Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2017-59
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
06 Feb 2017
Review status
This discussion paper is under review for the journal Hydrology and Earth System Sciences (HESS).
Towards assimilation of crowdsourced observations for different levels of citizen engagement: the flood event of 2013 in the Bacchiglione catchment
Maurizio Mazzoleni1, Vivian Juliette Cortes Arevalo2, Uta Wehn1, Leonardo Alfonso1, Daniele Norbiato3, Martina Monego3, Michele Ferri3, and Dimitri P. Solomatine1,4 1Integrated Water Systems & Governance, UNESCO-IHE Institute for Water Education, Delft, 2611AX, the Netherlands
2Water Engineering and Management, University of Twente, Enschede, 7522 NB, the Netherlands
3Alto Adriatico Water Authority, Venice, Italy
4Water Resources Section, Delft University of Technology, Delft, 2628 CD, the Netherlands
Abstract. Accurate flood predictions are essential to reduce the risk and damages over large urbanized areas. To improve prediction capabilities, hydrological measurements derived by traditional physical sensors are integrated in real-time within mathematic models. Recently, traditional sensors are complemented with low-cost social sensors. However, measurements derived by social sensors (i.e. crowdsourced observations) can be more spatially distributed but less accurate. In this study, we assess the usefulness for model performance of assimilating crowdsourced observations from a heterogeneous network of static physical, static social and dynamic social sensors. We assess potential effects on the model predictions to the extreme flood event occurred in the Bacchiglione catchment on May 2013. Flood predictions are estimated at the target point of Ponte degli Angeli (Vicenza), outlet of the Bacchiglione catchment, by means of a semi-distributed hydrological model. The contribution of the upstream sub-catchment is calculated using a conceptual hydrological model. The flow is propagated along the river reach using a hydraulic model. In both models, a Kalman filter is implemented to assimilate the real-time crowdsourced observations. We synthetically derived crowdsourced observations for either static social or dynamic social sensors because crowdsourced measures were not available. We consider three sets of experiments: (1) only physical sensors are available; (2) probability of receiving crowdsourced observations and (3) realistic scenario of citizen engagement based on population distribution. The results demonstrated the importance of integrating crowdsourced observations. Observations from upstream sub-catchments assimilated into the hydrological model ensures high model performance for high lead time values. Observations next to the outlet of the catchments provide good results for short lead times. Furthermore, citizen engagement level scenarios moved by a feeling of belonging to a community of friends indicated flood prediction improvements when such small communities are located upstream a particular target point. Effective communication and feedback is required between water authorities and citizens to ensure minimum engagement levels and to minimize the intrinsic low-variable accuracy of crowdsourced observations.

Citation: Mazzoleni, M., Cortes Arevalo, V. J., Wehn, U., Alfonso, L., Norbiato, D., Monego, M., Ferri, M., and Solomatine, D. P.: Towards assimilation of crowdsourced observations for different levels of citizen engagement: the flood event of 2013 in the Bacchiglione catchment, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2017-59, in review, 2017.
Maurizio Mazzoleni et al.
Maurizio Mazzoleni et al.
Maurizio Mazzoleni et al.

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Short summary
We assess the usefulness of assimilating crowdsourced observations, from a heterogeneous network of sensors, in a cascade of hydrological and hydraulic models during the flood event occurred in the Bacchiglione catchment on May 2013. Different sets of experiments are considered. We demonstrated how citizen engagement level scenarios moved by a feeling of belonging to a community of friends indicated flood prediction improvements when such small communities are located upstream a target point.
We assess the usefulness of assimilating crowdsourced observations, from a heterogeneous network...
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