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Assessing the utility of social media as a data source for flood risk management using a real-time modelling framework

Lookup NU author(s): Dr Luke Smith, Professor Qiuhua Liang, Professor Philip James, Dr Wen Lin

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

The utility of social media for both collecting and disseminating information during natural disasters is increasingly recognised. The rapid nature of urban flooding from intense rainfall means accurate surveying of peak depths and flood extents is rarely achievable, hindering the validation of urban flood models. This paper presents a real-time modelling framework to identify areas likely to have flooded using data obtained only through social media. Graphics processing unit (GPU) accelerated hydrodynamic modelling is used to simulate flooding in a 48km² area of Newcastle upon Tyne, with results automatically compared against flooding identified through social media, allowing inundation to be inferred elsewhere in the city with increased detail and accuracy. Data from Twitter during two 2012 flood events is used to test the framework, with the inundation results indicative of good agreement against crowd-sourced and anecdotal data, even though the sample of successfully geocoded Tweets was relatively small.

Publication metadata

Author(s): Smith L, Liang Q, James P, Lin W

Publication type: Article

Publication status: Published

Journal: Journal of Flood Risk Management

Year: 2017

Volume: 10

Issue: 3

Pages: 370-380

Print publication date: 01/09/2017

Online publication date: 27/03/2015

Acceptance date: 27/12/2014

Date deposited: 30/03/2015

ISSN (electronic): 1753-318X

Publisher: Wiley-Blackwell Publishing Ltd.

URL: http://dx.doi.org/10.1111/jfr3.12154

DOI: 10.1111/jfr3.12154

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