A Conceptual Prototype of an Urban Flood Early Warning System with High Spatial Resolution: A Study Case in São Paulo City

In 2022, the global population reached 8 billion, with 55% residing in urban areas. Projections for 2050 anticipate a growth to 9.77 billion, with approximately 6.6 billion people (nearly 68% of the world’s population) living in cities. Urban flooding emerges as a hazardous phenomenon affecting both developed and developing nations, endangering human lives and causing damage to properties, environmental degradation, and disruptions in economic and social activities, such as transportation systems and urban mobility. Addressing this challenge, Flood Early Warning Systems (FEWSs) can play a vital role in mitigating flood risks, enhancing absorptive capacity, and minimizing the impact of hazards, ultimately reducing the loss of life.

In this context, this project aims to create a prototype for a high spatial resolution flood early warning system that will identify flooding hotspots or zones in a pilot area (São Paulo City) and provide flood lead time at the urban micro-basins scale. The project will verify flood alerts by employing artificial intelligence (AI) methods. Furthermore, innovatively, the state of the art in this context will be explored for the national scenario. The anticipated outcomes are real-time geo-information of areas with higher flood risk, offering critical insights for effective response during such events. The project will advance scientific knowledge in this domain and provide a practical support tool for Civil Defense agents, decision-makers, and policymakers. The conceptual prototype developed in this initiative is envisaged to serve as a valuable resource for São Paulo City. Providing timely information empowers authorities to make informed decisions to contain and mitigate the impact of floods, fostering resilience in the face of this pressing environmental challenge.