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Policy-relevant flood risk modeling must capture interactions between physical and social processes to accurately project impacts from scenarios of sea level rise and inland flooding due to climate change. Here we simultaneously model urban growth, flood hazard change, and adaptive response using the FUTure Urban-Regional Environment Simulation (FUTURES) version 3 framework (Sanchez et al., 2023). FUTURES is an open source urban growth model designed to address the regional-scale ecological and environmental impacts of urbanization; it is one of the few land change models that explicitly captures the spatial structure of development in response to user-specified scenarios. We present probabilistic land change projections...
Tags: Alabama,
Arkansas,
Climate migration,
Florida,
Georgia, All tags...
Kentucky,
Land Use Change,
Land use change,
Louisiana,
Mississippi,
North Carolina,
Projection,
Scenario,
Scenario-based land change modeling,
South Carolina,
Southeast,
Tennessee,
Texas,
USGS Science Data Catalog (SDC),
Urban growth,
Urbanization,
environment,
society, Fewer tags
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This data release contains the associated data described in the related primary publication, “Predicting Flood Damage Probability Across the Conterminous United States” (Collins et al. [2022], see Related External Resources section). Publicly available geospatial datasets and random forest algorithms were used to analyze the spatial distribution and underlying drivers of flood damage probability caused by excessive rainfall and overflowing water bodies across the conterminous United States. Datasets contain input files for predictor and response variables used in the analysis and output files of flood damage probabilities generated from the analysis.
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Impacts of sea level rise will last for centuries; therefore, flood risk modeling must transition from identifying risky locations to assessing how populations can best cope. We present the first spatially interactive (i.e., what happens at one location affects another) land change model (FUTURES 3.0) that can probabilistically predict urban growth while simulating human migration and other responses to flooding, essentially depicting the geography of impact and response. Accounting for human migration reduced total amounts of projected developed land exposed to flooding by 2050 by 5%–24%, depending on flood hazard zone (50%–0.2% annual probability). We simulated various “what-if” scenarios and found managed retreat...
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Abstract (from Environmental Research Letters): Floods are the leading cause of natural disaster damages in the United States, with billions of dollars incurred every year in the form of government payouts, property damages, and agricultural losses. The Federal Emergency Management Agency oversees the delineation of floodplains to mitigate damages, but disparities exist between locations designated as high risk and where flood damages occur due to land use and climate changes and incomplete floodplain mapping. We harnessed publicly available geospatial datasets and random forest algorithms to analyze the spatial distribution and underlying drivers of flood damage probability (FDP) caused by excessive rainfall and...
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