The role of ICT in contributing to the “Smart Technologies EIP Priority” is widely recognised by the scientific community and water business professionals. Despite relevant progress and innovation achieved in this field, several barriers hinder the implementation of Smart Water Technologies such as the fragmentation of the sector, slow adoption, absence of SME development, and no holistic vision of water supply considering its whole life cycle. Moreover, at present a fully integrated Smart Water Network does not exist in Europe or globally. Hence, current lack of knowledge of EU water research and innovation results on industry, policy makers, and citizens is slowing down the widespread application of solutions that can leverage the development of the urban systems and infrastructures of tomorrow. This scenario shows that achieving water-related challenges cannot progress with the sole contribution of research. In this sense, the project has the vision of establishing and supporting a thriving, interconnected ICT for water community to promote the dissemination and exploitation of EU funded activities and results in this area. WIDEST will address its goals through a project-to-project approach and the coordination among relevant stakeholders by means of five objectives that will include, amongst others: Conducting literature reviews of relevant academic and commercial references; Establishing common frameworks such as standards, guidelines, website, video channel; Organizing events including conferences, workshops, special sessions; Producing three Topical Roadmaps and one Overall Roadmap; Producing a Portfolio of effective ICT for water management technologies including the methodology to build, update and execute it. The project is backed by a strong consortium composed by institutions with proven track record and expertise across different facets of ICT for water research, including established connections with key stakeholders.

Satellite remote sensing has been evolved into a powerful tool for global monitoring of surface waters. Earth Observations (EO) and remote sensing are widely used for quantifying the physical parameters of reservoirs as well as for retrieving selected water constituents concentrations. Space-O aims at the integration of state of the art (EO) and in situ monitoring with advanced hydrological, water quality models and ICT tools into a powerful decision support system (DSS) for generating real time, short to medium term forecasting water flows and quality data in reservoirs which will be used for the optimization of water treatment plants (WTPs) operations, establishing a complete service line from EO to water business sector. An operational service platform will be designed to facilitate increased interoperability among EO and modeled services. Data acquisition and integration of almost real time EO data in the hydrological and water quality models will be implemented in order to provide improved real-time, short to medium term water quantity and quality forecasting in reservoirs. A risk-based DSS will be developed in order to enable cost-effective and environmental sustainable Water Treatment Plants (WTPs) operation, based on the water quality parameters forecasts at the reservoir, the in situ monitoring data and the data collected through supervisory control and data acquisition (SCADA) systems used in WTPs for operation control. Additionally, developing Copernicus Services (C3S) will be jointly assessed with site-specific data sets generated through the satellite, modeling, in situ and citizens monitoring services, to produce continuous monitored indicators for enabling water quality Risk Assessment analysis on a catchment level.

PrimeWater aims to maximize the potential of the Earth Observation (EO) technologies for the water sector by enhancing and expanding the information base for inland water quality attributes, through advanced physics-based algorithms that integrate multi- and hyper-spectral imagery from satellite, airborne and ground-based sensors, increasing the situational intelligence of water regulators, emergency planners, water-related industry professionals and local communities. PrimeWater aspires to further add value to EO data and other Copernicus sectoral services through cross-cutting research with Data Assimilation (DA) and Machine Learning (ML) techniques aiming at improving the skill of hydro-ecological forecasts and their related impact at different spatial scales and time horizons, and hence improve preparedness against water hazards and enhance the capacity of decision-making through uncertainty information. PrimeWater will establish a complete value chain linking science with the water business sector, ensuring the co-development of products and services through continuous and efficient interaction and communication with water professionals across the globe and in-depth analysis of the intrinsic barriers for the wide market uptake of EO-enabled services in the water sector. As a result PrimeWater will deliver water intelligent services that capitalize on advanced EO data products and intersections with other data sources, will build on cause-effect analyses through diagnostic modelling tools, and will utilize predictive and prescriptive calculations by integrating forecasting capabilities with planning and scenario analysis.