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Solomatine DP (2018) Exploring the influence of citizen involvement on the assimilation of
crowdsourced observations: a modelling study based on the 2013 flood event in the
Bacchiglione catchment (Italy). Hydrol Earth Syst Sci 22:391–416. https://doi.org/10.5194/
hess-22-391-2018
62. Mazzoleni M, Verlaan M, Alfonso L, Monego M, Norbiato D, Ferri M, Solomatine DP (2017)
Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?
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63. Mazzoleni M (2017) Improving flood prediction assimilating uncertain crowdsourced data into
hydrologic and hydraulic models. UNESCO-IHE PhD thesis series, CRC Press/Balkema,
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Integration of information technology systems for flood forecasting with hybrid data sources.
International conference of flood management, Sao Paolo, Brazil
48. Fohringer J, Dransch D, Kreibich H, Schröter K (2015) Social media as an information source
for rapid flood inundation mapping. Nat Hazards Earth Syst Sci 15:2725–2738. https://doi.org/
10.5194/nhess-15-2725-2015
49. Gaitan S, van de Giesen NC, ten Veldhuis JAE (2016) Can urban pluvial flooding be predicted
by open spatial data and weather data? Environ Model Softw 85:156–171. https://doi.org/10.
1016/j.envsoft.2016.08.007
50. Giuliani M, Castelletti A, Fedorov R, Fraternali P (2016) Using crowdsourced web content for
informing water systems operations in snow-dominated catchments. Hydrol Earth Syst Sci
20:5049–5062. https://doi.org/10.5194/hess-20-5049-2016
51. Rollason E, Bracken LJ, Hardy RJ, Large ARG (2018) The importance of volunteered geographic information for the validation of flood inundation models. J Hydrol 562:267–280
52. Rosser JF, Leibovici DG, Jackson MJ (2017) Rapid flood inundation mapping using social
media, remote sensing and topographic data. Nat Hazards 87:103–120
53. Schneider P, Castell N, Vogt M, Dauge FR, Lahoz W, Bartonova A (2017) Mapping urban air
quality in near real-time using observations from lowcost sensors and model information.
Environ Int 106:234–247
54. Smith L, Liang Q, James P, Lin W (2015) Assessing the utility of social media as a data source
for flood risk management using a real-time modelling framework. J Flood Risk Manag
10:370–380. https://doi.org/10.1111/jfr3.12154
55. Starkey E, Parkin G, Birkinshaw S, Large A, Quinn P, Gibson C (2017) Demonstrating the
value of community-based (“citizen science”) observations for catchment modelling and characterisation. J Hydrol 548:801–817. https://doi.org/10.1016/j.jhydrol.2017.03.019
56. Yu D, Yin J, Liu M (2016) Validating city-scale surface water flood modelling using crowdsourced data. Environ Res Lett 11:124011. https://doi.org/10.1088/1748-9326/11/12/124011
57. Le Coz J, Patalano A, Collins D, Guillén NF, García CM, Smart GM, Bind J, Chiaverinica A,
Le Boursicauda R, Dramaisa G, Braud I (2016) Crowdsourced data for flood hydrology:
feedback from recent citizen science projects in Argentina, France and New Zealand. J Hydrol
541:766–777
58. Assumpção TH, Popescu I, Jonoski A, Solomatine DP (2018) Citizen observations contributing
to flood modelling: opportunities and challenges. Hydrol Earth Syst Sci 22:1473–1489. https://
doi.org/10.5194/hess-22-1473-2018
59. Shanley L, Burns R, Bastian Z, Robson E (2013) Tweeting up a storm: the promise and perils of
crisis mapping, available SSRN 2464599. https://ssrn.com/abstract¼2464599. Accessed
20 Mar 2016
60. Mazzoleni M, Alfonso L, Chacon-Hurtado J, Solomatine D (2015) Assimilating uncertain,
dynamic and intermittent streamflow observations in hydrological models. Adv Water Resour
83:323–339
61. Mazzoleni M, Cortes Arevalo VJ, Wehn U, Alfonso L, Norbiato D, Monego M, Ferri M,
Solomatine DP (2018) Exploring the influence of citizen involvement on the assimilation of
crowdsourced observations: a modelling study based on the 2013 flood event in the
Bacchiglione catchment (Italy). Hydrol Earth Syst Sci 22:391–416. https://doi.org/10.5194/
hess-22-391-2018
62. Mazzoleni M, Verlaan M, Alfonso L, Monego M, Norbiato D, Ferri M, Solomatine DP (2017)
Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?
Hydrol Earth Syst Sci 21:839–861. https://doi.org/10.5194/hess-21-839-2017
63. Mazzoleni M (2017) Improving flood prediction assimilating uncertain crowdsourced data into
hydrologic and hydraulic models. UNESCO-IHE PhD thesis series, CRC Press/Balkema,
Leiden
232
M. Mazzoleni et al.