Using web-based observations to identify thresholds of a person's stability in a flow

Flood risk assessment and mitigation are important tasks that should take advantage of rational vulnerability models to increase their effectiveness. These models are usually identified through a relevant set of laboratory experiments. However, there is growing evidence that these tests are not fully representative of the variety of conditions that characterize real flood hazard situations. This paper suggests a citizen science based and innovative approach to obtain information from web resources for the calibration of people's vulnerability models. A comprehensive study employing commonly-used web engines allowed the collection of a wide set of documents showing real risk situations for people impacted by flood, classified according to the stability of the involved subjects. A procedure to extrapolate the flow depth and velocity from the video frames is developed and its reliability is verified by comparing the results with observation. The procedure is based on the statistical distribution of the population height employing a direct uncertainty propagation method. The results complement the experimental literature data and conceptual models. The growing availability of online information will progressively increase the sample size of the sample on which the procedure is based and will eventually lead to the identification of a probability surface describing the transition between stability and instability conditions of individuals in a flow.