Advanced and novel hydrology models based on enhanced data collection, analysis, and prediction
CHIST-ERA IV project
CHIST-ERA-19-CES-002
Official starting date: May 1, 2021
Mission of the project
Apply ICT and ML techniques for improving the accuracy of hydrological models, optimize water management, and predict extreme events.
Funding framework: Horizon 2020 Future and Emerging Technologies (FET) through ERA-NET Cofund funding scheme
Funding agency for Italy: Ministero dell'Istruzione, dell'UniversitĂ e della Ricerca (MIUR)
Duration: 36 months (starting: May 1st, 2021)
Obj 1: improve data quality
Propose sensor location strategies and smart sampling algorithms to streamline the number of required measurement points and samples
Obj 2: Improve hydrologic models
Develop low-complexity algorithms to dynamically adjust existing hydrological models' parameters according to the physical system characteristics
Obj 3: Improve prediction reliability and quality
Apply distributed learning techniques and communication-efficient federated learning and analytics to solve comprehensive hydrological systems that account for athmospheric, surface and sub-surface water processes, and offer more accurate and long-term predictions
Obj4: Improve decision making
Develop interactive tools to display the model's outputs and visualize the (predicted) effects of actions, allowing for a more effective, reliable and informed decision making