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Article

Development of a Flash Flood Confidence Index from Disaster Reports and Geophysical Susceptibility

1
International Research Institute for Climate and Society (IRI), The Earth Institute at Columbia University, Palisades, NY 10964, USA
2
Red Cross Red Crescent Climate Centre, 2953 The Hague, HT, The Netherlands
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Faculty of Geo-Information Science and Earth Observation, University of Twente, 7514 Enschede, AE, The Netherlands
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Disaster Risk Department, Ecuadorian Red Cross (CRE), Quito 170403, Ecuador
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Center for International Earth Science Information Network (CIESIN), The Earth Institute at Columbia University, Palisades, NY 10964, USA
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Cooperative Institute for Mesoscale Meteorological Studies (CIMMS), The University of Oklahoma, Norman, OK 73019, USA
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NOAA National Severe Storms Laboratory (NSSL), Norman, OK 73072, USA
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Universidad Tecnológica de Peru (UTP), Lima 15046, Peru
*
Author to whom correspondence should be addressed.
Academic Editors: Xinyi Shen, Albert J. Kettner, Sagy Cohen and Yiwen Mei
Remote Sens. 2021, 13(14), 2764; https://doi.org/10.3390/rs13142764
Received: 13 May 2021 / Revised: 25 June 2021 / Accepted: 29 June 2021 / Published: 14 July 2021
The analysis of historical disaster events is a critical step towards understanding current risk levels and changes in disaster risk over time. Disaster databases are potentially useful tools for exploring trends, however, criteria for inclusion of events and for associated descriptive characteristics is not standardized. For example, some databases include only primary disaster types, such as ‘flood’, while others include subtypes, such as ‘coastal flood’ and ‘flash flood’. Here we outline a method to identify candidate events for assignment of a specific disaster subtype—namely, ‘flash floods’—from the corresponding primary disaster type—namely, ‘flood’. Geophysical data, including variables derived from remote sensing, are integrated to develop an enhanced flash flood confidence index, consisting of both a flash flood confidence index based on text mining of disaster reports and a flash flood susceptibility index from remote sensing derived geophysical data. This method was applied to a historical flood event dataset covering Ecuador. Results indicate the potential value of disaggregating events labeled as a primary disaster type into events of a particular subtype. The outputs are potentially useful for disaster risk reduction and vulnerability assessment if appropriately evaluated for fitness of use. View Full-Text
Keywords: flash flood; disaster risk reduction; historical disaster database; flood characterization; geomorphology; geospatial analysis; Ecuador; disaster management; text analytics; early warning system; climate informed decision making; flood risk flash flood; disaster risk reduction; historical disaster database; flood characterization; geomorphology; geospatial analysis; Ecuador; disaster management; text analytics; early warning system; climate informed decision making; flood risk
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MDPI and ACS Style

Kruczkiewicz, A.; Bucherie, A.; Ayala, F.; Hultquist, C.; Vergara, H.; Mason, S.; Bazo, J.; de Sherbinin, A. Development of a Flash Flood Confidence Index from Disaster Reports and Geophysical Susceptibility. Remote Sens. 2021, 13, 2764. https://doi.org/10.3390/rs13142764

AMA Style

Kruczkiewicz A, Bucherie A, Ayala F, Hultquist C, Vergara H, Mason S, Bazo J, de Sherbinin A. Development of a Flash Flood Confidence Index from Disaster Reports and Geophysical Susceptibility. Remote Sensing. 2021; 13(14):2764. https://doi.org/10.3390/rs13142764

Chicago/Turabian Style

Kruczkiewicz, Andrew, Agathe Bucherie, Fernanda Ayala, Carolynne Hultquist, Humberto Vergara, Simon Mason, Juan Bazo, and Alex de Sherbinin. 2021. "Development of a Flash Flood Confidence Index from Disaster Reports and Geophysical Susceptibility" Remote Sensing 13, no. 14: 2764. https://doi.org/10.3390/rs13142764

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