ICF International worked with collaborators at Colorado State University (CSU) to develop an integrated suite of models to project and map long-term county-level population movements in the United States. The purpose of this project is twofold:
- To create seamless, well-documented land use scenarios for the contiguous United States based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) storylines
- To create decision-focused land-use change scenarios for high-priority issues/areas where stakeholder endpoints may be sensitive to combinations of climate and land-use change
The approach for this project included two tracks of research to address the two goals stated above. Both tracks are dependent on a transparent set of county-level population projections developed by ICF and integrated with the Spatially Explicit Regional Growth Model (SERGoM) maintained by Dr. David Theobold at CSU. Using the population projections, SERGoM is used to analyze land-use patterns and to develop land-use maps.
In the first track of research, the population projections developed by ICF were fed into the SERGoM model to evaluate the outcomes of the SRES scenarios on land use. In the second track, the team developed two decision-focused case studies; one used by the EPA’s Office of Air Quality Planning and Standards to support long-term air quality modeling efforts and a second used by the EPA’s Office of Water that focuses on changes in impervious surface due to development patterns. The products of the first phase of this work include a report describing the modeling framework, Land-Use Scenarios: National-Scale Housing-Density Scenarios Consistent with Climate Change Storylines, and a geographic information systems (GIS)-based tool that allows users to access the data and model, Integrated Climate and Land Use Scenarios (ICLUS) Tool and Datasets. Outputs from this first phase have also been released for the National Climate Assessment.
ICF is currently supporting the second phase of this work, in which the team is updating the modeling framework. The population projections have been updated to improve the approach to modeling migration patterns using Internal Revenue Service (IRS) data and to incorporate projected climate variables based on established climate models. SERGoM is being updated to include a more detailed representation of land-use changes to commercial and industrial land and to incorporate regional variations in development patterns. The team also developed a methodology for incorporating sea-level rise into future iterations of the model. The results from these updates are due to be released in 2012.
Related Market + Service Offerings