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Hybrid Models for Hydrological Forecasting
This book presents the investigation of possibilities and different architectures of integrating hydrological knowledge and conceptual models with data-driven models for the purpose of hydrological flow forecasting. Models resulting from such integration are referred to as hybrid models. The book addresses the following specific topics: A classification of different hybrid modelling approaches in the context of flow forecasting.The methodological development and application of modular models based on clustering and baseflow empirical formulations.The integration of hydrological conceptual models with neural network error corrector models and the use of committee models for daily streamflow forecasting.The application of modular modelling and fuzzy committee models to the problem of downscaling weather information for hydrological forecasting. The results of this research show the increased forecasting accuracy when modular models, which integrate conceptual and data-driven models, are considered. Committee machine modelling show to be able to manage increased lead time with an acceptable accuracy.
Data Science for Civil Engineering
This book explains use of data science-based techniques for modeling and providing optimal solutions to complex problems in civil engineering. It discusses civil engineering problems like air, water and land pollution, climate crisis, transportation infrastructures, traffic and travel modes, mobility services, and so forth. Divided into two sections, the first one deals with the basics of data science and essential mathematics while the second section covers pertinent applications in structural and environmental engineering, construction management, and transportation. Features: Details information on essential mathematics required to implement civil engineering applications using data science techniques. Discusses broad background of data science and its fundamentals. Focusses on structural engineering, transportation systems, water resource management, geomatics, and environmental engineering. Includes python programming libraries to solve complex problems. Addresses various real-world applications of data science based civil engineering use cases. This book aims at senior undergraduate students in Civil Engineering and Applied Data Science.
Hydrology and Best Practices for Managing Water Resources in Arid and Semi-Arid Lands
The management of water resources is extremely important for survival. Depending on the climate, certain regions require different strategies to maintain sustainable hydrological systems. Hydrology and Best Practices for Managing Water Resources in Arid and Semi-Arid Lands is a crucial scholarly resource that outlines current trends in water management and offers solutions for the future of this growing field. Highlighting pertinent topics such as hydrological processes modelling, satellite hydrology, water pollution, and climate resources, this publication is ideal for environmental engineers, academicians, graduate students, and researchers that are eager to discover more about the issues and processes currently shaping water management technology.
Hydrology and Water Resources Management in Arid, Semi-Arid, and Tropical Regions
Hydrology is a key influence on water security, environmental sustainability, agricultural production, energy, and transport, especially in unique environments such as arid regions and the tropics, where degradation issues on water and land can threaten the livelihoods of poor communities. With implications in urbanization, landscape architecture, and sanitation, enhancing the practice of water use, management, and planning is imperative for the sustainable development of these regions. Hydrology and Water Resources Management in Arid, Semi-Arid, and Tropical Regions is an essential research publication that seeks to improve scientific understanding and sharing of data in hydrology and integrated water resources management of arid, semi-arid, and tropical regions in order to enhance water governance and alleviate reduction in the vulnerability of water resources systems to global changes. Featuring a wide range of topics such as hydrometeorology, sustainable development, and climate change, this book is ideal for researchers, technology developers, academicians, policymakers, government officials, and students.
Rejection of Emerging Organic Contaminants by Nanofiltration and Reverse Osmosis Membranes
Pollution of water sources with emerging contaminants (micropollutants) is a fact known worldwide. This book examines the presence of micropollutants (medicines, hormones, pesticides) in surface water and the lack of success in removal by conventional water treatment options, then explores nanofiltraion and reverse osmosis methods as better options. The author reviews quantification of removals by means of multivariate data analysis techniques, providing a better understanding of the separation of micropollutants by membranes. He discusses increases in water reuse practices and the important role water membrane treatment will play in the removal of micropollutants and the importance of understanding the characteristics, advantages and disadvantages of nanofiltration and reverse osmosis.
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Climate Change Adaptation, Resilience and Hazards
This book analyses the links between climate change adaptation, resilience and the impacts of hazards. The contributors cover topics such as climate change adaptation in coastal zones, the evaluation of community land models, climate change considerations in public health and water resource management, as well as conceptual frameworks for understanding vulnerabilities to extreme climate events. The book focuses on a variety of concrete projects, initiatives and strategies currently being implemented across the world. It also presents case studies, trends, data and projects that illustrate how cities, communities and regions have been striving to achieve resilience and have handled hazards.
Spatiotemporal Analysis of Extreme Hydrological Events
Spatio-temporal Analysis of Extreme Hydrological Events offers an extensive view of the experiences and applications of the latest developments and methodologies for analyzing and understanding extreme environmental and hydrological events. The book addresses the topic using spatio-temporal methods, such as space-time geostatistics, machine learning, statistical theory, hydrological modelling, neural network and evolutionary algorithms. This important resource for both hydrologists and statisticians interested in the framework of spatial and temporal analysis of hydrological events will provide users with an enhanced understanding of the relationship between magnitude, dynamics and the probability of extreme hydrological events. - Presents spatio-temporal processes, including multivariate dynamic modelling - Provides varying methodological approaches, giving the readers multiple hydrological modelling information to use in their work - Includes a variety of case studies making the context of the book relatable to everyday working situations
Modeling of Hydrodynamics and Sediment Transport in the Mekong Delta
This research aims to investigate the prevailing sediment dynamics and the sediment budget in the Mekong Delta by using a process-based model. Understanding sediment dynamics for the Mekong Delta requires high resolution analysis and detailed data, which is a challenge for managers and scientists. This study introduces such an approach and focuses on modeling the entire system with a process-based approach with Delft3D-4 and Delft3D Flexible Mesh (DFM). The first model is used to explore sediment dynamics at the coastal zone. The latter model allows straightforward coupling of 1D and 2D grids, making it suitable for analyzing the complex river and canal network of the Mekong Delta. The validated model suggests that the Mekong Delta receives ~99 Mt/year sediment from the Mekong River. This is much lower than the common estimate of 160 Mt/year. Only about 23% of the modelled total sediment load at Kratie is exported to the sea. The remaining portion is trapped in the rivers and floodplains of the Mekong Delta. The results advance understanding of sediment dynamics and sediment budget in the Mekong Delta. As such the model is an efficient tool to support delta management and planning.
