New flood model factors in human reactions
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Connecting state and local government leaders
A new open-source flood risk model assesses communities' adaptive responses to flood events, which can help local governments prepare for flood intervention measures like altering development plans or elevating buildings.
This story is republished from Futurity. Read the original article.
Researchers have created a land change model that simulates interactions among urban growth, increased flooding, and how humans adapt in response.
The new model could offer a more realistic assessment of risk for urban planners, natural resource managers, and other local government stakeholders.
“Traditional risk assessment typically involves overlaying inundation layers—areas that may flood—onto existing development or population distribution to identify areas and communities at risk,” says Georgina Sanchez, research scholar in North Carolina State University’s Center for Geospatial Analytics and corresponding author of the work. “Yet this approach only provides a partial picture.
“Urban planners and residents are increasingly aware of the growing flood risks from climate change and are ready to respond and adapt when able,” Sanchez says. “It’s crucial for models to consider our collective adaptation efforts—like elevating buildings or moving away from high-risk zones. Our model provides deeper insights, helping us understand adaptive capacities and identify communities with limited resources—essentially characterizing the geography of impact and response.”
The model, FUTURES 3.0 (FUTure Urban-Regional Environment Simulation), is an open-source, scalable model that includes three components of flood risk: exposure, which refers to urban development patterns; hazard, which includes increases in flooding due to climate change; and vulnerability, or the adaptive response of people living in the area. The model incorporates climate data as well as demographic, socio-economic, and flood-damage data.
The researchers used the greater Charleston, South Carolina metropolitan area as their test case. Charleston is a rapidly developing urban area located in a low-lying region bordered by the Atlantic Ocean and numerous rivers.
By comparing land change projections for 2035 and 2050 against a 2020 baseline and across various policy intervention and response scenarios, they envisioned possible demographic and population shifts and identified which scenarios resulted in the least exposure to future flooding, as well as where flood risk remained highest across the landscape.
“The study underscores the importance of incorporating human adaptive response alongside demographic shifts and urban expansion for accurate exposure and risk assessment,” Sanchez says. “Not all residents or communities will have the means or capacity to build protective measures. Visualizing potential ‘what-if’ scenarios help us consider the where and when of impact and understand who is being affected and how.”
The researchers’ next steps are to engage with communities to discuss potential interventions. They are also expanding their studies at a regional scale.
“Through scenario-based modeling,” Sanchez says, “we explore questions like: how will communities respond to damage, who has the means to adapt, and what challenges do those with limited resources for protection face?
“Additionally, these scenarios let us visualize the long-term consequences of our current development choices,” Sanchez continues. “If we anticipate that 30 years from now a newly developed community may face the decision to retreat, why not think about protecting that area now?”
The work appears in Scientific Reports and has support from the US Geological Survey Southeast Climate Adaptation Science Center; the National Science Foundation program for Smart and Connected Communities; and the intramural research program of the US Department of Agriculture, National Institute of Food and Agriculture, McIntire-Stennis.
The open-source FUTURES software is accessible through the GitHub repository with the identifier doi:10.5281/zenodo.6607097.
Source: NC State
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