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 over time. Disaster databases are potentially useful tools for exploring trends, however, criteria inclusion associated descriptive characteristics not standardized. For example, some include only primary types, such as ‘flood’, while others subtypes, ‘coastal flood’ ‘flash flood’. Here we outline method to identify candidate assignment specific subtype—namely, floods’—from the corresponding type—namely, ‘flood’. Geophysical data, including variables derived from remote sensing, integrated develop an enhanced flash flood confidence index, consisting both index based on text mining reports susceptibility sensing geophysical data. This was applied event dataset covering Ecuador. Results indicate potential value disaggregating labeled type into particular subtype. outputs reduction vulnerability assessment if appropriately evaluated fitness use.