large, combined with the fact that flood hazard is often high in cities. The urban‐rural gaps in income and flood risk may thus hide the fact that poor people are more exposed. This hypothesis is further supported by subnational analyses in two countries (Morocco and Malawi), where several regions are identified where poor people are clearly over‐exposed, when compared with the rest of the population in the country.

A particular concern is the fact that some of the countries where poor people are overexposed will also experience more frequent flooding or droughts in the future due to climate change. Poverty‐ vulnerability hotspots appear when combining countries with an overexposure of the poor and an increase in hazards expected from climate change. This signal is found in Burkina Faso, Burundi, Egypt, Ethiopia, Guinea, Kenya, Nigeria, Sierra Leone and Uganda for floods. For drought, Nigeria and Ghana were found to be in this situation although results for Ghana were found to be less robust.

Exposure, the topic of this paper, is only one component of risk. Almost everywhere, the other components of risk – from protection to vulnerability to the ability to cope and recover – are also biased against poor people (Hallegatte et al., 2016), which means that even in places without a poverty bias, poor people may still be at risk. Protection levels and quality are lower in poor countries, and lower in poor neighborhoods and regions. Poor people live in low quality houses that suffer more damage in case of floods, and they have most if not all of their assets in material form, making them more vulnerable to floods. Finally, poor people have limited access to recovery support, such as social protection and credit.

All of these factors combined with the results in this paper advocate for disaster risk management as a pro‐poor policy. In countries where we find that poor people are disproportionally exposed to floods and droughts, it is particularly important to integrate risk management policies within poverty reduction strategies, to understand the underlying drivers of the exposure bias, and to correct it through better land‐use regulation and other supporting policies. Critically, such policies should support the access of poor people to opportunities, and not stifle them. Where hazards will become more frequent or more intense, implementing risk‐sensitive land‐use policies that protect poor people, such as flood zoning, should be a priority.

# **Acknowledgements**

We thank Adrien Vogt‐Schilb and Anne Zimmer for their careful review of this paper, and Tom Pullum, Ruilin Ren, and Clara Burgert from ICF International for their very helpful guidance on using the DHS data. We are grateful for financial support from the Global Facility for Disaster Reduction and Recovery (and thank Alanna Simpson as being the main counter‐part from GFDRR) and the World Bank, under the work program on “Poverty and Climate Change,” led by the Office of the Chief Economist of the Climate Change Group. We also acknowledge support from Earth2Observe, EU FP7 project grant agreement no. 603608. Furthermore, P.J. Ward received additional financial support from a VENI grant for the Netherlands Organisation for Scientific Research (NWO).

# **Author contributions**

H.C.W. and P.J.W. computed the flood hazard maps for all projections. T.I.E.V. and P.J.W. established the drought hazard layers for all projections. M.B. prepared shapefiles from the DHS survey data, for use in this study. H.C.W., B.J., P.J.W. and T.I.E.V. established the computational framework to compute the poverty exposure bias. M.B. and S.H. performed background study on poverty and 22