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

• Main Authors: Andrew Kruczkiewicz, Agathe Bucherie, Fernanda Ayala, Carolynne Hultquist, Humberto Vergara, Simon Mason, Juan Bazo, Alex de Sherbinin
• Format: Article
• Language: English
• Published: MDPI AG 2021-07-01
• Series: Remote Sensing
• Subjects: flash flood; disaster risk reduction; historical disaster database; flood characterization; geomorphology; geospatial analysis
• Online Access: https://www.mdpi.com/2072-4292/13/14/2764

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.