Assessment of crowdsourced social media data and numerical modelling as complementary tools for urban flood mitigation

ABSTRACT

This paper explores how crowdsourced social media data complements urban flood modelling to improve model performance and achieve a better classification of impacts. In addition to georeferencing flood impacts, Twitter allows monitoring the events in terms of hazards and impacts, and YouTube facilitates a retrospective analysis from audiovisual data. The analysis of 2800 tweets collected during four storm events and of almost 900 videos of the recent history of the basin, together with the implementation of a high-resolution model, contributed to the expansion of the capacity to represent the temporal and spatial scales of the problem. The complementation of crowdsourced social media data and urban modelling enhances the understanding of the flood dynamics, thus offering a framework of greater certainty for the generation of flood risk management products.

KEYWORDS:

• crowdsourcing
• Twitter
• YouTube
• numerical modelling
• large urban basin
• floods

Editor S. Archfield Guest editor F. Nardi

Editor S. Archfield Guest editor F. Nardi

Acknowledgements

Financial support for the work was provided by the Secretaría de Ciencia y Técnica de la Universidad de Buenos Aires (Grant UBACyT 20020190200132BA, Analysis of urban flood impacts using numerical modelling and citizen information). The authors are grateful to Marcelo Uriburu Quirno for his comments on a draft of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Secretaria de Ciencia y Tecnica, Universidad de Buenos Aires [UBACyT 20020190200132BA].