Geo-social media as a proxy for hydrometeorological data for streamflow estimation and to improve flood monitoring

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Abstract

Floods are one of the most devastating types of worldwide disasters in terms of human, economic, and social losses. If authoritative data is scarce, or unavailable for some periods, other sources of information are required to improve streamflow estimation and early flood warnings. Georeferenced social media messages are increasingly being regarded as an alternative source of information for coping with flood risks. However, existing studies have mostly concentrated on the links between geo-social media activity and flooded areas. Thus, there is still a gap in research with regard to the use of social media as a proxy for rainfall-runoff estimations and flood forecasting. To address this, we propose using a transformation function that creates a proxy variable for rainfall by analysing geo-social media messages and rainfall measurements from authoritative sources, which are later incorporated within a hydrological model for streamflow estimation. We found that the combined use of official rainfall values with the social media proxy variable as input for the Probability Distributed Model (PDM), improved streamflow simulations for flood monitoring. The combination of authoritative sources and transformed geo-social media data during flood events achieved a 71% degree of accuracy and a 29% underestimation rate in a comparison made with real streamflow measurements. This is a significant improvement on the respective values of 39% and 58%, achieved when only authoritative data were used for the modelling. This result is clear evidence of the potential use of derived geo-social media data as a proxy for environmental variables for improving flood early-warning systems.

Item Type: Journal Article
Subjects: G Geography. Anthropology. Recreation > GB Physical geography
H Social Sciences > HM Sociology
Divisions: Faculty of Social Sciences > Centre for Interdisciplinary Methodologies
Library of Congress Subject Headings (LCSH): Hydrometeorological services, Streamflow, Social media
Journal or Publication Title: Computers & Geosciences
Publisher: Pergamon
ISSN: 0098-3004
Official Date: 2018
Dates:
Date
Event
2018
Published
28 October 2017
Available
22 October 2017
Accepted
Volume: 111
Page Range: pp. 148-158
DOI: 10.1016/j.cageo.2017.10.010
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 1 November 2017
Date of first compliant Open Access: 1 November 2017
RIOXX Funder/Project Grant:
Project/Grant ID
RIOXX Funder Name
Funder ID
2017/15413-0
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
UNSPECIFIED
Fundação de Amparo à Pesquisa do Estado de São Paulo
UNSPECIFIED
Fundação Araucária de Apoio ao Desenvolvimento Científico e Tecnológico do Paraná
UNSPECIFIED
Secretário de Ciência, Tecnologia e Ensino Superior, Governo do Estado de Parana
Global Challenges Research Fund
[EPSRC] Engineering and Physical Sciences Research Council
#88887.091743/2014-01
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
#465501/2014-1
Conselho Nacional de Desenvolvimento Científico e Tecnológico
#2014/50848-9 & INCT–II
Fundação de Amparo à Pesquisa do Estado de São Paulo
#312056/2016-8
Conselho Nacional de Desenvolvimento Científico e Tecnológico
PPGSHS EESC USP
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Related URLs:
URI: https://wrap.warwick.ac.uk/94004/

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