Donoso et al. (2026) Uncovering the 2024 Rio Grande do Sul floods: land use change, extreme rainfall, and the urgent need for local adaptation in south Brazil

Identification

• Journal: Natural Hazards
• Year: 2026
• Date: 2026-01-01
• Authors: Verônica Garcia Donoso, Larissa Böhrkircher, Edimilson Rodrigues dos Santos, Michael Leuchner
• DOI: 10.1007/s11069-025-07776-1

Research Groups

• Federal University of Santa Maria (UFSM), Brazil
• Department of Geography, RWTH Aachen University, Germany
• São Carlos School of Engineering, University of São Paulo (USP), Brazil

Short Summary

This study integrates current spatial exposure, land-use patterns, and future precipitation projections to understand and prioritize flood adaptation needs in the Guaíba catchment, Rio Grande do Sul, finding that low-lying, densely populated areas with significant land-use change are disproportionately affected and face expanding flood risk due to projected rainfall increases.

Objective

• To identify the areas most affected by the extreme precipitation event and their locations.
• To characterize the principal changes in land use and land cover of the Guaíba catchment area from 1985 to 2023.
• To analyze underlying historical precipitation patterns and project their development in future climate scenarios.
• To identify priority areas within the study region where adaptation measures are most necessary and inform decision-making based on the analyses.

Study Configuration

• Spatial Scale: Guaíba catchment area, Rio Grande do Sul state, South Brazil (84,764 km²).
• Temporal Scale:
  • Flood event analysis: April–May 2024
  • Land Use and Land Cover (LULC) data: 1985–2023
  • Historical precipitation variability: 1981–2024
  • Future precipitation projections: 2011–2040, 2041–2070, 2071–2100 (with 1981–2010 as reference)

Methodology and Data

• Models used:
  • Height Above the Nearest Drainage (HAND) model (globally available, 30 m spatial resolution, 100-cell accumulation threshold)
  • CMIP6 climate projections from CHELSA V2 database (GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL) for SSP1-2.6, SSP3-7.0, and SSP5-8.5 scenarios.
  • Non-parametric Mann–Kendall (MK) test and Sen’s slope estimator for trend analysis of precipitation extremes.
• Data sources:
  • Publicly available satellite imagery (Sentinel 2, Planet Scope) for flood mapping.
  • Geographical data from Brazilian Institute of Geography and Statistics (IBGE) and Brazilian National Water and Basic Sanitation Agency (ANA).
  • Topographic data from Brazilian Agricultural Research Company (Embrapa) based on Shuttle Radar Topography Mission (SRTM) at 30 m spatial resolution.
  • Flood area database from Possantti et al. (2024) and Fonseca et al. (2024).
  • Land Use and Land Cover (LULC) maps from the MapBiomas project, Collection 9 (1985–2023).
  • CHIRPS v2.0 daily precipitation data (0.05° resolution, 1981–2024).
  • Oceanic Niño Index (ONI) data from ERSST V5 (NOAA/CPC) for ENSO analysis.

Main Results

• Flood Extent and Exposure: 87.9% of the total flooded area (777,822 hectares) had HAND ≤ 6 meters, with 67.2% (594,653 hectares) being ≤ 3 meters. The flood inundated 31.1% of all land with HAND ≤ 3 meters in the watershed.
• Affected Municipalities: The 20 most affected municipalities accounted for 67% of the inundated area with HAND ≤ 3 meters and 80% of the total affected area. Canoas (154,000 people) and Porto Alegre (151,000 people) had the highest number of affected individuals, while Eldorado do Sul (80%) and Estrela (46%) showed the highest percentage of affected populations.
• Land Use Change: From 1985 to 2023, the Guaíba watershed experienced significant expansion of anthropogenic land uses (agriculture, livestock, urban areas) at the expense of natural areas. Anthropogenic land use exceeded 50% of the entire watershed after 2019, reaching over 74% in low-lying affected areas (HAND ≤ 3 meters).
• Landslides: Landslides were concentrated along the higher-relief Serra Geral Escarpment and Campos Gerais Plateau, exclusively within Atlantic Forest ecoregions (77% in Alto Paraná Atlantic forests, 26 km²; 23% in Araucaria moist forests, 6 km²), with no occurrences in the Pampa ecoregion.
• Historical Precipitation Extremes: The 2024 annual maximum 5-day consecutive precipitation (RX5day) reached 256.5 mm, significantly exceeding the historical range (70–180 mm) from 1981 to 2023. The number of very heavy precipitation days (R50mm) reached an all-time high of 8 days in 2024. RX5day shows a statistically significant upward trend of +0.78 mm per year (p = 0.036).
• Future Precipitation Projections: Multi-model means project a general increase in monthly precipitation until 2100, particularly in austral autumn (April–June) and spring (October–December). By 2100, annual precipitation is projected to increase basin-wide, with the strongest gains in the central to north-eastern highlands. Under the SSP5-8.5 scenario, annual precipitation is projected to rise by 190–460 mm (more than 13%) by 2100.
• Flood Risk Gradient: The study delineates a north–south directed flood-risk gradient, where intense precipitation generated along the northern escarpment (hazard-generation zone) rapidly translates into runoff that converges downstream into the flood-prone Central Gaúcho Depression (exposure/damage zone).

Contributions

• Integrates current spatial exposure (using HAND and high-resolution flood mapping), land-use dynamics, and future climate projections into a spatially explicit framework for flood-risk management.
• Provides an evidence-based prioritization framework for identifying critical zones and informing anticipatory planning for climate adaptation in the Guaíba catchment.
• Offers a complementary, inductive framework for flood risk assessment that can be applied in other regions, particularly in data-scarce contexts, by utilizing globally available terrain models like HAND.

Funding

• The Alexander von Humboldt Foundation (Experienced Researcher Fellowship Grant, for the first author).

Citation

@article{Donoso2026Uncovering,
  author = {Donoso, Verônica Garcia and Böhrkircher, Larissa and Santos, Edimilson Rodrigues dos and Leuchner, Michael},
  title = {Uncovering the 2024 Rio Grande do Sul floods: land use change, extreme rainfall, and the urgent need for local adaptation in south Brazil},
  journal = {Natural Hazards},
  year = {2026},
  doi = {10.1007/s11069-025-07776-1},
  url = {https://doi.org/10.1007/s11069-025-07776-1}
}