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

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.

2016 ◽  
Vol 9 (9) ◽  
pp. 3055-3069 ◽  
Author(s):  
Yannick Le Page ◽  
Tris O. West ◽  
Robert Link ◽  
Pralit Patel

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.


2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaowei Yao ◽  
Zhanqi Wang ◽  
Hua Wang

Land-use/land cover change (LUCC) is one of the fundamental causes of global environmental change. In recent years, understanding the regional climate impact of LUCC has become a hot-discussed topic worldwide. Some studies have explored LUCC impact on regional climate in specific cities, provinces, or farming areas. However, the quick-urbanized areas, which are highly influenced by human activities, have the most severe land-use changes in developing countries, and their climatic impact cannot be ignored. This study aims to identify the impact of land-use change coupled with urbanization on regional temperature and precipitation in the metropolitan areas of middle and lower reaches of the Yangtze River in China by means of spatial analysis and numeric methods. Based on the exploration of land-use change and climate change during 1988–2008, the impact of land-use transition from non-built-up area to built-up area on temperature and precipitation was analyzed. The results indicated that the land-use conversion has affected the regional temperature with an increasing effect in the study area, while the influence on precipitation was not so significant. The results can provide useful information for spatial planning policies in consideration of regional climate change.


2016 ◽  
Author(s):  
Yannick Le Page ◽  
Tris O’Brien West ◽  
Robert Link ◽  
Pralit Patel

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.


2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Susanne Rolinski ◽  
Alexander V. Prishchepov ◽  
Georg Guggenberger ◽  
Norbert Bischoff ◽  
Irina Kurganova ◽  
...  

AbstractChanges in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.


2021 ◽  
Author(s):  
Bekam Bekele Gulti ◽  
Boja Mokonnen Manyazew ◽  
Abdulkerim Bedewi Serur

Abstract Climate change (CC) and land use/cover change (LUCC) are the main drivers of streamflow change. In this paper, we investigate the impact of climate and LULC change impact on stream flow of Guder catchment by using Soil and Water Assessment model (SWAT). The scenarios were designed in a way that LULC was changed while climate conditions remain constant; LULC was then held constant under a changing climate and combined effect of both. The result shows that, the combined impacts of climate change and LULC dynamics can be rather different from the effects that follow-on from LULC or climate change alone. Streamflow would be more sensitive to climate change than to the LULC changes scenario, even though changes in LULC have far-reaching influences on streamflow in the study region. A comprehensive strategy of low impact developments, smart growth, and open space is critical to handle future changes to streamflow systems.


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