New research published by Willis Research Network partner Cloud to Street, now provides ground-breaking insights into the rising global flood risk.
Cloud to Street uses direct satellite observations of flooding and refines this geospatial data with machine learning, AI and other methods instead of modelled estimates which are widely used in the insurance industry.
The research, published as the Global Flood Database, offers a comprehensive view of flood exposure around the world and underscores how alternative methods of analysing flood risks through platforms like Cloud to Street allows insurers to understand flooding in a new and revolutionary way. The entire database is hosted openly at Global-flood-database.cloudtostreet.ai.
The analysis reveals that the proportion of global population exposed to floods has grown by 24% since the turn of the millennium, a tenfold difference from what scientists previously thought. Growing exposure and a growing number of flood events are behind the rapid increase, according to the research.
Since Cloud to Street joined the Willis Research Network in 2020, the partnership has worked to address the insurance gap in the developing world, where some 90% of economic losses from disasters remain uninsured, putting economically vulnerable households at greater risk and slowing recovery efforts following disasters.
Today, most flood maps rely on modelling that simulates floods based on available ground data, such as elevation, rainfall and ground sensors. These models are time intensive and can have substantial limitations, entirely missing flooding incidents in regions not historically prone to flooding. This leads to a large flood insurance coverage gap and low flood insurance penetration worldwide, where coverage is either not available or inadequate.
In contrast, Cloud to Street’s Global Flood Database relies on satellite observations of actual flooding over the past two decades, which marks a step change in developing a comprehensive view of global flood risk. This allows additional analyses of the scope, impact, and trends of recent flooding. It represents a major advancement in the field of flood mapping and is essential to capture climate change’s accelerating, record-breaking disasters, while also enabling greater flood insurance penetration worldwide.
Bessie Schwarz, CEO and Co-founder of Cloud to Street, said: “More people and more assets are impacted by flooding than any other climate-fuelled disaster. The Global Flood Database will help insurers understand the changing nature of flood risk and offer more competitive insurance coverage. We are proud to enable governments and insurers to protect millions of people and billions in assets they have never been able to before.”
Simon Young, a senior director in the Climate and Resilience Hub at Willis Towers Watson added “The collaboration between Cloud to Street and the Willis Research Network is already delivering beyond our expectations, particularly in the research and development of tools to better understand flood risk and mitigate the economic impact of flooding for communities throughout the world. Alongside our Willis Re and Alternative Risk Transfer units, the Climate and Resilience Hub is also creating innovative parametric solutions building on this rapidly evolving flood mapping technology.”
The researchers looked at daily satellite imagery to estimate both the extent of flooding and the number of people exposed to over 900 large flood events between 2000 and 2018. They found that between 255 and 290 million people were directly affected – and between 2000 and 2015, the number of people living in these flooded locations increased by 58-86 million.
Further findings from the research:
- By 2030 the model estimates that climate and demographic change will add 25 new countries to the 32 already experiencing increasing floods.
- Despite representing less than 2 percent of floods, dam breaks had the highest increased incidence (177%) in proportion of population exposed.
- Population growth in flooded areas is driven by people moving into flood-prone areas—and economic development in those regions. Vulnerable populations often have no choice but to settle in flood zones.
- Nearly 90% of flood events occurred in South and Southeast Asia, with the large basins (Indus, Ganges-Brahmaputra, and Mekong) having the largest absolute numbers of people exposed and increased proportions of population exposed to inundation.
- The satellite data also uncovered previously unidentified increases in flood exposure in Southern Asia, Southern Latin America, and the Middle East.
It is hoped that the database will provide a unique and credible benchmark for the insurance industry to assess flood risks, both from an aggregated annual average loss perspective, as well as single extreme loss-making floods. This can be useful for reinsurance practices undertaken by Willis Re, involving model comparison, developing new views of flood risk, and testing the efficiency of various reinsurance structures. It can equally be used to support disaster resilience and post-event analysis as the insurance industry and governments prepare for, and respond to, large-scale flooding in all parts of the world.
As flood risk is expected to increase through population changes and urbanisation, overlaid onto a background trend driven by climate change, the dataset will provide an ongoing and essential view of risk to support humanitarian and risk management efforts.