The exploitation of rivers and hydropower reservoirs involves daily monitoring of the water resources, the meteorological conditions, the status of the coast, the flood areas, etc. Providing timely and easy to consume information, analytics and early warnings for current and upcoming statuses or events helps water resources managers and high level officials to adequately observe and plan operations for sustainable development of river areas. We present an intelligent web-based workflow that combines different methods of AI, e.g. linked data, deep learning and reasoning, to provide an integrated information system that ensures interoperability between spatial information of GIS systems, remote sensing information, symbolic and numerical data like meteorological data and proprietary measurements and creates an actionable knowledge value chain for the needs of rivers and hydropower reservoirs exploitation. We show how hydrodynamic modelling using Telemac with forecasted water economic data, produced from earth observation and in-situ measurements applied to a series of neural network architectures, derive predictive river models, that are integrated into the work-flow and made available for querying, reviewing, projecting the changes in the navigational conditions of navigable rivers, geo-spatial visualization on GIS. The intelligent work-flow further provides functional features like forecasts generation for river discharge, turbidity, water level, and querying of a variety of correlations and synchronized visualizations in tables, graphs and GIS maps. It helps improve the operational efficiency by providing the ability to interact with and view all water resources management information at once, ensures accuracy and decision making ability by correlating historic and forecast data with satellite imagery and data, gives automated forecasting of water economic data using satellite meteorological data, and reduces risk through automated alerts. We demonstrate on the example of Danube the advantages of the presented intelligent web-based work-flow for the monitoring of rivers and their environment for sustainable development and planning.
Dr. Mariana Damova is the CEO of Mozaika (http://www.mozajka.co), a company providing research and solutions in the field of data science, natural interfaces, and human insight that specializes in building semantic information infrastructures in different verticals, such as business information delivery, human resources management, cultural heritage, earth observation, water resources management, and sells data as a service, intelligence as a service and research and development. Her background is in natural language processing, Semantic Web Technologies and AI, with strong academic and industrial track record in North America and Europe, including C-level executive. She has taught graduate courses, conducted research at several universities in Europe and North America, led international interdisciplinary teams with projects on various facets of knowledge management that carried technological risk. At Mozaika she drives the business strategy and the projects from management and engineering stand point, and has acquired customers such as the European Space Agency, the European Commission, Bulgarian Academy of Sciences, Sofia Municipality, Rittal GmbH, the German-Bulgarian Chamber of Industry and Commerce and partners from a large range of European academic institutions and private sector companies to execute innovative projects with disruptive edge. Dr. Damova holds a PhD from the University of Stuttgart, Germany, and a mini MBA from McGill University, Canada. She regularly reviews books and articles for ACM ComputingReviews.com and has authored/co-authored more than 50 publications in linguistics, semantic technologies, earth observation and AI. ((http://www.marianadamova.com))