Author(s): Marco Rodrigo Lopez Lopez; Adrian Pedrozo-Acuna
Linked Author(s): Adrián Pedrozo Acuña
Keywords: Predictive modeling; Cellular automata; Ensemble rainfall forecasts; Urban flood management
Abstract: Extreme rainfall events and urban flooding are becoming increasingly frequent worldwide, intensifying the need for reliable forecasting tools that support risk-informed decision-making. Urban areas with complex hydrological conditions and high population density are especially vulnerable to flood impacts and require predictive systems capable of issuing timely and reliable warnings. This study evaluates the feasibility of generating probabilistic rainfall and flood forecasts by integrating historical observations with numerical weather prediction outputs, coupled with a cellular automata–based flood simulation model, applied in Mexico City. Results show that flood probability maps with lead times of up to 72 hours can be produced at street-level resolution, enabling detailed identification of areas with elevated inundation risk. These findings represent a significant step toward improving operational decision-making and strengthening early warning capabilities for urban flood risk management.
Year: 2026