Unknown risk

Assessing refugee camp flood risk in Ethiopia

Bibliographic Data

ID15549166
AuthorsMark Bernhofen (0000-0002-4919-0111, University of Leeds, corresponding author), Faye Blenkin (University of Leeds), Mark A Trigg (0000-0002-8412-9332, University of Leeds, corresponding author)
Year2023
Volume18
Issue6
Pages064041-064041
Publication date2023-05-25
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironmental Research Letters (JOURNAL)
Journal identifiersISSN: 1748-9326 • E-ISSN: 1748-9326
PublisherIOP Publishing (PUBLISHER • GB)
DOI10.1088/1748-9326/acd8d0
OpenAlexW4378190969
LanguageEN
Citations received1
References cited35

The number of global refugees has been rising annually for the last decade. Many of these refugees are housed within camps, in temporary structures, vulnerable to the impacts of flooding. The flood risk of refugees is not well understood. Flood risk guidance available for camp planners and managers is vague, and existing flood risk data is often lacking in the remote areas where camps are typically located. We show how global data should, and should not, be used to assess refugee flood risk in Ethiopia; a country hosting 725 000 refugees, primarily from four neighboring countries, in 24 camps. We find that global population (GP) datasets, typically used in national flood risk assessments, do not accurately capture camp populations (CPs). Even the most accurate GP datasets are missing three fifths of camp flood exposure. We propose, and test, alternative approaches for representing exposure that combine reported estimates of CP with data on camp area, building footprints, and population density. Applying these approaches in our national flood risk assessment, we find that 95.8% of camps in Ethiopia are exposed to flooding of some degree and between 143 208 (19.8%) and 182 125 refugees (25.2%) are exposed to a 1% annual exceedance probability flood (100 year return period). South Sudanese refugees are the nationality most exposed to flooding, but Eritrean refugees are the nationality most exposed to flooding with a high risk to life. Promisingly, we find that many camps may be set up in such a way that reduces the exposure of refugees to flooding. Our study demonstrates that global data, augmented with local data, can be useful for understanding the flood risk of refugee camps. The consistent scalable approach can be used as a first-order analysis of risk, identifying risk hotspots, and help to prioritize further detailed analyses to inform within-camp adaptation

Computer security · Environmental health · Flood myth · Flood risk assessment · Flooding (psychology · Geography · Immigration · Nationality · Population · Refugee · Risk assessment · Socioeconomics · Sociology · Climate Change, Adaptation, Migration · Computer Science · Disaster Management and Resilience · Flood Risk Assessment and Management · Medicine

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