Porto Alegre Submerged in Floods: Brazil Hit by Torrential Rains Causing Devastating Flooding

An image from a satellite revealing the flood-stricken downtown district of Porto Alegre was taken on May 8, 2024. This picture was captured by the Operational Land Imager on Landsat 8.

The southernmost state of Brazil, Rio Grande do Sul, has been severely affected by flooding resulted from heavy rains. NASA has been supplying crucial satellite data to aid in the relief efforts, stressing the wider context of climate change that precipitates such extreme weather incidents.

Beginning on April 27, 2024, severe storms characterized by high winds and heavy rainfall started battering Rio Grande do Sul, leading to over 300 millimeters (12 inches) of rainfall in less than a week. Subsequently, river banks were overflown leading to widespread catastrophic flooding.

The flooded downtown area of Porto Alegre was captured on May 8, 2024, by the Landsat 8's OLI (Operational Land Imager). The floodwater led to shutting down of the international airport, disruption of major stadiums, closure of several highways and inundation of the historic downtown area.

Two images shot by the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra and Aqua satellites on May 6 and April 20, 2024, showed the before and during flooding scenarios. Porto Alegre and several upstream towns and cities were heavily flooded as water overflew the banks of the Jacuí, Cai, and Sinos rivers. Runoff, muddied with suspended sediments is visibly flowing into the Patos Lagoon located south of Porto Alegre.

The May 6 and April 20, 2024, images of the flooding before and during stages were captured by the Moderate Resolution Imaging Spectroradiometer on NASA's Terra and Aqua satellites.

Over 160,000 people have been displaced due to the severe flooding causing havoc throughout the Rio Grande do Sul state. Numerous casualty reports have been filed and confirmed by the state’s civil defense agency. Export industries and large producers of soy, rice, wheat, and meat have been significantly affected by the flooding. Farmers are also reporting heavy damage in various regions, and potential disruption in grain exports due to damage to storage facilities, transportation infrastructure and ports is anticipated.

The weakening El Niño is deemed partially responsible for the extreme rain events as per Brazil’s National Institute of Meteorology (INMET). This event has steered cold fronts towards Rio Grande do Sul and amplified atmospheric instability over the state. Humidity levels have been elevated due to unnaturally warm South Atlantic Ocean waters, intensifying the storms through a clash of warm, humid air from the Amazon and colder air to the south of the state.

Scientific projections based on continuously increasing atmospheric concentrations of carbon dioxide and other greenhouse gases anticipate an increase in annual precipitation totals and annual 5-day precipitation maximums in South America by 2050, per the Intergovernmental Panel on Climate Change’s Sixth Assessment Report. These projections are derived from the simulations of the CMIP-6 (Coupled Model Intercomparison Project) multi-model ensemble that includes modeling results from the GISS ModelE, a circulation model developed by NASA’s Goddard Institute for Space Studies.

NASA's Global Flood Product visually portrays extensive flooding in Rio Grande do Sul witnessed after the heavy downpours on May 6, 2024. This 1-day product presents active floods in red color and regular surface water in blue color.

NASA's Earth Applied Sciences Disasters program area is actively aiding in responding to the flooding event. Satellite data is being utilized to locate landslides, map powerless regions, and as new information becomes available, it will be shared via the open-access mapping portal. NASA’s MODIS Near Real-Time Global Flood product is one such tool, it demonstrated the widespread flooding in and around the city on May 6, 2024.

The satellite images of the Earth Observatory produced by NASA have been created by Wanmei Liang and use MODIS data from NASA EOSDIS LANCE and GIBS/Worldview along with Landsat data acquired from the U.S. Geological Survey.