Advanced and novel hydrology models based on enhanced data collection, analysis, and prediction

CHIST-ERA IV project

Mission of the project

Apply ICT and ML techniques for improving the accuracy of hydrological models, optimize water management, and predict extreme events.

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


Questions?

Contact andrea.zanella@unipd.it to get more information on the project