Carried out as part of the DTE Challenge of the European Space Agency (ESA), the DTE Hydrology project studied the possibility of creating a Digital Twin Earth of the hydrological cycle strongly based on satellite data and physical-mathematical modeling.
The project
Lasting one year (September 2020 – September 2021), the DTE Hydrology project is part of an ESA research and technological development line which aims to develop a digital twin Earth (DTE, in fact), a sort of interactive model capable of reproducing the dynamics of the planet by integrating satellite data with those from other sources, Big Data and artificial intelligence. DTE Hydrology focused on the study of the water cycle, hydrological processes, and their potential impacts, aiming to highlight the potential of high resolution (1 km) satellite products for the description of the water cycle, for the prediction of hydrological hazard (floods, droughts and landslides) and for resource monitoring and management.
The project saw its continuation with the subsequent DTE Hydrology Evolution.
Results
- Alfieri L, Avanzi F, Delogu F, Gabellani S, Bruno G, Campo L, Libertino A, Massari C, Tarpanelli A, Rains D, Miralles DG, Quast R, Vreugdenhil M, Wu H and Brocca L. High-resolution satellite products improve hydrological modeling in northern Italy. Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022: il paper descrive come dati satellitari innovativi, ad alta risoluzione, possono essere impiegati nei modelli idrologici per rappresentare il ciclo dell’acqua, e monitorare e prevedere gli eventi estremi
CIMA Research Foundation’s role
During the project, innovative data for the estimation of precipitation, soil moisture and satellite evapotranspiration were developed. CIMA’s role was to integrate these data into the physical-mathematical modeling of the hydrological cycle. In particular, the S3M and Continuum models made use of these innovative data on the Po basin with the aim of understanding whether they could effectively reproduce the hydrological cycle in the basin. The results show that distributed, high-resolution hydrological modeling can be implemented with excellent results using only and exclusively satellite data.