Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 21, issue 2
Articles | Volume 21, issue 2
https://doi.org/10.5194/hess-21-839-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-839-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 21, issue 2
Research article
 | 
14 Feb 2017
Research article |  | 14 Feb 2017

Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?

Maurizio Mazzoleni, Martin Verlaan, Leonardo Alfonso, Martina Monego, Daniele Norbiato, Miche Ferri, and Dimitri P. Solomatine

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Short summary
This study assesses the potential use of crowdsourced data in hydrological modeling, which are characterized by irregular availability and variable accuracy. We show that even data with these characteristics can improve flood prediction if properly integrated into hydrological models. This study provides technological support to citizen observatories of water, in which citizens can play an active role in capturing information, leading to improved model forecasts and better flood management.
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