Cover -- Contents -- Editorial -- Preface -- Chapter 1 : Revisiting the motives for hydroinformatics -- 1.1   Introduction -- 1.2   Engineering Roots of Hydroinformatics -- 1.3   Modelling at the Centre of Hydroinformatics -- 1.4   Hydroinformatics: From Technology to Sociotechnology -- 1.5   Decision Support and Hydroinformatics -- 1.6   Hydroinformatics and the Virtual World -- 1.7   Role of Hydroinformaticians -- References -- Chapter 2 : Computational hydraulics: stage for the hydroinformatics act -- 2.1   Introduction -- 2.1.1   Historical context -- 2.2   Role of Characteristics in Computational Hydraulics -- 2.2.1   The meaning of characteristics -- 2.2.2   The three- and four-point method of characteristics -- 2.2.3   Practical aspects of characteristics -- 2.3   The Generations of Modelling -- 2.3.1   First- and second-generation modelling -- 2.3.2   Third-generation modelling -- 2.3.2.1   Establishment of the computational hydraulics centre -- 2.3.2.2   Challenges of the development -- 2.3.2.3   Stratified flow modelling -- 2.3.2.4   Wave modelling -- 2.3.2.5   Applications and commercialization of the third-generation models -- 2.3.3   Fourth-generation modelling -- 2.3.3.1   Driving forces for the development -- 2.3.3.2   Scope of the development -- 2.3.4   New developments in numerical methods -- 2.3.4.1   Finite difference methods -- 2.3.4.2   Unstructured grids -- 2.3.4.3   Particle tracking methods -- 2.4   Other Mike Abbott-Related Developments in Numerical Modelling -- 2.4.1   A dynamic population model -- 2.4.2   European Hydrologic System: Syst�eme Hydrologique Europ�een (SHE) -- 2.4.3   Laying of marine pipelines -- 2.5   From Computational Hydraulics to Hydroinformatics -- 2.5.1   The changing nature of modelling systems.

2.5.2   Challenges to model users -- 2.5.3   The way ahead -- References -- Chapter 3 : Hydroinformatics opening new horizons: union of computational hydraulics and artificial intelligence -- 3.1   Introduction -- 3.2   Earliest AI Efforts in Hydraulics, Hydrology and Hydroinformatics -- 3.3   Picking-Up Momentum -- 3.4   The Formative Years -- 3.5   Opening the Black Box -- 3.6   Growing Volumes of Data and Accelerating Computing Power -- 3.7   Recent Examples of AI-Enabled Systems -- 3.7.1   Planetary-scale surface water detection from space -- 3.7.2   Water quality sensing -- 3.7.3   Computer vision for opportunistic rainfall monitoring -- 3.7.4   Hydrologically informed machine learning for rainfall-runoff modelling -- 3.8   Opportunities for Future Developments -- 3.8.1   Machine learning -- 3.8.2   Enabling technologies -- 3.8.3   Freedom to the data! -- 3.8.4   Deep learning -- 3.8.5   Hydroinformatics-informed machine learning? -- 3.9   The Way Forward -- References -- Chapter 4 : Hydroinformatics impact on hydrological modelling -- 4.1   Introduction -- 4.2   Terminology and Model Classifications -- 4.2.1   Classification according to hydrological process description -- 4.2.2   Classification according to technological level -- 4.3   The SHE Venture -- 4.3.1   State of the art in hydrological modelling in the early 1970s -- 4.3.2   Motivation of the SHE development and creation of the SHE partnership -- 4.3.3   The initial SHE development (1976-1986) -- 4.3.4   From research code to practical applications (1986-1990s) -- 4.4   Evaluation Of the SHE Achievements -- 4.4.1   SHE: a contentious quantum leap -- 4.4.2   Evaluation of the impact of SHE on hydrological modelling today -- 4.5   Other Hydroinformatics Contributions.

4.5.1   Encapsulation of knowledge in digital modelling systems -- 4.5.2   Intelligent software systems to support stakeholders in water management -- 4.6   Conclusions -- Acknowledgements -- References -- Chapter 5 : Hydroinformatics as a 'game changer' in the water business -- 5.1   Introduction -- 5.2   Evolution of Hydroinformatics -- 5.2.1   Building the fundaments: 1960s and 1970s -- 5.2.2   The rise of computational modelling business: 1980s -- 5.2.3   Maturing and expanding: 1990s -- 5.2.4   Water business in the new millennium -- 5.3   Technical and Commercial Aspects of Hydroinformatics -- 5.3.1   Original view on hydroinformatics as part of the knowledge economy -- 5.3.2   State of technology -- 5.3.3   Changes in education of hydroinformatics and their reflections on business -- 5.3.4   Business transformation -- 5.3.5   Software providers and their business models -- 5.3.6   Software users and their needs -- 5.3.7   Data collection, sharing and publishing -- 5.4   Societal and Political Aspects of Hydroinformatics -- 5.4.1   Social justice and hydroinformatics -- 5.4.2   Learning by playing -- 5.4.3   Transparency of modelling and ethical aspects of presentation materials -- 5.5   Business Opportunities as Seen from 21st Century Perspectives -- 5.5.1   Water in cities market -- 5.5.2   Water resources market -- 5.5.3   Marine market -- 5.5.4   Other market segments related to water or the environment -- 5.6   Future Challenges for Hydroinformatics Business -- 5.6.1   Uncertainty and parametrisation of models -- 5.6.2   Climate change and its impacts -- 5.6.3   New business models in simulation modelling -- 5.6.4   Growth in hydroinformatics: consultancy demands -- 5.6.5   Vision for future or business -- References.

Chapter 6 : Hydroinformatics in China: overall developments and showcase of accomplishments in the Changjiang River basin -- 6.1   Introduction -- 6.2   DTR Decision Support Framework -- 6.3   Data Acquisition and Management -- 6.3.1   Types of data -- 6.3.2   Data acquisition -- 6.3.3   Data monitoring technologies -- 6.4   Models and Their Roles in DSS -- 6.4.1   Physically based water-related models -- 6.4.1.1   Meteorological modelling -- 6.4.1.2   Hydrological modelling and stochastic modelling -- 6.4.2   Regulation models -- 6.4.2.1   Regulation model for flood management in a river basin -- 6.4.2.2   Water resources regulation model -- 6.4.2.3   Ecological regulation model -- 6.4.2.4   Regulation model for power generation of group of reservoirs -- 6.4.2.5   Multi-objective regulation model -- 6.4.3   Risk assessment models -- 6.4.4   Data-driven approaches: artificial intelligence models -- 6.4.4.1   ML and AI models used for hydrological forecasting -- 6.4.4.2   Intelligent regulation technology based on a knowledge graph -- 6.4.4.3   ML and AI models for other water management tasks -- 6.5   Improved Governance and Public Involvement: The River/Lake Chief System -- 6.6   Applications in The Changjiang River Basin -- 6.6.1   Flood management -- 6.6.1.1   Data acquisition in the Changjiang River basin -- 6.6.1.2   Models and DSSs for the Changjiang River basin -- 6.6.1.3   Joint regulation of water projects for flood management -- 6.6.1.4   Application examples -- 6.6.2   River/Lake chief system and public participation -- 6.6.2.1   Functionalities of the RCS -- 6.6.2.2   Public participation -- 6.6.2.3   Performance of Chongqing RCS -- 6.7   Summary -- References -- Chapter 7 : Hydroinformatics education at IHE Delft: past and future -- 7.1   Introduction.

7.2   Motivation and Origins -- 7.3   Developments of IHE ' s Hydroinformatics Education Over Last 30 Years -- 7.4   Current Status and The Course Content of the Hydroinformatics MSc Specialization -- 7.5   Associated MSc Programmes -- 7.5.1   Erasmus + Flood Risk Management Master ' s programme -- 7.5.2   International Master ' s in Hydroinformatics -- 7.6   Hydroinformatics Education Worldwide -- 7.7   Outlook -- References -- 1. On the numerical computation of nearly-horizontal flows -- 2. On the Numerical modelling of short waves in shallow water -- 3. The fourth generation of numerical modelling in hydraulics -- 4. Introducing hydroinformatics -- 5. Forchheimer and Schoklitsch: a postmodern retrospection -- 6. Towards the hydraulics of the hydroinformatics era -- 7. Towards a hydroinformatics praxis in the service of social justice.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2023. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.