# Flood risk map from hydrological and mobility data: a case study in São Paulo (Brazil)

**Authors:** Lívia Rodrigues Tomás, Giovanni Guarnieri Soares, Aurelienne A. S. Jorge, Jeferson Feitosa Mendes, Vander L. S. Freitas, Leonardo B. L. Santos  
**arXiv:** [2204.05982](https://arxiv.org/abs/2204.05982)  
**Date:** 2022-04-10  
**Summary page:** https://www.summarizepaper.com/en/paper/2204.05982v1/

## Key points

- Cities facing flood risk due to conversion of natural land cover to built-up areas
- Road interruption as a major contributor to flood impacts in urban areas
- Zokagoa et al. proposed an urban flood risk map for São Paulo, Brazil
- Flood susceptibility estimated using Height Above the Nearest Drainage algorithm
- Potential impact assessed through exposure and vulnerability components
- Variables aggregated into a regular grid and classified into three classes: Moderate, High, and Very High
- Few cells fell into the Very High class for components other than flood susceptibility
- Scope for improvement in methodology by incorporating dynamic data capturing population movement
- Future investigations should include dynamic data considering how people move until they reach their destination
- Efforts should be made to develop an index calculating network vulnerability during an event
- Study area covered 115.3 km² of Tamanduateí river basin within São Paulo city
- Focus on 25 districts including historical center districts like Sé and República
- Data from various sources and geographic topologies used in the study
- Brazilian statistical grid chosen for integrating and analyzing data effectively over time
- Research contributes to understanding urban flood risk in São Paulo by providing a comprehensive assessment based on hydrological and mobility data

## Summary

Cities are increasingly facing flood risk due to the conversion of natural land cover to built-up areas with impervious surfaces, resulting in significant changes in hydrological patterns. Road interruption is a major contributor to flood impacts in urban areas. To address this issue, Zokagoa et al. proposed an urban flood risk map for the megacity of São Paulo, Brazil. The authors estimated flood susceptibility using the Height Above the Nearest Drainage algorithm and assessed potential impact through exposure and vulnerability components. These variables were aggregated into a regular grid and classified into three classes: Moderate, High, and Very High. Notably, except for flood susceptibility, few cells fell into the Very High class for other components. The flood susceptibility component was influenced by watercourses and played a crucial role in identifying cells classified as Very High risk. However, there is scope for improvement in the methodology by incorporating dynamic data that captures population movement towards their final destinations such as volumetric vehicle counting or crowdsourced data. Future investigations should include dynamic data that considers how people move until they reach their destination and efforts should be made to develop an index that can calculate network vulnerability by taking multiple elements into account during an event. The study area covered 115.3 km² of the Tamanduateí river basin within São Paulo city which experiences constant flooding along its impermeable riverbed due to high rainfall events. It focused on 25 districts within São Paulo city including its historical center comprising districts like Sé and República. Data from various sources and geographic topologies were used in this study with Brazilian statistical grid chosen as it serves as a receptacle for integrating and analyzing data effectively over time. This research contributes to understanding urban flood risk in São Paulo by providing a comprehensive assessment based on hydrological and mobility data which highlights the importance of considering all components when mapping urban flood risk - namely flood susceptibility, exposure and vulnerability.