Tackling loss and damage: who is most vulnerable to disaster displacement?

Drawing on recent research, Simon Addison and Sam Barrett explain why disaster displacement risk assessments must integrate better quality data on the specific vulnerabilities of different people to escalating climate risks.

Simon Addison's picture Sam Barrett's picture
Insight by 
Simon Addison
Sam Barrett
Simon Addison is principal researcher in IIED’s Climate Change research group; Sam Barrett is researcher in IIED's Natural Resources research group
17 November 2021
UN climate change conference (COP26)
A series of pages related to IIED's activities at the 2021 UNFCCC climate change summit in Glasgow
Piles of bags and jerrycans. Men pick some of them up.

Food distribution to those affected by flooding in Beletweyne, Somalia, leading to the displacement of 17,000 people (Photo: Tobin Jones via FlickrCC0 1.0)

At COP26, vulnerable developing countries highlighted the urgent need to address loss and damage caused by climate-related disasters, and for their international donor partners to step up and provide significant financial support for them to do so.

The COP also drove home how population displacement caused by extreme weather events is now one of the most pressing forms of loss and damage and needs immediate attention.

The number of people affected by climate- and weather-related disasters has more than tripled since the 1970s, and the number of people forced from their homes due to destructive climate events has also escalated dramatically.

Worldwide, over 283 million people were displaced by weather-related disasters between 2008 and 2020, and over 30 million in 2020 alone – mainly in poor regions of Africa, Asia and Central America.

The frequency and intensity of climate shocks will worsen as global heating increases, and will be most devastating for the poorest people most vulnerable to climate change. In the least developed countries (LDCs) and Small Island Developing States (SIDS) entire communities and even nations may be forced to migrate.

Tools fit for the job?

To address disaster displacement effectively, governments, civil society organisations (CSOs) and their international partners – including donor governments, multilateral development banks and UN agencies – must build a good understanding of:

  1. How populations at risk are likely to be impacted as extreme weather events intensify
  2. Who is likely to be displaced as those events escalate and compound over time, and
  3. The challenges facing populations, once displaced.

In recent years, our understanding of disaster displacement risks has evolved rapidly, and so too have the approaches and tools we can use to understand them better. A variety of tools are now available, some of which – like probabilistic models – can even predict how many people might be displaced to particular locations due to hazards such as floods, storms and sea-level rise.

These tools mark a step change in our ability to assess displacement risk, especially at global level.

But IIED's latest research has found the tools are limited in providing detailed data on the specific vulnerabilities of different people to different climate hazards; this data could help decision-makers to design and deliver projects that better meet the needs of displaced people.

No two people experience the same level of displacement risk. Vulnerability to climate shocks varies dramatically depending on a range of social, economic and cultural factors, such as gender, age, physical ability, ethnicity, income level, asset ownership, food security, and access to essential services and social protection.

To be effective, assessments of disaster displacement risk must consider the diverse ways that different individuals, households, communities and social groups might be affected by climate shocks.

Unless risk assessment methodologies integrate the different factors that expose different people to different types and levels of displacement risk, the results they generate will not provide the full picture on who is at risk from particular hazards, or how they may be impacted differently.

Mind the data gap

Our research found that most displacement risk assessment methodologies only predict the number of people likely to be displaced due to a particular type of extreme weather event. None of the approaches we reviewed either integrate or generate robust data on the ways different types of people may be more or less vulnerable, or resilient, to climate shocks.

As a result, they cannot provide detailed insights into the extent to which different groups might be at risk of disaster displacement, or how they might be impacted if displaced.

This creates a serious gap, not only in our understanding of disaster displacement risks and how people most vulnerable to these risks are affected, but also in the data available to inform the design and delivery of interventions to save lives, protect livelihoods and reduce disaster displacement risks in the face of escalating climate shocks.

We also found significant demand, among planners and programme managers responsible for delivering disaster response and risk reduction programmes, for more robust assessments of disaster displacement risks that include detailed data on vulnerability, as well as on resilience and adaptive capacity at community and household levels.

Better data can sharpen tools to assess displacement risk

Luckily, developers of disaster displacement assessment tools do not need to start from scratch to integrate such data into their models.

Over the past 20 years, researchers and practitioners in the climate adaptation and climate risk management communities have done a huge amount of research and developed many practical tools that can be used to assess vulnerability, resilience and adaptive capacity at the micro-level.

This learning offers disaster displacement specialists a wealth of options for integrating more robust, granular data into the tools they currently use.

But further research is required to understand how different forms of quantitative and qualitative data, generated at different scales and with different levels of detail, can be interwoven to produce more accurate, vulnerability-informed displacement risk assessments that can be used easily by operational decision-makers at sub-national and local levels.