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Abstract:
Human safety is seriously threatened due to extreme events such as floods in urban areas. To assess people's exposure to the risk of being swept away by strong water flows, we employed the HydroPol2D cellular automata-based model to calculate flow velocity and water depth, a fully distributed, explicit diffusive model. We enhanced accuracy and reduced execution time, for this, we developed a craving method (Forward-Mole) to correct digital elevation data, and also a modified Courant-Friedrichs–Lewy criterion. Furthermore, we compared two methods (physical and empirical-based models) to assess human instability flooding risk in the Franquiho Watershed in the Metropolitan Area of São Paulo, Brazil. Results indicate that data correction and modified numerical stability criteria improve accuracy and reduce execution time for the HydroPol2D model. Related to the human instability, although the nature of the assessment model to estimate the risk of being dragged by the floods, according to both approaches, there is a risk of human instability within the FW, but the extent of the area differs. In summary, the empirical human stability method was more critical than the physics-based method. The results of this study highlight areas of potential injuries and fatalities due to human instability, herein, this could improve decision-making and better city planning to tackle probable future changes in climate, emphasizing the need for measures to safeguard urban areas against extreme events.
