scholarly journals What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?

2016 ◽  
Vol 85 ◽  
pp. 246-265 ◽  
Author(s):  
Alan V. Di Vittorio ◽  
Page Kyle ◽  
William D. Collins
Keyword(s):  
Land Use ◽  
Global Change ◽  
Assessment Model ◽  
Land Resource ◽  
Change Assessment ◽  
Ecological Zones ◽  
Global Change Assessment Model ◽  
Agro Ecological Zones

scholarly journals Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models

2016 ◽  
Vol 9 (9) ◽  
pp. 3055-3069 ◽  
Author(s):  
Yannick Le Page ◽  
Tris O. West ◽  
Robert Link ◽  
Pralit Patel
Keyword(s):  
Land Use ◽  
Global Change ◽  
Land Cover ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Critical Parameters ◽  
Reference Scenario ◽  
Change Assessment ◽  
Global Change Assessment Model ◽  
Wide Range

Abstract. The Global Change Assessment Model (GCAM) is a global integrated assessment model used to project future societal and environmental scenarios, based on economic modeling and on a detailed representation of food and energy production systems. The terrestrial module in GCAM represents agricultural activities and ecosystems dynamics at the subregional scale, and must be downscaled to be used for impact assessments in gridded models (e.g., climate models). In this study, we present the downscaling algorithm of the GCAM model, which generates gridded time series of global land use and land cover (LULC) from any GCAM scenario. The downscaling is based on a number of user-defined rules and drivers, including transition priorities (e.g., crop expansion preferentially into grasslands rather than forests) and spatial constraints (e.g., nutrient availability). The default parameterization is evaluated using historical LULC change data, and a sensitivity experiment provides insights on the most critical parameters and how their influence changes regionally and in time. Finally, a reference scenario and a climate mitigation scenario are downscaled to illustrate the gridded land use outcomes of different policies on agricultural expansion and forest management. Several features of the downscaling can be modified by providing new input data or changing the parameterization, without any edits to the code. Those features include spatial resolution as well as the number and type of land classes being downscaled, thereby providing flexibility to adapt GCAM LULC scenarios to the requirements of a wide range of models and applications. The downscaling system is version controlled and freely available.

scholarly journals Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models

2016 ◽  
Author(s):  
Yannick Le Page ◽  
Tris O’Brien West ◽  
Robert Link ◽  
Pralit Patel
Keyword(s):  
Land Use ◽  
Global Change ◽  
Land Cover ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Critical Parameters ◽  
Reference Scenario ◽  
Change Assessment ◽  
Global Change Assessment Model ◽  
Wide Range

Abstract. The Global Change Assessment Model (GCAM) is a global integrated assessment model used to project future societal and environmental scenarios, based on economic modeling and on a detailed representation of food and energy production systems. The terrestrial module in GCAM represents agricultural activities and ecosystems dynamics at the sub-regional scale, and must be downscaled to be used for impact assessments in gridded models (e.g. climate models). In this study, we present the downscaling algorithm of the GCAM model, which generates gridded time series of global land use and land cover (LULC) from any GCAM scenario. The downscaling is based on a number of user-defined rules and drivers, including transition priorities (e.g. crop expansion preferentially into grasslands rather than forests) and spatial constraints (e.g. nutrient availability). The default parameterization is evaluated using historical LULC change data, and a sensitivity experiment provides insights on the most critical parameters and how their influence changes regionally and in time. Finally, a reference scenario and a climate mitigation scenario are downscaled to illustrate the gridded land use outcomes of different policies on agricultural expansion and forest management. Several features of the downscaling can be modified by providing new input data or changing the parameterization, without any edits to the code. Those features include spatial resolution as well as the number and type of land classes being downscaled, thereby providing flexibility to adapt GCAM LULC scenarios to the requirements of a wide range of models and applications. The downscaling system is version controlled and freely available.

scholarly journals Scenario-Based Analysis on the Structural Change of Land Uses in China

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Qian Xu ◽  
Qunou Jiang ◽  
Kai Cao ◽  
Xing Li ◽  
Xiangzheng Deng
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Global Change ◽  
Land Use Change ◽  
Global Environmental Change ◽  
Structure Change ◽  
Assessment Model ◽  
Change Assessment ◽  
Global Change Assessment Model ◽  
The Impact

Land Use/Land Cover change (LUCC) is a key aspect of global environmental change, which has a significant impact on climate change. In the background of increasing global warming resulting from greenhouse effect, to understand the impact of land use change on climate change is necessary and meaningful. In this study, we choose China as the study area and explore the possible land use change trends based on the AgLU module and ERB module of global change assessment model (GCAM model and Global Change Assessment Model). We design three scenarios based on socioeconomic development and simulated the corresponding structure change of land use according to the three scenarios with different parameters. Then we simulate the different emission of CO2under different scenarios based on the simulation results of structure change of land use. At last, we choose the most suitable scenario that could control the emission of CO2best and obtain the relatively better land use structure change for adaption of climate change. Through this research we can provide a theoretical basis for the future land use planning to adapt to climate change.

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