Geospatial Analysis of Population Exposure to Flooding in the Sudd Region, South Sudan

Journal article

The Sudd wetland in South Sudan extends over 90,000 km2. Large‐scale flood events in recent years (2019–2022) are said to have led to the displacement of an estimated 1.8 million people in total. However, these estimates are approximate and to date there has not been a systematic analysis of population exposure to flooding in the Sudd region. This study seeks to address this gap by using global flood modeling, satellite observations of flood extent, and global gridded population datasets to analyze population exposure. Recognizing the inevitable limitations of these datasets, we intersect all the available global flood mapping and population datasets. The results indicate that 0.8–2.9 million people are currently exposed to the 100‐year return period flood extent, depending on the flood model and population dataset used. Aggregated results of the model agreement intercomparison indicate that all five global models agree on key flood‐prone areas within and around the Sudd, which is further corroborated with satellite flood observations. Intercomparison of the population density among the four georeferenced population products demonstrates that WorldPop and GHSL‐Pop population distributions better represent the patterns of the Sudd rural settlements that are typically in forms of clusters. The uncertainty in exposure estimates is attributable to variations in both flood outlines and geospatial population estimates. These findings provide hitherto unavailable insights into flood exposure in South Sudan, to inform flood management decisions and disaster reduction responses in the Sudd region. This study demonstrates the global significance of model intercomparison as best practice for any flood exposure analysis to underpin policy and decision‐making in Africa and other data‐scarce regions.

Authors: Chol, DM; Hall, JW; Wheeler, KG; Bernhofen, M; Di Vittorio, CA

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: Journal of Flood Risk Management
• Volume: 19
• Issue: 1
• Article number: e70168
• Publication date: 2026-01-04
• Acceptance date: 2025-12-17
• DOI: 10.1111/jfr3.70168
• EISSN: 1753318X
• ISSN: 1753318X
• Language: English
• Keywords: model intercomparison; South Sudan; population exposure; Sudd region; flood hazards