Data Release Offers Valuable Information on Future Urbanization Patterns Across the Southeastern US
Two SE CASC supported data releases, Status Quo Projections of Future Patterns of Urbanization Across the Conterminous United States from 2020 to 2100 and Scenarios of Future Patterns of Urbanization in Response to Sea Level Rise and Frequent Flooding Across the Southeast United States from 2020 to 2100, have just been published with credit to Anna Petrasova (NCSU), Georgina Sanchez (NCSU), Adam Terando (SE CASC), Ross Meentemeyer (NCSU), and others.
The data releases are a product of the SE CASC project, Improving Scenarios of Future Patterns of Urbanization, Climate Adaptation, and Landscape Change in the Southeast. Georgina Sanchez contributed to the following summary.
The Southeastern United States is experiencing rapid changes from climate change, urbanization, and landscape change. As population continues to rise in this region, areas are becoming increasingly urbanized to accommodate for the influx of people. Transition of the landscape from previously permeable surfaces, such as forests or grasslands, to impermeable surfaces, such as sidewalks and roads, affects climate adaptation efforts. For example, with increased precipitation in future climate scenarios, these impermeable surfaces will be unable to absorb the water thus contributing to more intense flooding. In addition, climate change puts the coast at an increased risk, thus encouraging migration from low-lying coastal areas to less risky inland locations at higher elevation.
This data release has two parts:
- Projections of future patterns of urbanization for a business-as-usual trajectory of growth across the CONUS from 2020 to 2100 (computed with FUTURES version 2.0) and
- Scenarios of future urbanization in response to sea level rise and frequent flooding across the Southeast (computed with the most advanced version FUTURES 3.0). For the first scenario, “Reactive”, residents are assumed to adapt to threats as they occur, without incentives or policies in place to minimize exposure or damage. For the second scenario, we simulated a “Managed Retreat” intervention, where policymakers incentivize relocation and resettlement for at-risk residents, regardless of their level of adaptive capacity.
Projecting human mobility and shifts in development patterns in response to future flooding is crucial for anticipating the need for policies and/or investments that protect lives, livelihoods, and property. To address this, the research team developed an enhanced version of the FUTure Urban-Regional Environment Simulation (FUTURES 3.0) land change model. This updated model can now simultaneously incorporate urban growth, climate change-induced increases in flood hazard, and human adaptive response to flooding.
Considering the ongoing expansion of urban areas, the intensifying flood hazards under climate change, and the likelihood of individuals seeking to reduce flood risk and protect their properties, projections of future exposure must integrate all three components of flood risk relevant to policy-making: exposure, hazard, and vulnerability. Flood risk, which refers to the probability of flood damage at a specific time and location, depends on these three factors.
For the purposes of policy-making, it is essential to consider the patterns of urban development that determine exposure – the amount of infrastructure that could be damaged by a flood. Hazard pertains to the likelihood and intensity of floodwaters, and with rising sea levels and increased riverine flooding due to climate change, the spatial extent of flood hazard expands. Lastly, vulnerability relates to the capacity of a population to reduce exposure or mitigate hazards through adaptive responses. For instance, the construction of seawalls aims to diminish hazard by preventing floodwaters from reaching protected areas, while elevation of homes or retreat from hazardous zones reduces exposure. However, the ability of populations to enact such responses depends on their available resources.
Anticipating human responses to flood hazards or damage presents challenges, as the past may not be an accurate guide to the future. Scenario-based modeling allows us to conduct simulation experiments and test approaches for efficiently and equitably allocating resources for adaptation. These experiments enable us to iteratively evaluate assumptions and predict outcomes based on insights gained from regional-scale analysis of flood management policies, local case studies of damage and adaptive capacity, or community-specific plans.
With FUTURES 3.0, we can now utilize customizable flood response functions to capture the range of human behaviors specific to different areas. This provides a diverse set of alternative scenarios that can help us anticipate various outcomes based on different assumptions, political climates, or economic conditions. Besides a business-as-usual response scenario (wherein residents are assumed to adapt to threats as they occur, without incentives or policies in place to affect outcomes), we parameterized a managed retreat trajectory (wherein policymakers incentivize converting developed land with high flood risk into undeveloped and facilitate the relocation of residents to safer locations).
This project was pursued under the request of the U.S. Fish and Wildlife Service (FWS), National Park Service, and state fish and wildlife agency partners to provide updated urbanization and habitat change scenarios to meet regulatory obligations and facilitate management decisions. The data can not only help decision makers plan for future urbanization and population movement across the Southeast, but also inform management of wildlife, ecosystems, and habitats of concern. Currently the Southeast Conservation Adaptation Strategy is using this data for their Southeast Conservation Blueprint to allow their stakeholders to consider how urbanization may present a future risk to conservation.
— Full citations and abstracts for the data releases follow —
Petrasova, A., Sanchez, G.M., Lawrimore, M.A., Vogler, J.B., Collins, E.L., Petras, V., Harper, T., Butzler, E., and Meentemeyer, R.K., 2023, FUTURES v2: Status Quo Projections of Future Patterns of Urbanization Across the Conterminous United States from 2020 to 2100: U.S. Geological Survey data release, https://doi.org/10.5066/P94N3ICH.
Summary: We simulated future patterns of urban growth using the FUTure Urban-Regional Environment Simulation (FUTURES; Meentemeyer et al., 2013) version 2 framework. 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 that predict urban growth under a Status Quo scenarios of growth. We computed each scenario for 50 stochastic iterations from 2020 through 2100 at annual time steps.
Petrasova, A., Sanchez, G.M., Skrip, M.M., Collins, E.L., Lawrimore, M.A., Vogler, J.B., Terando, A., Vukomanovica, J., Mitasova, H., and Meentemeyer, R.K., 2023, FUTURES v3: Scenarios of Future Patterns of Urbanization in Response to Sea Level Rise and Frequent Flooding Across the Southeast United States from 2020 to 2100: U.S. Geological Survey data release, https://doi.org/10.5066/P9BD5V4B.
Summary: 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 that predict urban growth while also simulating human migration and other response actions. We simulated two scenarios of urban growth and adaptive response: 1) “Reactive”, wherein residents are assumed to adapt to threats as they occur, without incentives or policies in place to affect outcomes; and 2) “Managed Retreat”, in which policymakers incentivize converting at-risk developed land to undeveloped land (i.e., abandoned), with residents of all levels of adaptive capacity moving elsewhere. We computed each scenario for 20 stochastic iterations from 2020 through 2100 at annual time steps. Our scenario advances local to national-scale efforts to evaluate tradeoffs between adaptation strategies in response to global anthropogenic change.