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Jitendra Kumar Vyas, Muthiah Perumal and Tommaso Moramarco
Streamflow measurements during high floods is a challenge for which the World Meteorological Organization fosters the development of innovative technologies for achieving an accurate estimation of the discharge. The use of non-contact sensors for monitor...
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Donatella Termini and Tommaso Moramarco
The estimation of velocity profile in turbulent open channels is a difficult task due to the significant effects of the secondary flow. The present paper investigates the mechanism of the velocity-dip phenomenon, whereby the location of the maximum veloc...
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Donatella Termini and Tommaso Moramarco
The estimation of velocity profile in turbulent open channels is a difficult task due to the significant effects of the secondary flow. The present paper investigates the mechanism of the velocity-dip phenomenon, whereby the location of the maximum veloc...
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Tommaso Moramarco, Silvia Barbetta, Angelica Tarpanelli
Pág. 1 - 12
A new methodology for estimating the discharge starting from the monitoring of surface flow velocity, usurf, is proposed. The approach, based on the entropy theory, involves the actual location of maximum flow velocity, umax, which may occur below the wa...
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Tommaso Moramarco, Silvia Barbetta and Angelica Tarpanelli
A new methodology for estimating the discharge starting from the monitoring of surface flow velocity, usurf, is proposed. The approach, based on the entropy theory, involves the actual location of maximum flow velocity, umax, which may occur below the wa...
ver más
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Silvia Barbetta, Gabriele Coccia, Tommaso Moramarco and Ezio Todini
This work presents the application of the multi-temporal approach of the Model Conditional Processor (MCP-MT) for predictive uncertainty (PU) estimation in the Godavari River basin, India. MCP-MT is developed for making probabilistic Bayesian decision. I...
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Silvia Barbetta, Gabriele Coccia, Tommaso Moramarco, Ezio Todini
Pág. 1 - 25
This work presents the application of the multi-temporal approach of the Model Conditional Processor (MCP-MT) for predictive uncertainty (PU) estimation in the Godavari River basin, India. MCP-MT is developed for making probabilistic Bayesian decision. I...
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Christian Massari, Luca Brocca, Luca Ciabatta, Tommaso Moramarco, Simone Gabellani, Clement Albergel, Patricia De Rosnay, Silvia Puca and Wolfgang Wagner
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Christian Massari, Luca Brocca, Luca Ciabatta, Tommaso Moramarco, Simone Gabellani, Clement Albergel, Patricia De Rosnay, Silvia Puca and Wolfgang Wagner
The ever-increasing availability of new remote sensing and land surface model datasets opens new opportunities for hydrologists to improve flood forecasting systems. The current study investigates the performance of two operational soil moisture (SM) pro...
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