This project focuses on development of new interdisciplinary modeling capabilities of long-term time series that capture interactions among climate, land use, water use, and water availability. Research builds on expanding the USGS Forecasting Scenarios of Land Use (FORE-SCE) model and integrating with spatially explicit models from other disciplines. Interdisciplinary models will be co-developed and applied with our partners to assess land use impacts on water quality, conservation priorities and biodiversity, and greenhouse gases and climate.
Statement of Problem:
Feedbacks among land use and land-cover (LULC) and climate change impact a wide variety of ecological and societal processes at local to global scales. Data on LULC change are thus vital for many research applications and for land and resource management. For over 20 years, USGS has produced consistent, national-scale land-use and land-cover data from remote sensing imagery, data that are the most widely used LULC data in the Nation, and likely the world. However, these data are only available for time periods when source remote sensing data are available, with consistent land cover data for the United States only available from 1985 to present
Analyses and modeling of historical LULC (prior to availability of remote sensing based LULC) are required to understand past effects of LULC change on ecological and societal processes, which informs scenario-based modeling of future landscapes, including landscape response to climate change. This in turn informs long-term analyses of feedbacks of land use, climate, and a multitude of ecological and societal processes, and facilitates planning and mitigation for critical impacts on societal interests.
Why this Research is Important:
Climate-sensitive historical landscape reconstructions and future scenarios provide long-term time series of landscape change, allowing for the exploration and analyses of LULC impacts on biodiversity, carbon and greenhouse gas fluxes, exposure to natural hazards, water quality, and a variety of other environmental and human systems. Historical landscape reconstruction enables analyses of past relationships between landscape change and these processes, while future scenarios facilitate planning and mitigation efforts. A major priority here is climate-sensitive landscape modeling to support conservation priorities, including the administration’s 30x30 initiative. However, through connections noted below we also will address other Department of the Interior (DOI) and USGS priorities, particularly those related to hydrologic processes, and carbon and greenhouse gases.
Objective(s):
Long-term time series of past, present, and future landscapes inform interdisciplinary analyses of feedbacks between LULC change, climate, hydrologic processes, and an array of ecosystem services. The goal of this activity is to develop interdisciplinary modeling approaches of long-term land-change time series to support conservation priorities and other ecosystem services.
Our overarching research objectives include:
- Develop and evaluate spatially explicit models of interactions among climate, land use, water use, and water availability, including representation of socioeconomic and biophysical drivers of change at scales from global to local.
- Methodological development and application of historical landscape reconstruction methodologies, facilitating long-term time series analyses (past, present, future).
- Stakeholder-relevant co-development of climate-sensitive landscape scenarios designed to meet hypothesis driven application and management needs.
- Interdisciplinary and collaborative scenario development, modeling, and assessment to support application priorities.
Methods:
This project focuses on three major tasks to address the hypotheses and research objectives above.
- Development of interdisciplinary modeling frameworks. This task focuses on augmentation and evolution of the USGS Forecasting Scenarios of land use (FORE-SCE) model, integration of FORE-SCE with other land-change modeling frameworks, and integration of land-change models with interdisciplinary models of water use, water availability, climate, and other ecosystem processes.
- Development of Multi-scale Scenarios. This task focuses on development of comprehensive, multi-scale scenarios that account for an array of biophysical and socioeconomic driving forces of landscape change. Scenarios are used to represent the high inherent uncertainties in modeling future land use change.
- Collaborative model application in support of USGS, DOI, and partner priorities. This task focuses on the application of scenario-based, integrated modeling frameworks to address specific science questions of interest to the USGS and our partners. Primary areas of focus are looking at feedbacks between land use, climate, water availability, water use, carbon, and biodiversity.
Land-Cover Modeling Methodology - The FORE-SCE Model
- Overview
This project focuses on development of new interdisciplinary modeling capabilities of long-term time series that capture interactions among climate, land use, water use, and water availability. Research builds on expanding the USGS Forecasting Scenarios of Land Use (FORE-SCE) model and integrating with spatially explicit models from other disciplines. Interdisciplinary models will be co-developed and applied with our partners to assess land use impacts on water quality, conservation priorities and biodiversity, and greenhouse gases and climate.
Sources/Usage: Public Domain. Visit Media to see details.Modeled land cover change in the Delaware River Basin from 1700 to 2100. The Forecasting Scenarios of land use (FORE-SCE) model was used to reconstruct historical landscapes back to 1700, and project future landscapes through 2100. The resultant long-term landscape database can be used to assess the impacts of land use on water quality, biodiversity, carbon and greenhouse gases, and other processes. Statement of Problem:
Feedbacks among land use and land-cover (LULC) and climate change impact a wide variety of ecological and societal processes at local to global scales. Data on LULC change are thus vital for many research applications and for land and resource management. For over 20 years, USGS has produced consistent, national-scale land-use and land-cover data from remote sensing imagery, data that are the most widely used LULC data in the Nation, and likely the world. However, these data are only available for time periods when source remote sensing data are available, with consistent land cover data for the United States only available from 1985 to present
Analyses and modeling of historical LULC (prior to availability of remote sensing based LULC) are required to understand past effects of LULC change on ecological and societal processes, which informs scenario-based modeling of future landscapes, including landscape response to climate change. This in turn informs long-term analyses of feedbacks of land use, climate, and a multitude of ecological and societal processes, and facilitates planning and mitigation for critical impacts on societal interests.
Why this Research is Important:
Climate-sensitive historical landscape reconstructions and future scenarios provide long-term time series of landscape change, allowing for the exploration and analyses of LULC impacts on biodiversity, carbon and greenhouse gas fluxes, exposure to natural hazards, water quality, and a variety of other environmental and human systems. Historical landscape reconstruction enables analyses of past relationships between landscape change and these processes, while future scenarios facilitate planning and mitigation efforts. A major priority here is climate-sensitive landscape modeling to support conservation priorities, including the administration’s 30x30 initiative. However, through connections noted below we also will address other Department of the Interior (DOI) and USGS priorities, particularly those related to hydrologic processes, and carbon and greenhouse gases.
Objective(s):
Long-term time series of past, present, and future landscapes inform interdisciplinary analyses of feedbacks between LULC change, climate, hydrologic processes, and an array of ecosystem services. The goal of this activity is to develop interdisciplinary modeling approaches of long-term land-change time series to support conservation priorities and other ecosystem services.
Our overarching research objectives include:
- Develop and evaluate spatially explicit models of interactions among climate, land use, water use, and water availability, including representation of socioeconomic and biophysical drivers of change at scales from global to local.
- Methodological development and application of historical landscape reconstruction methodologies, facilitating long-term time series analyses (past, present, future).
- Stakeholder-relevant co-development of climate-sensitive landscape scenarios designed to meet hypothesis driven application and management needs.
- Interdisciplinary and collaborative scenario development, modeling, and assessment to support application priorities.
Methods:
Terry Sohl talks about the FORE-SCE Land Use model that is being used to assist a variety of groups. the model uses land cover products from the USGS and extrapolates that data to predict what areas will look like in the future, based on a variety of scenarios.
This project focuses on three major tasks to address the hypotheses and research objectives above.
- Development of interdisciplinary modeling frameworks. This task focuses on augmentation and evolution of the USGS Forecasting Scenarios of land use (FORE-SCE) model, integration of FORE-SCE with other land-change modeling frameworks, and integration of land-change models with interdisciplinary models of water use, water availability, climate, and other ecosystem processes.
- Development of Multi-scale Scenarios. This task focuses on development of comprehensive, multi-scale scenarios that account for an array of biophysical and socioeconomic driving forces of landscape change. Scenarios are used to represent the high inherent uncertainties in modeling future land use change.
- Collaborative model application in support of USGS, DOI, and partner priorities. This task focuses on the application of scenario-based, integrated modeling frameworks to address specific science questions of interest to the USGS and our partners. Primary areas of focus are looking at feedbacks between land use, climate, water availability, water use, carbon, and biodiversity.
Sources/Usage: Public Domain.Modeled land cover change near Lakin, Kansas from 2014-2100. The Forecasting Scenarios of land use (FORE-SCE) model was used to project landscape change under multiple scenarios, using real land ownership and land management parcels to represent change processes. The scenario here represents a biofuel scenario from the Department of Energy. Declining aquifer levels and a hotter and drier climate result in loss of irrigated cropland (corn, alfalfa) and conversion to dryland crops (wheat, sorghum) or rangeland. - Science
Land-Cover Modeling Methodology - The FORE-SCE Model
Many factors determine how human beings modify the earth's landscape. Land-cover change is inherently a local event, yet broader scale socioeconomic and biophysical factors also affect how humans make decisions to use the landscape. Projecting future land cover requires modelers to account for driving forces of land-cover change operating at scales from local ("bottom-up") to global ("top-down")... - Multimedia
- Publications