ISME-HYDRO offers an information e-Infrastructure, a web-based workflow that successfully addresses the need of daily and effective monitoring of hydropower reservoirs and rivers and of informed decision making for maintenance, routine exploitation and emergency situations. The daily operations of water resources managers include the inspection of periodically collected information from different sources, such as: detailed data about the condition of the distinct hydropower reservoirs, water economic data, meteorological data and forecasts, geographical information, information about the integrated nature environment. These data sources are usually dispersed in different locations and available in different formats for viewing and processing. For example, to make observations about the water equivalent of the snow stock, the expert water management analysts have to consult data from 6-7 sources, e.g. meteorological data, sunshine intensity, precipitation, soil moisture, air temperature, snow coverage size, and apply formulas to calculate the water snow equivalent and consider the potential harmful impact of its quantity to contingent areas of the water reservoirs. Some of this information like the precipitation, the snow cover, soil moisture, as well as the areas contingent to the water reservoirs are best observed from satellite data and images. To make the daily operations of water management easier and more effective it is necessary to provide with capability of federated and integrated representation of different kinds of information, e.g. spatial and digital, symbolic data, images and metadata and to ensure their easy linking in a common open, easy to maintain, update and rely on information. An information system that successfully addresses this need requires an information infrastructure that provides with this capability. ISME-HYDRO is such an information infrastructure based on linked data technologies and implemented in a distributed architecture to employ it in a wholesome software system, composed of several logical layers. Further, a crucial element for river exploitation is the ability to monitor the sediment deposition processes and the changes in the river dynamics for a variety of purposes, including setting the fairway in navigable rivers. Thus, ISME-HYDRO uses AI methods of deep learning to predict the upcoming hydrodynamic changes in the river and correctly set the fairway trajectory. These features are integrated into the linked data infrastructure and provide flexible querying and visualization of the hydrodynamic features, meteorological data from satellites and fairway on an interactive map, in tables and on graphs.
ISME-HYDRO infrastructure is easily extendable with other features and prone to very efficient maintenance.
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ISME-HYDRO is funded by ESA PECS Bulgaria under contracts No 4000122783/17/NL/S, No 4000133836/21/NL/SC, No. 4000141832/23/NL/MH/rp