Articles | Volume 17, issue 5
https://doi.org/10.5194/nhess-17-735-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-17-735-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
19 May 2017
Research article |
| 19 May 2017
Probabilistic flood extent estimates from social media flood observations
Tom Brouwer
Deltares, Delft, Boussinesqweg 1, 2629 HV, the Netherlands
Dept. of Water Engineering and Management, University of Twente,
Enschede, Drienerlolaan 5, 7522NB, the Netherlands
Deltares, Delft, Boussinesqweg 1, 2629 HV, the Netherlands
Arnejan van Loenen
Deltares, Delft, Boussinesqweg 1, 2629 HV, the Netherlands
Martijn J. Booij
Dept. of Water Engineering and Management, University of Twente,
Enschede, Drienerlolaan 5, 7522NB, the Netherlands
Kathelijne M. Wijnberg
Dept. of Water Engineering and Management, University of Twente,
Enschede, Drienerlolaan 5, 7522NB, the Netherlands
Jan S. Verkade
Deltares, Delft, Boussinesqweg 1, 2629 HV, the Netherlands
Jurjen Wagemaker
FloodTags, The Hague, Binckhorstlaan 36, 2511 BE, the Netherlands
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- Post‐event flood mapping for road networks using taxiGPSdata X. Kong et al. 10.1111/jfr3.12799
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- Using social media to measure impacts of named storm events in the United Kingdom and Ireland M. Spruce et al. 10.1002/met.1887
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Short summary
The increasing number and severity of floods, driven by e.g. urbanization, subsidence and climate change, create a growing need for accurate and timely flood maps. At the same time social media is a source of much real-time data that is still largely untapped in flood disaster management. This study illustrates that inherently uncertain data from social media can be used to derive information about flooding.
The increasing number and severity of floods, driven by e.g. urbanization, subsidence and...
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