Unknown risk: assessing refugee camp flood risk in Ethiopia

Mark V Bernhofen, Faye Blenkin, and Mark A Trigg

Environmental Research Letters, Volume 18, Number 6 (2023) 

http://dx.doi.org/10.1088/1748-9326/acd8d0

Review

This article explores different approaches for using global data to assess refugee flood risk in refugee camps in Ethiopia. Ethiopia hosts over 870 000 refugees from Sudan, South Sudan, Eritrea, and Somalia, most of whom (90 percent) live in refugee camps. Refugee camps in Ethiopia have a history of flooding, and flood rick is expected to increase with climate change. 

The authors test various approaches to assessing floor risk exposure that combine estimates of camp population with data on camp area, building footprints, and population density. The authors map 24 refugee camps in Ethiopia using a combination of country-level information from UNHCR, remote sensing data, OpenStreetMap data, and building footprint data.  

The authors also assess the accuracy of global population datasets at capturing refugee camp populations in Ethiopia, by comparing population estimates for the geographical cells within the camp boundaries to UNHCR population data. The global population datasets used were the Global Human Settlement Population 2019 and 2022 revisions (GHS-POP R2019 and GHS-POP R2022), Facebook High Resolution Settlement Layer (HRSL), LandScan, WorldPop unconstrained and constrained.  

Main findings: 

  • Global population datasets, typically used in national flood risk assessments, chronically underestimate refugee camp populations in Ethiopia. In the 24 camps examined, global population datasets estimated, on average, only 27 percent of the refugee camp population reported by UNHCR. Global population datasets rely on census data which typically do not include refugees and are not updated frequently enough to capture dynamic refugee flows. The two most accurate global population maps were GHS-POP R2022 and HRSL, which captured only 44 percent and 36 percent of the UNHCR reported camp populations, respectively. 
  • The approach used to calculate flood exposure has a significant impact on flood exposure estimates. Even the most accurate global population maps underpredict between three-fifths and two-thirds of flood exposed refugees, relative to approaches which incorporate UNHCR camp population data.  
  • Almost all refugee camps are exposed to flooding. Augmenting global data with local data on refugee camp populations, it is estimated that 23 out of 24 refugee camps are exposed to flooding of some degree, and between 143,208 (20 percent) and 182,125 (25 percent) refugees are exposed to a 1 percent annual exceedance probability flood (100-year return period flood). Four of the five most exposed camps are in the Gambela region, which is one of the most flood-prone regions in the country. The camps in Gambela are home to South Sudanese refugees, who are disproportionately more exposed to flooding than other refugees in Ethiopia.  Most refugees in Ethiopia are exposed to pluvial (rainfall) flooding, and the majority of this (80 to 85 percent) exposure is a low risk to life. Eritrean refugees are the nationality most exposed to flooding with a high risk to life. 
  • Camp planners appear to be making rational decisions about the internal organization of camps with respect to potential flood exposure. Incorporating information on the spatial distribution of camp residents into flood exposure analysis, led to substantially lower estimates of average annual exposure, suggesting that camp planners are making rational decisions about the internal organization of camps with respect to potential flood exposure. 

The authors conclude that global population datasets do a poor job at estimating refugee camp populations and should not be used in studies of refugee flood risk. The analysis demonstrates the benefits of combining local and global data for assessing refugee camp flood risk in Ethiopia. This kind of analysis can be useful for understanding the degree of risk faced by refugees in a country and for prioritizing further detailed risk analyses.