The May 2024 Flood Disaster in Southern Brazil: Causes, Impacts, and SWOT‐Based Volume Estimation

In May 2024, southern Brazil experienced a severe flood that caused widespread devastation, particularly in the metropolitan area of Porto Alegre. This disaster resulted from a rare combination of atmospheric conditions: a heatwave stalled a cold front, leading to prolonged and intense rainfall. The flood claimed 183 lives, left 27 missing, and displaced many more. Notably, the flood's peak coincided with satellite observations from both SWOT and Sentinel‐2, providing a valuable snapshot of the disaster. To assess the flood's scope, and volume, we integrate these satellite data with FABDEM topography. SWOT's water height measurements, evaluated with in situ data, underscore its flood monitoring potential. The estimated floodwater volume was 1.5 billion . While primarily damaging croplands, the flood directly affected 420,000 individuals in the study region, with 16% identified as socially vulnerable. These findings offer insights into floodwater distribution and contribute to future flood dynamics research, mitigation strategies, and disaster preparedness. Plain Language Summary In May 2024, the state of Rio Grande do Sul in southern Brazil faced a devastating flood, with the capital city, Porto Alegre, and its metro area being particularly hard‐hit. An unusual combination of weather conditions, including a heatwave that blocked a cold front, led to record‐breaking rainfall. This resulted in a disaster that claimed 183 lives, left 27 people missing, and displaced over 600,000 individuals from their homes in the whole state. To better understand the scale of the flooding, this study used advanced satellite data and topographic maps to measure how much water was involved, how deep the floodwaters were, and how far they reached. The findings showed that croplands were heavily affected, but within the city, over 420,000 people were directly impacted, including 67,000, especially vulnerable due to social and economic factors. The total volume of floodwater was estimated to be 1.5 billion cubic meters—enough to supply New York City for more than a year. This research helps us better understand the dynamics of floods and can be used to improve disaster preparedness and response in the future. Key Points Unusual high‐temperature anomalies and an atmospheric blocking caused unprecedented rainfall in south Brazil during May of 2024 Using a novel combination of satellite data, we assessed the extent and volume of flooded areas, showing SWOT's flood monitoring potential 16% of affected communities are socially vulnerable, emphasizing the urgent need for targeted climate disaster preparedness and mitigation

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UNC Libraries
Published
2025-02-27
DOI
https://doi.org/10.17615/5fqm-1x05
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
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article

The May 2024 Flood Disaster in Southern Brazil: Causes, Impacts, and SWOT‐Based Volume Estimation

Juliana Távora, Tamlin M. Pavelsky, Iury T. Simoes‐Sousa, Carolina M.L. Camargo et al.
UNC Libraries
Flood Risk Assessment and Management
article

The May 2024 Flood Disaster in Southern Brazil: Causes, Impacts, and SWOT‐Based Volume Estimation

Juliana Távora, Tamlin M. Pavelsky, Iury T. Simoes‐Sousa, Carolina M.L. Camargo, J. Thomas Farrar, Agata Piffer‐Braga
article en

Abstract

In May 2024, southern Brazil experienced a severe flood that caused widespread devastation, particularly in the metropolitan area of Porto Alegre. This disaster resulted from a rare combination of atmospheric conditions: a heatwave stalled a cold front, leading to prolonged and intense rainfall. The flood claimed 183 lives, left 27 missing, and displaced many more. Notably, the flood's peak coincided with satellite observations from both SWOT and Sentinel‐2, providing a valuable snapshot of the disaster. To assess the flood's scope, and volume, we integrate these satellite data with FABDEM topography. SWOT's water height measurements, evaluated with in situ data, underscore its flood monitoring potential. The estimated floodwater volume was 1.5 billion . While primarily damaging croplands, the flood directly affected 420,000 individuals in the study region, with 16% identified as socially vulnerable. These findings offer insights into floodwater distribution and contribute to future flood dynamics research, mitigation strategies, and disaster preparedness. Plain Language Summary In May 2024, the state of Rio Grande do Sul in southern Brazil faced a devastating flood, with the capital city, Porto Alegre, and its metro area being particularly hard‐hit. An unusual combination of weather conditions, including a heatwave that blocked a cold front, led to record‐breaking rainfall. This resulted in a disaster that claimed 183 lives, left 27 people missing, and displaced over 600,000 individuals from their homes in the whole state. To better understand the scale of the flooding, this study used advanced satellite data and topographic maps to measure how much water was involved, how deep the floodwaters were, and how far they reached. The findings showed that croplands were heavily affected, but within the city, over 420,000 people were directly impacted, including 67,000, especially vulnerable due to social and economic factors. The total volume of floodwater was estimated to be 1.5 billion cubic meters—enough to supply New York City for more than a year. This research helps us better understand the dynamics of floods and can be used to improve disaster preparedness and response in the future. Key Points Unusual high‐temperature anomalies and an atmospheric blocking caused unprecedented rainfall in south Brazil during May of 2024 Using a novel combination of satellite data, we assessed the extent and volume of flooded areas, showing SWOT's flood monitoring potential 16% of affected communities are socially vulnerable, emphasizing the urgent need for targeted climate disaster preparedness and mitigation

UNC Libraries
University of North Carolina at Chapel Hill (US)
Openalex Percentile: Top 73%
Flood Risk Assessment and Management
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