This section presents, in a compact form, future research directions in ICT4Water resulted from the state of the art section correlated with priority areas of HORIZON 2020. The main current directions of Hydroinformatics to properly manage the problems of aquatic environment are mentioned here.

Water related subjects

• River/urban flood forecasting and management
• Reservoir operations
• Water supply management (Drinking water, Industry, Irrigation)
• Water and energy efficiency in water distribution networks
• Ecology and Water quality (Wastewater, Environmental flows, Drinking water)

Research directions

• Water management solutions that consider synergies across sectors: nexus not only between water and energy, but also with other aspects in Smart Cities land, food, climate change, and smart home ecosystems; need contributions in:
  • monitoring systems
  • predictive models and tools
  • analytical methods to handle climate uncertainty
  • user access to modelling results
  • high performance decision support
• Improved solutions for social perceptions of water
  • adaptive pricing strategies, legal and policy challenges
• Reduced total cost of ownership for Water ICT
  • accurate monitoring and understanding of water use, demand and related risks
  • cost-effective technical solutions addressing sensing, analysis, engagement
  • business models with energy consumption monitoring,
  • improved leakage detection technologies
  • analysis (understanding TCO/benefit ratio)
• Increase interoperability by the use of standards for
  • data formats, vocabularies, procedures,
  • metadata – centralized metadata catalogue
  • software (API)
  • Decision Support Systems – comparability between implementations (technologies, algorithms)
  • common frameworks and KPIs for objective assessment of improvements
• Measure results in the application of ICT for water management
  • define new indicators related to water management.
• Improvement of the Data4Water services
  
• integrated information-centric system will facilitate the conversion of data to knowledge; the process integrates the hydrological information with the economics, political and social disciplines  
• participatory citizen science for water management will improve water quality monitoring, expand data collection, improve the statistical power of data sets, facilitate the observation of difficult to quantify phenomena, proliferation of citizen science, etc.
• anomaly detection on smart sensors data used in water management
• anonymity protection of data sources that share and interact around content and information on mobile and web-based platforms; data anonymization targets the privacy protection of data sources
• extend the Cloud to IoT, for optimizing the managing of data for water by rapidly, near to source processing data or analyzing and sending it to other IoTs and/or Cloud
• allow exchange and combination of data from heterogeneous domains through mechanisms that support the interoperability of cross-domain applications.