Development of a Flash Flood Confidence Index from Disaster Reports and Geophysical Susceptibility
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.
Kruczkiewicz, A.; et al.
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