How to Account for the Human Motion to Improve Flood Risk Assessment in Urban Areas

Abstract

Floods are critical disasters affecting urban areas and their users. Interactions with floodwater spreading and built environment features influence the users’ reaction to the emergency, especially during immediate disaster phases (i.e., evacuation). Recent studies tried to define simulation models to evaluate such exposure-related criticalities, assess individuals’ flood risk, and propose risk-mitigation strategies aimed at supporting the community’s proper response. Although they generally include safety issues (e.g., human body stability), such tools usually adopt a simplified approach to individuals’ motion representation in floodwaters, i.e., using input from non-specialized databases and models. This study provides general modelling approaches to estimate evacuation speed variations depending on individual’s excitement (walking, running), floodwaters depths and individuals’ features (age, gender, height, average speed on dry surfaces). The proposed models prefer a normalized evacuation speeds approach in respect of minimum motion constraint conditions to extend their applicability depending on the individuals’ characteristics. Speed data from previous experiments are organized using linear regression models. Results confirm how individuals’ speed reduces when depth and age increase. The most significant models are discussed to be implemented in evacuation simulation models to describe the evacuees’ motion in floodwaters with different confidence degree levels and then assess the community’s flood risk and risk-reduction strategies effectiveness.