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

ABSTRACT The Sudd wetland in South Sudan extends over 90,000 km 2 . 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.

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Publication Details

Journal
Journal of Flood Risk Management
Published
2026-01-04
DOI
https://doi.org/10.1111/jfr3.70168
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Kenneth Marc Strzepek, Mark Bernhofen, Kevin Wheeler, Courtney A. Di Vittorio et al.
Journal of Flood Risk Management
Flood Risk Assessment and Management
article

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

Kenneth Marc Strzepek, Mark Bernhofen, Kevin Wheeler, Courtney A. Di Vittorio, Deng Majok Chol, Jim W. Hall
article en

Abstract

ABSTRACT The Sudd wetland in South Sudan extends over 90,000 km 2 . 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.

Journal of Flood Risk ManagementVol. 19(1)
Stockholm Environment Institute (GB), University of Oxford (GB), IIT@MIT (US), Wake Forest University (US), Ball (France) (FR)
Foreign, Commonwealth and Development Office
Climate action
Openalex Percentile: Top 98%
Flood Risk Assessment and Management
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