthermore, it is demonstrated that a committee of several predictive uncertainty models allows for an increase in prediction accuracy. Catchments in Nepal, UK and USA are used as case studies. In flood modelling hydrological models are typically used in combination with hydraulic models forming a cascade, often supported by geospatial processing. For uncertainty analysis of flood inundation modelling of the Nzoia catchment (Kenya) SWAT hydrological and SOBEK hydrodynamic models are integrated, and the parametric uncertainty of the hydrological model is allowed to propagate through the model cascade using Monte Carlo simulations, leading to the generation of the probabilistic flood maps. Due to the high computational complexity of these experiments, the high performance (cluster) computing framework is designed and used. This study refined a number of hydroinformatics techniques, thus enhancing uncertainty-based hydrological and integrated modelling.
Book Synopsis Practical Hydroinformatics by : Robert J. Abrahart
Download or read book Practical Hydroinformatics written by Robert J. Abrahart and published by Springer Science & Business Media. This book was released on 2008-10-24 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. ...
Book Synopsis Hydrological Data Driven Modelling by : Renji Remesan
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 261 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.
Book Synopsis Advances in Hydrologic Forecasts and Water Resources Management by : Fi-John Chang
Download or read book Advances in Hydrologic Forecasts and Water Resources Management written by Fi-John Chang and published by MDPI. This book was released on 2021-01-20 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Applications of Information Theory and Machine Learning for Hydrologic Modeling by : Andrew R. Bennett
Download or read book Applications of Information Theory and Machine Learning for Hydrologic Modeling written by Andrew R. Bennett and published by . This book was released on 2021 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: An explosion of new data sources, expansion of computing resources, and theoretical advancesin data science have spurred the rapid adaptation of data-driven methods in earth system science, including hydrology. In this dissertation I will describe three applications of data-driven methods with applications to hydrologic modeling. In chapter 2 I present a framework for hydrologic model intercomparison which examines process interactions within a process-based hydrologic model (PBHM). I show that taking a more holistic approach can shed light into the functioning of these complex models. In chapter 3 I couple machine learned representations of turbulent heat fluxes into a PBHM, and show that neural networks can provide better predictions and transferability than the process-based equations that are used in PBHMs. Building on this, in chapter 4 I use explainable AI (XAI) methods to examine what the neural network has learned. I find that the neural network is able to learn physically plausible relationships and can identify how to partition between latent and sensible heat fluxes based only on short-term temporal data. I also show how we can use XAI to examine what neural networks have learned between sites.This method can uncover that certain sites can be used as predictors for many other sites, as well as that site specific traits such as vegetation type play a large role in the neural network’s ability to generalize to sites it was not trained on. Finally, based on the findings of these three applications I discuss in Chapter 5 how data-driven techniques in general can contribute to improved hydrologic understanding
Book Synopsis Advances in Hydrologic Forecasts and Water Resources Management by : Fi-John Chang
Download or read book Advances in Hydrologic Forecasts and Water Resources Management written by Fi-John Chang and published by . This book was released on 2020 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Artificial Intelligence Techniques in Hydrology and Water Resources Management by : Fi-John Chang
Download or read book Artificial Intelligence Techniques in Hydrology and Water Resources Management written by Fi-John Chang and published by Mdpi AG. This book was released on 2023-05-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The sustainable management of water cycles is crucial in the context of climate change and global warming. It involves managing global, regional, and local water cycles, as well as urban, agricultural, and industrial water cycles, to conserve water resources and their relationships with energy, food, microclimates, biodiversity, ecosystem functioning, and anthropogenic activities. Hydrological modeling is indispensable for achieving this goal, as it is essential for water resources management and the mitigation of natural disasters. In recent decades, the application of artificial intelligence (AI) techniques in hydrology and water resources management has led to notable advances. In the face of hydro-geo-meteorological uncertainty, AI approaches have proven to be powerful tools for accurately modeling complex, nonlinear hydrological processes and effectively utilizing various digital and imaging data sources, such as ground gauges, remote sensing tools, and in situ Internet of Things (IoT) devices. The thirteen research papers published in this Special Issue make significant contributions to long- and short-term hydrological modeling and water resources management under changing environments using AI techniques coupled with various analytics tools. These contributions, which cover hydrological forecasting, microclimate control, and climate adaptation, can promote hydrology research and direct policy making toward sustainable and integrated water resources management.
Book Synopsis Nonlinear Dynamics and Chaos with Applications to Hydrodynamics and Hydrological Modelling by : Slavco Velickov
Download or read book Nonlinear Dynamics and Chaos with Applications to Hydrodynamics and Hydrological Modelling written by Slavco Velickov and published by CRC Press. This book was released on 2004-05-15 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hydroinformatics system represents an electronic knowledge encapsulator that models part of the real world and can be used for the simulation and analysis of physical, chemical and biological processes in water systems, in order to achieve a better management of the aquatic environment. Thus, modelling is at the heart of hydroinformatics. The theory of nonlinear dynamics and chaos, and the extent to which recent improvements in the understanding of inherently nonlinear natural processes present challenges to the use of mathematical models in the analysis of water and environmental systems, are elaborated in this work. In particular, it demonstrates that the deterministic chaos present in many nonlinear systems can impose fundamental limitations on our ability to predict behaviour, even when well-defined mathematical models exist. On the other hand, methodologies and tools from the theory of nonlinear dynamics and chaos can provide means for a better accuracy of short-term predictions as demonstrated through the practical applications in this work.
Book Synopsis New Uncertainty Concepts in Hydrology and Water Resources by : Zbigniew W. Kundzewicz
Download or read book New Uncertainty Concepts in Hydrology and Water Resources written by Zbigniew W. Kundzewicz and published by Cambridge University Press. This book was released on 2007-03-05 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains an overview of conventional and nonorthodox methods of representing and analyzing aspects of uncertainty in hydrology and water resources. Topics covered include: fractals, deterministic chaos, risk and reliability related criteria, fuzzy sets, pattern recognition, random fields, time series, stochastic modeling, outliers detection, nonparametric methods, information measures, and neural networks. Many new topics are discussed that make this book particularly valuable, and they include multifractals (applied to rain), a Bayesian relative information measure as a tool for analyzing the outputs of general circulation models, and a stochastic weather generator using atmospheric circulation patterns as a means to evaluate climate change.
Book Synopsis Practical Hydroinformatics by : Robert J. Abrahart
Download or read book Practical Hydroinformatics written by Robert J. Abrahart and published by Springer. This book was released on 2009-08-29 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. ...
Book Synopsis Applications of Machine Learning in Hydroclimatology by : Roshan Karan Srivastav
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.
Book Synopsis Hydraulics of Dam and River Structures by : Farhad Yazdandoost
Download or read book Hydraulics of Dam and River Structures written by Farhad Yazdandoost and published by Taylor & Francis. This book was released on 2004-08 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises the papers of the International Conference on Hydraulics of Dams and Rivers Structures, held in Tehran, 26-28 April 2004. The topics covered include air-water flows, intakes and outlets, hydrodynamic forces, energy dissipators, stepped spillways, scouring and sedimentation around structures, numerical approaches in river hydrodynamics, river response to hydraulic structures and hydroinformatic applications. This proceedings provides professionals and researchers with news of interdisciplinary research findings, considering future development of the sector in its many and various applications.
Book Synopsis Flood Forecasting Using Machine Learning Methods by : Fi-John Chang
Download or read book Flood Forecasting Using Machine Learning Methods written by Fi-John Chang and published by MDPI. This book was released on 2019-02-28 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
