Flood water surrounds a home following Tropical Storm Imelda in Fannett, Texas, in 2019. The remnants of Imelda lashed Houston and coastal Texas, inundating homes, paralyzing travel, disrupting oil supplies, and threatening hospitals and refineries.
Flood water surrounds a home following Tropical Storm Imelda in Fannett, Texas, in 2019. The remnants of Imelda lashed Houston and coastal Texas, inundating homes, paralyzing travel, disrupting oil supplies, and threatening hospitals and refineries.
Over the past two decades, as San Antonio and surrounding Bexar County, Texas, grew by more than 600,000 people, some 17% of the city’s blocks experienced a decrease in population.
That delta is largely due to flood risk that climate change exacerbates, according to a new report by the First Street Foundation, a data nonprofit with the mission of communicating climate hazards.
Bexar — sitting in a swath of Texas known as Flash Flood Alley — is part of a national trend of hyper-local migration to avoid flooding, which is hollowing out blocks within cities, the report finds. The research is based on a model, published Monday in the journal Nature Communications, that looks at population changes using granular U.S. Census Bureau data and controls for factors besides flooding, such as nearby job opportunities and school quality.
In all, First Street finds, 3.2 million Americans moved away from high-flood-risk areas between 2000 and 2020. The full extent of the migration has been hidden, however, since most people didn’t move far.
“There appear to be clear winners and losers in regard to the impact of flood risk on neighborhood-level population change,” Jeremy Porter, head of climate implications research at First Street, said in a statement. “The downstream implications of this are massive and impact property values, neighborhood composition and commercial viability, both positively and negatively.”
The analysis also extrapolates these trends 30 years into the future, predicting that vulnerable areas will continue to lose population.
In the U.S., the frequency of disasters causing at least $1 billion in damages has gone from roughly three a year during the 1980s to an annual average of 17.8 over the period 2018 to 2022, according to the National Oceanic and Atmospheric Administration. Global warming has knock-on effects that exacerbate flooding in particular, including sea level rise, more ferocious hurricanes and more frequent and extended downpours.
It’s no secret that some climate migration is underway, whether along the Gulf Coast, which is losing a football field’s worth of land every 100 minutes, or in California, where whole towns have been sent into diaspora by wildfires. However, quantifying the impact of climate change on migration down to the neighborhood level has never been done on a national scale. First Street focused solely on floods, since flooding is the most common weather-related disaster.
The researchers created a model that looks at population change down to the smallest geographical unit used by the U.S. Census, the census block. They overlaid that with historical flood data. They then tried to isolate the influence of flooding on migration as compared to other social and economic factors commonly associated with moving, like excellent or poor schools.
They found that when between 5% to 10% of properties in a census block are at risk of flooding, there is a tipping point, and people begin moving out even if there are other attractive amenities, such as a view of the coast.
In some cases this movement is enough to leave previously thriving areas in decline. In many other cases it is just enough to slow otherwise red-hot growth. Looking deeply at Bexar County, First Street found that neighborhoods with lower flooding risk grew much faster than those with higher risk.
Of course, people’s motivations for moving can be complicated. Kristina Dahl, principal climate scientist for the climate and energy program at the nonprofit Union of Concerned Scientists, said that while she didn’t see any flaws in the First Street model, its findings run contrary to most current scientific literature.
