%0 Journal Article
%T Interactions between Climate, Socioeconomics, and Land Dynamics in Qinghai Province, China: A LUCD Model-Based Numerical Experiment
%A Xiangzheng Deng
%A Jikun Huang
%A Yingzhi Lin
%A Qingling Shi
%J Advances in Meteorology
%D 2013
%I Hindawi Publishing Corporation
%R 10.1155/2013/297926
%X This simulation-based research produces a set of forecast land use data of Qinghai Province, China, applying the land use change dynamics (LUCD) model. The simulation results show that the land use pattern will almost keep being consistent in the period from 2010 to 2050 with that in 2000 in Qinghai Province. Grassland and barren or sparsely vegetated land will cover more than 80% of the province¡¯s total area. The land use change will be inconspicuous in the period from 2010 to 2050 involving only 0.49% of the province¡¯s land. The expansion of urban and built-up land, grassland, and barren or sparsely vegetated land and the area reduction of mixed dryland/irrigated cropland and pasture, water bodies, and snow or ice will dominate land use changes of the case study area. The changes of urban and built-up land and mixed dryland/irrigated cropland and pasture will slow down over time. Meanwhile, the change rates of water bodies, snow and ice, barren or sparsely vegetated land, and grassland will show an inverted U-shaped trajectory. Except for providing underlying surfaces for RCMs for future climate change assessment, this empirical research of regional land use change may enhance the understanding of land surface system dynamics. 1. Introduction Land use change and the resulting changes in land surface characteristics are recognized drivers of climate change [1¨C3]. The biogeochemical impacts of land use change on the climate through changing atmospheric concentrations of greenhouse gases (GHGs) have been of great concern. For instance, the GHGs from agriculture land uses are estimated to account for 10¨C20% of the total global anthropogenic emissions [4]. The gross CO2 emissions from tropical deforestation are roughly equivalent to 40% of global fossil fuel emissions from 1990 to 2007 [5]. Besides lands under management, natural land cover types such as wetlands and primeval forest are also found to be large sources and sinks of GHGs [6]. Land use change affects climate by not only impacting GHG emissions but also land surface properties. Urban heat island (UHI) is one of the most noticeable effects of land surface property changes on local climate change [7¨C9]. Land use change may result in changes of thermal properties (albedo, thermal conductivity, and emissivity) and further affect the surface energy budgets as well as atmospheric circulations [10¨C13]. Consequently, land use data should play a central role in climate change assessment. While the importance of land use change in climate change modeling has been fully realized, most regional climate
%U http://www.hindawi.com/journals/amete/2013/297926/