A behavioural model for quantifying flood warning effectiveness

Abstract

The extent of losses avoided as a result of a warning is a key measure of warning
\nsystem effectiveness. Tools to estimate the impact of warnings on losses are limited
\nto postflood analysis or estimates of potential rather than actual damages. This
\npaper illustrates a method for the appraisal of actual damages when a flood
\nwarning is issued. The approach combines social science with engineering
\napproaches to the problem of flood warning effectiveness. From a starting point
\nof estimating potential damages by means of depth–damage curves, the method
\nallows the identification of damage reduction by modelling how people respond to
\nthe warning. The model is in the form of an event tree representing human
\nbehavioural steps in the flood warning process. Two Australian case studies show
\nhow to apply the developed methodology. The results from these cases demonstrate
\nthe utility of the event-tree model that also allows the identification of weak
\nlinks in the warning chain.